{"title":"AtaGenix ELISA Kits","description":"\u003cp\u003eELISA kits from AtaGenix Laboratories for quantitative detection of proteins and biomarkers in research samples.\u003c\/p\u003e","products":[{"product_id":"bsa-elisa-kit-bhe21400006","title":"BSA ELISA KIT","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eBSA ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eBSA\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1-32 ng\/mL; analytical sensitivity 1 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eBSA\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=BSA - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=BSA - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=BSA - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=BSA - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=BSA --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047343808877,"sku":"BY411018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_65b5337c-e9ff-483f-aaf9-1c7460981538.png?v=1772020746"},{"product_id":"human-amyloid-1-42-elisa-kit-bhe21400004","title":"Human β-Amyloid (1-42) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHuman β Amyloid (1-42) ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eβ Amyloid (1-42)\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1–100ng\/mL; analytical sensitivity 200 pg\/ml. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eβ Amyloid (1-42)\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=%CE%B2+Amyloid+%281-42%29 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=%CE%B2+Amyloid+%281-42%29 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=%CE%B2+Amyloid+%281-42%29 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=%CE%B2+Amyloid+%281-42%29 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=%CE%B2+Amyloid+%281-42%29 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047343841645,"sku":"HY235018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_9c9a3730-4c07-44ee-8859-42543ca3b66f.png?v=1772020748"},{"product_id":"sars-cov-2-surrogate-virus-neutralization-test-kit-jn-1-bhe21400013","title":"SARS-CoV-2 Surrogate Virus Neutralization Test Kit (JN.1)","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 Surrogate Virus Neutralization Test Kit (JN.1)\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSARS-CoV-2 Neutralization Antibody\u003c\/strong\u003e (SARS-CoV-2) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 31.25 - 2000 ng\/mL; analytical sensitivity 16.81 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 Neutralization Antibody\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=SARS-CoV-2+Neutralization+Antibody - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=SARS-CoV-2+Neutralization+Antibody - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=SARS-CoV-2+Neutralization+Antibody - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=SARS-CoV-2+Neutralization+Antibody - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=SARS-CoV-2+Neutralization+Antibody --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047343874413,"sku":"AK565098-96T","price":1598.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_ee3afa6f-1ecf-4547-beb1-9f5e09724381.png?v=1772020745"},{"product_id":"pedv-np-nucleoprotein-elisa-kit-bhe21400010","title":"PEDV NP\/Nucleoprotein ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePEDV NP\/Nucleoprotein ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eNP\u003c\/strong\u003e (PEDV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eNP\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=NP - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=NP - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=NP - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=NP - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=NP --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047343907181,"sku":"VK727018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_de03f1ad-d238-4223-8cc5-ca331b8713df.png?v=1772020743"},{"product_id":"satralizumab-elisa-kit-bhe21400028","title":"Satralizumab ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSatralizumab ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSatralizumab\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSatralizumab\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Satralizumab - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Satralizumab - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Satralizumab - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Satralizumab - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Satralizumab --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047343972717,"sku":"DY583028-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_04ea85a3-bc71-4f5a-a014-3a14551f1d37.png?v=1772020746"},{"product_id":"human-epo-erythropoietin-elisa-kit-bhe21400009","title":"Human EPO\/Erythropoietin ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHuman EPO\/Erythropoietin ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eEPO\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eEPO\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=EPO - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=EPO - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=EPO - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=EPO - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=EPO --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047343939949,"sku":"HF703018-96T","price":616.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_437379f0-5a34-4ac8-abcf-d97a55ebc1d9.png?v=1772020747"},{"product_id":"cgmp-elisa-kit-bhe21400007","title":"cGMP ELISA KIT","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ecGMP ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003ecGMP\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.78-100 pmol\/mL; analytical sensitivity 0.78 pmol\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eGuanosine 3’, 5’-cyclic monophosphate (cGMP) is a key second messenger molecule in intracellular signal transduction. Monitoring cGMP levels is one of the most common ways to screen for agonists and antagonists of G protein–coupled receptors(GPCRs). Bioyeargene cGMP ELISA Kit is based on the competition between HRP-labeled cGMP and free cGMP for fixed amounts of mouse monoclonal anti-cAMP antibody(cGMP MAb) binding sites. Because the concentration of the HRP-labeled cGMP is held constant while the concentration of cGMP varies, the amount of HRP-labeled cGMP that is able to bind to the cGMP MAb will be inversely proportional to the concentration of cGMP in the well. This antigen-antibody complex binds to the goat anti-mouse IgG that has been previously attached to the well. The plate is washed to remove any unbound reagents and then developed. The ELISA typically displays an IC50 (50% B\/B0) of approximately 5 pmol\/mL and a detection limit of approximately 0.1 pmol\/mL.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=cGMP - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=cGMP - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=cGMP - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=cGMP - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=cGMP --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344005485,"sku":"YA864018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_6770ab81-5c99-4e02-969c-9f181adaaaea.png?v=1772020746"},{"product_id":"orforglipron-elisa-kit-bhe21400024","title":"Orforglipron ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eOrforglipron ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eOrforglipron\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eOrforglipron\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Orforglipron - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Orforglipron - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Orforglipron - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Orforglipron - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Orforglipron --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344038253,"sku":"DW328048-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_65dee680-a5a9-4db0-8d22-d71e34110050.png?v=1772020741"},{"product_id":"tau-pt217-elisa-kit-bhe21400001","title":"TAU pT217 ELISA KIT","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTAU pT217 ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eTAU pT181\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.17-800pg\/mL; analytical sensitivity 1.17 pg\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThis gene encodes the microtubule-associated protein tau (MAPT) whose transcript undergoes complex, regulated alternative splicing, giving rise to several mRNA species. MAPT transcripts are differentially expressed in the nervous system, depending on stage of neuronal maturation and neuron type. MAPT gene mutations have been associated with several neurodegenerative disorders such as Alzheimer's disease, Pick's disease, frontotemporal dementia, cortico-basal degeneration and progressive supranuclear palsy.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=TAU+pT181 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=TAU+pT181 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=TAU+pT181 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=TAU+pT181 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=TAU+pT181 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344071021,"sku":"HY086028-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_77bb7d88-6a9a-4d35-b5ea-0fd4540b84e3.png?v=1772020745"},{"product_id":"teriparatide-elisa-kit-bhe21400020","title":"Teriparatide ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTeriparatide ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eTeriparatide\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTeriparatide\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Teriparatide - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Teriparatide - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Teriparatide - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Teriparatide - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Teriparatide --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344103789,"sku":"DF921018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_5c192c8c-dcd7-4468-97cd-6437530c42d4.png?v=1772020748"},{"product_id":"pegfilgrastim-elisa-kit-bhe21400021","title":"Pegfilgrastim ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePegfilgrastim ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003ePegfilgrastim\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePegfilgrastim\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Pegfilgrastim - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Pegfilgrastim - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Pegfilgrastim - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Pegfilgrastim - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Pegfilgrastim --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344136557,"sku":"DY258018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_621254e7-90ce-4587-bf81-8308ae48abf7.png?v=1772020746"},{"product_id":"dulaglutide-elisa-kit-bhe21400025","title":"Dulaglutide ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDulaglutide ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eDulaglutide\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eDulaglutide\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Dulaglutide - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Dulaglutide - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Dulaglutide - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Dulaglutide - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Dulaglutide --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344169325,"sku":"DW328038-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_2e7219b8-bfa0-441a-907c-3b05fe14500d.png?v=1772020746"},{"product_id":"liraglutide-elisa-kit-bhe21400026","title":"Liraglutide ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eLiraglutide ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eLiraglutide\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eLiraglutide\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Liraglutide - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Liraglutide - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Liraglutide - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Liraglutide - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Liraglutide --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344234861,"sku":"DW328018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_3a2a2ead-838b-4e50-9728-a602718260b3.png?v=1772020742"},{"product_id":"insulin-lispro-elisa-kit-bhe21400017","title":"Insulin Lispro ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eInsulin Lispro ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eInsulin Lispro\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eInsulin Lispro\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Insulin+Lispro - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Insulin+Lispro - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Insulin+Lispro - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Insulin+Lispro - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Insulin+Lispro --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344202093,"sku":"DF990038-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_c00e1758-a272-401e-b5d2-d67ba6606f56.png?v=1772020745"},{"product_id":"hsv-2-hhv-2-us8-ge-elisa-kit-bhe21400042","title":"HSV-2\/HHV-2 US8\/gE ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHSV-2\/HHV-2 US8\/gE ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eUS8\u003c\/strong\u003e (HSV-2\/HHV-2) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eUS8\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=US8 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=US8 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=US8 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=US8 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=US8 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344300397,"sku":"VK697018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_e156e2cd-1109-4195-b1bb-f76f43fdecc1.png?v=1772020749"},{"product_id":"tau-pt181-elisa-kit-bhe21400002","title":"TAU pT181 ELISA KIT","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTAU pT181 ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eTAU pT181\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56-600pg\/mL; analytical sensitivity 1.56 pg\/ml. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThis gene encodes the microtubule-associated protein tau (MAPT) whose transcript undergoes complex, regulated alternative splicing, giving rise to several mRNA species. MAPT transcripts are differentially expressed in the nervous system, depending on stage of neuronal maturation and neuron type. MAPT gene mutations have been associated with several neurodegenerative disorders such as Alzheimer's disease, Pick's disease, frontotemporal dementia, cortico-basal degeneration and progressive supranuclear palsy.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=TAU+pT181 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=TAU+pT181 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=TAU+pT181 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=TAU+pT181 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=TAU+pT181 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344267629,"sku":"HY086018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_cb094c08-85ea-4a10-b124-c5c6a4f73ec9.png?v=1772020746"},{"product_id":"hsv-2-hhv-2-gd-us6-elisa-kit-bhe21400043","title":"HSV-2\/HHV-2 gD\/US6 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHSV-2\/HHV-2 gD\/US6 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003egD\u003c\/strong\u003e (HSV-2\/HHV-2) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003egD\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=gD - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=gD - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=gD - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=gD - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=gD --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344333165,"sku":"VK737018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_99e2789f-d098-4996-a1d5-b685cb944341.png?v=1772020744"},{"product_id":"treponema-pallidum-tpp17-elisa-kit-bhe21400034","title":"Treponema pallidum TPP17 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTreponema pallidum TPP17 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eTPP17\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTPP17\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=TPP17 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=TPP17 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=TPP17 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=TPP17 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=TPP17 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344365933,"sku":"JN980018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_166597a2-35c0-4a2b-bc57-c1fb569bd3d8.png?v=1772020746"},{"product_id":"hmpv-n-nucleoprotein-elisa-kit-bhe21400029","title":"HMPV N\/Nucleoprotein ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHMPV N\/Nucleoprotein ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eN\u003c\/strong\u003e (HMPV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eN\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=N - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=N - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=N - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=N - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=N --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344398701,"sku":"VK571018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_4c6a8e52-022b-4dd9-9593-21564e98ec20.png?v=1772020744"},{"product_id":"human-amyloid-1-40-elisa-kit-bhe21400003","title":"Human β-Amyloid (1-40) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHuman β Amyloid (1-40) ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eβ Amyloid (1-40)\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1–100ng\/mL; analytical sensitivity 200 pg\/ml. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eβ Amyloid (1-40)\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=%CE%B2+Amyloid+%281-40%29 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=%CE%B2+Amyloid+%281-40%29 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=%CE%B2+Amyloid+%281-40%29 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=%CE%B2+Amyloid+%281-40%29 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=%CE%B2+Amyloid+%281-40%29 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344464237,"sku":"HY235028-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_1f9f727f-da24-4918-9e2f-2c3b4c6a3c7b.png?v=1772020747"},{"product_id":"anti-marv-envelope-glycoprotein-gp-human-igg-elisa-kit-bhe21400054","title":"Anti-MARV Envelope glycoprotein (GP) Human IgG ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-MARV Envelope glycoprotein (GP) Human IgG ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eEnvelope glycoprotein\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 1.19 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eEnvelope glycoprotein\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Envelope+glycoprotein - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Envelope+glycoprotein - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Envelope+glycoprotein - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Envelope+glycoprotein - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Envelope+glycoprotein --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344431469,"sku":"AK669018-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_cddf8519-2fe4-48a7-994e-dad9323dce10.png?v=1772020747"},{"product_id":"hmpv-f-fusion-glycoprotein-f0-elisa-kit-bhe21400031","title":"HMPV F\/Fusion glycoprotein F0 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHMPV F\/Fusion glycoprotein F0 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eF\u003c\/strong\u003e (HMPV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eF\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=F - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=F - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=F - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=F - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=F --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344497005,"sku":"VK430018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_d26d59ac-7c9b-4904-b780-27fef3003414.png?v=1772020747"},{"product_id":"insulin-aspart-elisa-kit-bhe21400018","title":"Insulin Aspart ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eInsulin Aspart ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eInsulin Aspart\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eInsulin Aspart\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Insulin+Aspart - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Insulin+Aspart - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Insulin+Aspart - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Insulin+Aspart - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Insulin+Aspart --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344529773,"sku":"DF990028-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_cab89a4a-08fb-4076-805f-bed6c623a84f.png?v=1772020747"},{"product_id":"retatrutide-elisa-kit-bhe21400023","title":"Retatrutide ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eRetatrutide ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eRetatrutide\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eRetatrutide\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Retatrutide - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Retatrutide - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Retatrutide - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Retatrutide - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Retatrutide --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344562541,"sku":"DW328058-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_c93d4363-77e9-4400-b4c3-9e29ec847595.png?v=1772020745"},{"product_id":"sars-cov-2-surrogate-virus-neutralization-test-kit-kp-2-bhe21400012","title":"SARS-CoV-2 Surrogate Virus Neutralization Test Kit (KP.2)","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 Surrogate Virus Neutralization Test Kit (KP.2)\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSARS-CoV-2 Neutralization Antibody\u003c\/strong\u003e (SARS-CoV-2) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 23.44 - 1500 ng\/mL; analytical sensitivity 13.45 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 Neutralization Antibody\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=SARS-CoV-2+Neutralization+Antibody - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=SARS-CoV-2+Neutralization+Antibody - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=SARS-CoV-2+Neutralization+Antibody - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=SARS-CoV-2+Neutralization+Antibody - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=SARS-CoV-2+Neutralization+Antibody --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344595309,"sku":"AK565108-96T","price":1598.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_eb41a416-e4b9-4b5a-a8f7-c48e6b50c4b0.png?v=1772020745"},{"product_id":"anti-sars-cov-2-nucleocapsid-np-mouse-igg-elisa-kit-bhe21400071","title":"Anti-SARS-CoV-2ÿNucleocapsidÿ(NP)ÿMouseÿIgGÿELISAÿKit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-SARS-CoV-2 Nucleocapsid (NP) Mouse IgG ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eNP\u003c\/strong\u003e (Mouse) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.06 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eNP\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=NP - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=NP - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=NP - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=NP - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=NP --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344660845,"sku":"AK805018-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_bb499ec5-e775-44e1-97a2-06c1bc9c8f5f.png?v=1772020748"},{"product_id":"weev-spike-glycoprotein-e2-elisa-kit-bhe21400041","title":"WEEV Spike glycoprotein E2 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eWEEV Spike glycoprotein E2 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSpike glycoprotein E2\u003c\/strong\u003e (WEEV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSpike glycoprotein E2\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Spike+glycoprotein+E2 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Spike+glycoprotein+E2 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Spike+glycoprotein+E2 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Spike+glycoprotein+E2 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Spike+glycoprotein+E2 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344628077,"sku":"VK634018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_a0e0885e-a194-412d-b707-06bddb881149.png?v=1772020743"},{"product_id":"protein-a-elisa-kit-bhe21400005","title":"Protein A ELISA KIT","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eProtein A ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eProtein A\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.078-5 ng\/mL; analytical sensitivity 20 pg\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eProtein A ELISA kit applies the quantitative sandwich enzyme immunoassay technique. The microtiter plate has been pre-coated with a monoclonal antibody specific for Protein A. Samples containing Protein A are first diluted in the Sample Diluent provided with the kits. The Denaturing Buffer is then added and mixed to dissociate the Protein A from the product antibody. The samples are then reacted in microtiter strips coated with a monoclonal anti-Protein A capture antibody. A second anti-Protein A biotinylated monoclonal antibody is simultaneously reacted forming a sandwich complex of solid phase antibody-Protein A: biotin labeled antibody. After a wash step to remove any unbound reactants, Streptavidin labeled HRP is added to each well. After a short incubation period, the strips are then reacted with TMB substrate. The enzyme-substrate reaction is terminated by addition of a sulphuric acid solution and the color change is measured spectrophotometrically at a wavelength of 450 nm. A standard curve is plotted relating the intensity of the color (OD) to the concentration of standards. The Protein A concentration in each sample is interpolated from this standard curve.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Protein+A - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Protein+A - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Protein+A - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Protein+A - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Protein+A --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344726381,"sku":"JN856018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_27b2a8f0-7521-4fed-90ed-fe40c393ba42.png?v=1772020747"},{"product_id":"hmpv-m-matrix-protein-elisa-kit-bhe21400030","title":"HMPV M\/Matrix protein ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHMPV M\/Matrix protein ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eM\u003c\/strong\u003e (HMPV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eM\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=M - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=M - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=M - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=M - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=M --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344693613,"sku":"VK777018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_0282e6f7-e61f-4161-b5e3-4b2752b0d645.png?v=1772020744"},{"product_id":"camp-elisa-kit-bhe21400008","title":"cAMP ELISA KIT","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ecAMP ELISA KIT\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003ecAMP\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56-200 pmol\/mL; analytical sensitivity 1.56 pmol\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eAdenosine 3', 5'-cyclic monophosphate (cAMP) is a key second messenger molecule in intracellular signal transduction. Monitoring cAMP levels is one of the most common ways to screen for agonists and antagonists of G protein–coupled receptors(GPCRs). Bioyeargene cAMP ELISA Kit is based on the competition between HRP-labeled cAMP and free cAMP for fixed amounts of mouse monoclonal anti-cAMP antibody(cAMP MAb) binding sites. Because the concentration of the HRP-labeled cAMP is held constant while the concentration of cAMP varies, the amount of HRP-labeled cAMP that is able to bind to the cAMP MAb will be inversely proportional to the concentration of cAMP in the well. This antigen-antibody complex binds to the goat anti-mouse IgG that has been previously attached to the well. The plate is washed to remove any unbound reagents and then developed. The ELISA typically displays an IC50(50% B\/B0) of approximately 12 pmol\/mL and a detection limit of approximately 0.15 pmol\/mL.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=cAMP - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=cAMP - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=cAMP - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=cAMP - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=cAMP --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344759149,"sku":"YP051018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_2c34f481-1fec-4c8d-a046-ce9fa6f81fb7.png?v=1772020748"},{"product_id":"sars-cov-2-rbd-kp-2-elisa-kit-bhe21400068","title":"SARS-CoV-2 RBD (KP.2) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSARS-CoV-2 RBD (KP.2) ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eRBD\u003c\/strong\u003e (SARS-CoV-2) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 15.63 - 1,000 pg\/mL; analytical sensitivity 10.01 pg\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eRBD\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=RBD - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=RBD - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=RBD - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=RBD - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=RBD --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344791917,"sku":"VK565058-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_c357e0a4-785f-4a52-9d60-071c210a70d3.png?v=1772020743"},{"product_id":"hsv-2-hhv-2-gc-ul44-elisa-kit-bhe21400045","title":"HSV-2\/HHV-2 gC\/UL44 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHSV-2\/HHV-2 gC\/UL44 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003egC\u003c\/strong\u003e (HSV-2\/HHV-2) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003egC\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=gC - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=gC - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=gC - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=gC - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=gC --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344824685,"sku":"VK701018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_4cb4fa88-d6fd-4b9c-b4e4-adf1a7f5d5d8.png?v=1772020744"},{"product_id":"hsv-1-hhv-1-gd-elisa-kit-bhe21400047","title":"HSV-1\/HHV-1 gD ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHSV-1\/HHV-1 gD ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003egD\u003c\/strong\u003e (HSV-1\/HHV-1) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003egD\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=gD - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=gD - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=gD - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=gD - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=gD --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344857453,"sku":"VK413018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_4874dfc8-04cc-4018-814d-44595b8869cd.png?v=1772020746"},{"product_id":"marv-nucleoprotein-np-elisa-kit-bhe21400051","title":"MARV Nucleoprotein (NP) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eMARV Nucleoprotein (NP) ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eNucleoprotein\u003c\/strong\u003e (MARV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.07 - 50 ng\/mL; analytical sensitivity 0.15 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eNucleoprotein\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Nucleoprotein - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Nucleoprotein - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Nucleoprotein - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Nucleoprotein - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Nucleoprotein --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344890221,"sku":"VK660018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_bf5f6bac-a6ce-4db5-9997-4ee8d9e67a7a.png?v=1772020746"},{"product_id":"pedv-spike-glycoprotein-rbd-elisa-kit-bhe21400011","title":"PEDV Spike glycoprotein (RBD) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003ePEDV Spike glycoprotein (RBD) ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSpike glycoprotein\u003c\/strong\u003e (PEDV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSpike glycoprotein\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Spike+glycoprotein - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Spike+glycoprotein - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Spike+glycoprotein - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Spike+glycoprotein - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Spike+glycoprotein --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344922989,"sku":"VK564018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_6259e1bd-2dc6-41dd-8bbc-b0a08ff846d3.png?v=1772020743"},{"product_id":"aldafermin-elisa-kit-bhe21400015","title":"Aldafermin ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAldafermin ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eAldafermin\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAldafermin\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Aldafermin - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Aldafermin - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Aldafermin - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Aldafermin - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Aldafermin --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344955757,"sku":"DF862018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_dd77dca1-9c64-4cca-ba68-dbd2e162c4ad.png?v=1772020743"},{"product_id":"anti-tirzepatide-ly3298176-human-igg-elisa-kit-bhe21400014","title":"Anti-Tirzepatide (LY3298176) Human IgG ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-Tirzepatide (LY3298176) Human IgG ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eTirzepatide\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.31 - 20 ng\/mL; analytical sensitivity 0.28 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eTirzepatide is a new molecule capable of controlling glucose blood levels by combining the dual agonism of Glucose-Dependent Insulinotropic Polypeptide (GIP) and Glucagon-Like Peptide-1 (GLP-1) receptors.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eTirzepatide\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Tirzepatide - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Tirzepatide - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Tirzepatide - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Tirzepatide - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Tirzepatide --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047344988525,"sku":"AP899028-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_c644b21f-1bec-45d5-874c-bcf4abe751c2.png?v=1772020746"},{"product_id":"albiglutide-elisa-kit-bhe21400022","title":"Albiglutide ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAlbiglutide ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eAlbiglutide\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 78.125 - 5,000 ng\/mL; analytical sensitivity 33.12 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAlbiglutide\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Albiglutide - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Albiglutide - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Albiglutide - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Albiglutide - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Albiglutide --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345021293,"sku":"DW328068-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_efb31b5d-4a18-4a4d-857c-056e7738f5df.png?v=1772020744"},{"product_id":"anti-mpxv-a29l-human-iga-elisa-kit-bhe21400084","title":"Anti-MPXV A29L Human IgA ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-MPXV A29L Human IgA ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eA29L\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.25 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eA29L\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=A29L - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=A29L - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=A29L - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=A29L - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=A29L --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345054061,"sku":"AK415048-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_5e43dde9-2b73-4b03-91d4-4472c04dbb31.png?v=1772020746"},{"product_id":"human-atp7b-elisa-kit-bhe21400036","title":"Human ATP7B ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHuman ATP7B ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eATP7B\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.78 - 50 ng\/mL; analytical sensitivity 0.13 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eATP7B\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=ATP7B - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=ATP7B - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=ATP7B - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=ATP7B - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=ATP7B --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345086829,"sku":"HW635018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_f70ad946-1457-460a-98fa-404ede549b89.png?v=1772020747"},{"product_id":"human-erbb2-elisa-kit-bhe21400067","title":"Human ERBB2 (HER2) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHuman ERBB2 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eCD340\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.78 - 50 ng\/mL; analytical sensitivity 0.13 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eCD340\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=CD340 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=CD340 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=CD340 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=CD340 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=CD340 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345119597,"sku":"HY286028-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_0008e741-13e9-4bbd-b105-e0243f038781.png?v=1772020745"},{"product_id":"eeev-spike-glycoprotein-e2-elisa-kit-bhe21400039","title":"EEEV Spike glycoprotein E2 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eEEEV Spike glycoprotein E2 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSpike glycoprotein E2\u003c\/strong\u003e (EEEV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSpike glycoprotein E2\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Spike+glycoprotein+E2 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Spike+glycoprotein+E2 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Spike+glycoprotein+E2 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Spike+glycoprotein+E2 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Spike+glycoprotein+E2 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345152365,"sku":"VK634038-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_ecab373d-6576-44f7-81e7-97a38424df81.png?v=1772020745"},{"product_id":"anti-mpxv-m1r-human-igm-elisa-kit-bhe21400089","title":"Anti-MPXV M1R Human IgM ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-MPXV M1R Human IgM ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eM1R\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 93.75 - 6,000 ng\/mL; analytical sensitivity 22.1 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eM1R\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=M1R - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=M1R - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=M1R - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=M1R - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=M1R --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345185133,"sku":"AK785038-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_a2a3d502-6b75-4a74-ace6-3675b4ae60dd.png?v=1772020745"},{"product_id":"human-scd14-elisa-kit-bhe21400122","title":"HumanÿsCD14 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHuman sCD14 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003esCD14\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Serum, Plasma and Cell culture supernatant. matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003esCD14\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=sCD14 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=sCD14 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=sCD14 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=sCD14 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=sCD14 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345217901,"sku":"HY038018-96T","price":546.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_de9c7a02-ae7a-4438-9c64-f1e9e77028fb.png?v=1772020748"},{"product_id":"dsrna-elisa-kit-bhe21400037","title":"dsRNA ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003edsRNA ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003edsRNA\u003c\/strong\u003e in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.43 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003edsRNA\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=dsRNA - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=dsRNA - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=dsRNA - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=dsRNA - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=dsRNA --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345250669,"sku":"YP150018-96T","price":748.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_621526d2-9c96-40a6-a7aa-71c09a3273df.png?v=1772020745"},{"product_id":"anti-sars-cov-2-spike-protein-beta-b-1-351-human-igg-elisa-kit-bhe21400081","title":"Anti-SARS-CoV-2 Spike Protein (Beta\/B.1.351) Human IgG ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-SARS-CoV-2 Spike Protein (Beta\/B.1.351) Human IgG ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSpike Protein\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.47 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSpike Protein\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Spike+Protein - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Spike+Protein - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Spike+Protein - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Spike+Protein - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Spike+Protein --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345283437,"sku":"AK474028-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_3120ced2-15ef-4921-b3b1-8b7264fa4f09.png?v=1772020745"},{"product_id":"marv-envelope-glycoprotein-gp-elisa-kit-bhe21400055","title":"MARV Envelope glycoprotein (GP) ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eMARV Envelope glycoprotein (GP) ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eEnvelope glycoprotein\u003c\/strong\u003e (MARV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 0.07 - 50 ng\/mL; analytical sensitivity 0.07 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eEnvelope glycoprotein\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Envelope+glycoprotein - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Envelope+glycoprotein - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Envelope+glycoprotein - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Envelope+glycoprotein - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Envelope+glycoprotein --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345316205,"sku":"VK669018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_ae2369ab-45b3-4a72-8c20-c4d4ef890f6c.png?v=1772020745"},{"product_id":"hmpv-g-major-surface-glycoprotein-g-elisa-kit-bhe21400032","title":"HMPV G\/Major surface glycoprotein G ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eHMPV G\/Major surface glycoprotein G ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eG\u003c\/strong\u003e (HMPV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eG\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=G - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=G - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=G - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=G - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=G --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345348973,"sku":"VK673018-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_113d0243-dcd4-4074-bd4c-70b2e6dd2db7.png?v=1772020750"},{"product_id":"anti-mpxv-m1r-human-iga-elisa-kit-bhe21400088","title":"Anti-MPXV M1R Human IgA ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eAnti-MPXV M1R Human IgA ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eM1R\u003c\/strong\u003e (Human) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.25 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eM1R\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=M1R - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=M1R - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=M1R - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=M1R - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=M1R --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345414509,"sku":"AK785048-96T","price":1398.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_856aede8-fedc-45bc-9a48-f01f2d1c2a6a.png?v=1772020747"},{"product_id":"weev-spike-glycoprotein-e1-elisa-kit-bhe21400040","title":"WEEV Spike glycoprotein E1 ELISA Kit","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eWEEV Spike glycoprotein E1 ELISA Kit\u003c\/strong\u003e is an ELISA-based immunoassay designed for quantitative measurement of \u003cstrong\u003eSpike glycoprotein E1\u003c\/strong\u003e (WEEV) in research samples. It is commonly used to generate traceable concentration data for biomarker discovery, pathway studies, and comparative analyses across experimental conditions.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay format:\u003c\/strong\u003e Quantitative Colorimetric ELISA. The format defines how signal scales with analyte abundance and how results are interpreted across a standard curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eWorking range and sensitivity:\u003c\/strong\u003e dynamic range 1.56 - 100 ng\/mL; analytical sensitivity 0.65 ng\/mL. Use these values to plan dilutions and keep readouts within the linear portion of the calibration curve.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eSample compatibility:\u003c\/strong\u003e Intended for Plasma, Serum matrices. As with most immunoassays, matrix composition can influence apparent signal and should be evaluated with dilution linearity and spike-recovery concepts.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eRecovery reference:\u003c\/strong\u003e Typical recovery is reported as 80-120%. Recovery helps assess whether the sample matrix interferes with detection of spiked analyte.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThis kit is supplied for research use in laboratory settings where defined, quantitative readouts are needed for experimental interpretation.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003e\u003cstrong\u003eSpike glycoprotein E1\u003c\/strong\u003e is a commonly studied research analyte. Its biological roles and regulation can be context-dependent (cell type, tissue state, and experimental perturbation). For authoritative gene\/protein function summaries and nomenclature, researchers typically consult curated databases.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eBiomarker translation in RUO settings:\u003c\/strong\u003e Increasing use of quantitative immunoassays to stratify experimental cohorts, track longitudinal changes, and benchmark model systems.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix-aware assay design:\u003c\/strong\u003e Greater emphasis on dilution linearity, spike-recovery, and control concepts to reduce matrix-driven artifacts in serum\/plasma and complex lysates.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIntegration with multi-omics:\u003c\/strong\u003e ELISA measurements are often used alongside transcriptomics and proteomics to connect abundance changes with pathway activity and phenotype.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eComparative quantification:\u003c\/strong\u003e Measure relative changes in analyte levels across treatments, time points, or genotypes to support mechanistic hypotheses.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eAssay development and standardization:\u003c\/strong\u003e Generate reproducible concentration inputs for method qualification, inter-operator comparisons, or bridging studies across platforms.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eModel and sample characterization:\u003c\/strong\u003e Profile baseline and stimulated levels to help interpret immune, endocrine, neurodegenerative, or metabolic phenotypes (as relevant to the target).\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eInterpretation typically focuses on direction and magnitude of change in the context of controls and sample handling metadata, rather than single-point absolute values.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eMatrix effects:\u003c\/strong\u003e Hemolysis, lipemia, and high protein content can alter background and apparent concentration. Consider consistent collection\/processing and evaluate dilution behavior.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsoforms and modified forms:\u003c\/strong\u003e Some targets exist as isoforms, fragments, or post-translationally modified species. Ensure the measured form aligns with the biological question and the kit’s intended analyte definition.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eControl concepts:\u003c\/strong\u003e Use negative\/blank controls, replicate wells, and—when feasible—orthogonal confirmation (e.g., WB or MS) to strengthen conclusions.\u003c\/li\u003e\n\u003c\/ul\u003e\u003c!-- Sources (internal): - UniProt (search): https:\/\/www.uniprot.org\/uniprotkb?query=Spike+glycoprotein+E1 - NCBI Gene (search): https:\/\/www.ncbi.nlm.nih.gov\/gene\/?term=Spike+glycoprotein+E1 - Ensembl (search): https:\/\/www.ensembl.org\/Multi\/Search\/Results?q=Spike+glycoprotein+E1 - PubMed (search): https:\/\/pubmed.ncbi.nlm.nih.gov\/?term=Spike+glycoprotein+E1 - NCBI Bookshelf (background reviews): https:\/\/www.ncbi.nlm.nih.gov\/books\/?term=Spike+glycoprotein+E1 --\u003e","brand":"AtaGenix Laboratories","offers":[{"title":"96 T","offer_id":53047345381741,"sku":"VK634028-96T","price":1126.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/ELISA_Kits_Display_Image_1_95b168a0-f80b-4a8f-835e-f74f95bb342e.png?v=1772020746"}],"url":"https:\/\/www.ebiohippo.com\/collections\/atagenix-elisa-kits.oembed?page=3","provider":"BioHippo","version":"1.0","type":"link"}