{"title":"Caprico Biotechnologies","description":"Products supplied by Caprico.","products":[{"product_id":"cd10-pe-cyanine7-bha19900034","title":"CD10 PE-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 PE-Cyanine7 is a Mouse monoclonal targeting CD10, supplied as a PE-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751133037,"sku":"114984","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072812769645,"sku":"114985","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072812802413,"sku":"114986","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_106378dd-2721-4304-8d8a-1028235fe384.png?v=1772634828"},{"product_id":"cd64-apc-ifluor750-bha19900004","title":"CD64 APC-iFluor750","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD64 APC-iFluor750 is a Mouse monoclonal targeting CD64, supplied as a APC-iFluor™ 750 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 10.1 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-iFluor™ 750 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (638nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 10.1, a mouse monoclonal antibody selectively binds with a 72kD single chain type I glycoprotein known as CD64 or FcγRI. CD64 is a member of the immunoglobulin superfamily. FcγRI is expressed on the cell surface in association with the γ-chain. Expression of CD64 is observed on monocytes\/macrophages, dendritic cells, and activated granulocytes. CD64 plays important role in the process of antigen capture, phagocytosis and antibody-dependent cellular cytotoxicity (ADCC).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD64 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD64-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD64-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751165805,"sku":"1145104","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810279277,"sku":"1145105","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810312045,"sku":"1145106","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_2183cad1-d0a8-4fad-8eed-c9a0fedc708d.png?v=1772634831"},{"product_id":"cd19-apc-ifluor750-bha19900002","title":"CD19 APC-iFluor750","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD19 APC-iFluor750 is a Mouse monoclonal targeting CD19, supplied as a APC-iFluor™ 750 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 4G7 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-iFluor™ 750 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (638nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 4G7 recognizes a 90-kDa CD19 antigen that is present on human B lymphocytes. The CD19 antigen is present on approximately 7 to 23% of human peripheral blood lymphocytes at all stages of B cell maturation but is lost on terminally differentiated plasma cells. CD19 does not react with resting or activated T lymphocytes, granulocytes, or monocytes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD19 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD19-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD19-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751198573,"sku":"1029104","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813949293,"sku":"1029105","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813982061,"sku":"1029106","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_1806c5b7-baee-4c25-bb69-e664749fd69d.png?v=1772634832"},{"product_id":"cd10-apc-bha19900032","title":"CD10 APC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 APC is a Mouse monoclonal targeting CD10, supplied as a APC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751231341,"sku":"114944","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813883757,"sku":"114945","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813916525,"sku":"114946","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20220531-CD10-C-1A12-APC-149AA1-in-REH-FV.jpg?v=1772634834"},{"product_id":"cd38-pe-cyanine7-bha19900003","title":"CD38 PE-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD38 PE-Cyanine7 is a Mouse monoclonal targeting CD38, supplied as a PE-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e HB7 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone HB-7, a mouse monoclonal antibody, specifically binds to the 45 kDa type II transmembrane cell surface glycoprotein known as CD38. The CD38 antigen is expressed on pre-B lymphocytes, plasma cells, thymocytes and monocytes. It is expressed at high levels on activated T lymphocytes, natural killer (NK) lymphocytes, myeloblasts, and erythroblasts. Antigen expression is detected during the early stage of T- and B-lymphocyte differentiation, then lost during the intermediate stage of maturation, only to reappear during the final stage of maturation. The CD38 antigen is expressed on 90% of CD34+ cells and is not expressed on pluripotent stem cells. It is also expressed in T- and B-acute lymphoblastic leukemia (ALL), Burkitt's lymphoma, multiple myeloma, acute myeloid leukemia (AML), and chronic lymphocytic leukemia (CLL).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD38 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD38-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD38-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751264109,"sku":"131484","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072808804717,"sku":"131485","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072808837485,"sku":"131486","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_6357e27f-556f-4249-b90e-c2dcdf0b85b7.png?v=1772634828"},{"product_id":"cd10-ifluor594-bha19900024","title":"CD10 iFluor594","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 iFluor594 is a Mouse monoclonal targeting CD10, supplied as a iFluor™ 594 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e iFluor™ 594 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eCD10 also known as common acute lymphoblastic leukemia antigen (CALLA), is a 100 kD protein having neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides. CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). In normal healthy volunteers precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cell in germinal centers.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751296877,"sku":"1039134","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072815489389,"sku":"1039135","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072815522157,"sku":"1039136","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD10-iFluor594-FR4D11-39A3F1.jpg?v=1772634836"},{"product_id":"cd1a-pe-cyanine7-bha19900012","title":"CD1a PE-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a PE-Cyanine7 is a Mouse monoclonal targeting CD1a, supplied as a PE-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751329645,"sku":"111584","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810017133,"sku":"111585","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810049901,"sku":"111586","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20210726-CD1a-OKT6-PE-Cyanine7-115A2T1-Molt-4-FV.jpg?v=1772634831"},{"product_id":"cd10-mfluor450-bha19900025","title":"CD10 mFluor450","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 mFluor450 is a Mouse monoclonal targeting CD10, supplied as a mFluor™ 450 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e mFluor™ 450 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Violet (405nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone FR4D11, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. It is also known as common acute lymphoblastic leukemia antigen (CALLA). CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). Normal, healthy precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cells the in germinal center.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751362413,"sku":"1039144","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072815292781,"sku":"1039145","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072815325549,"sku":"1039146","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20211007-CD10-FR4D11-mFluor450-39A4F1-20uL-REH-FV.jpg?v=1772634834"},{"product_id":"cd10-unconjugated-bha19900017","title":"CD10 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 Unconjugated is a Mouse monoclonal targeting CD10, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eCD10 also known as common acute lymphoblastic leukemia antigen (CALLA), is a 100 kD protein having neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides. CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). In normal healthy volunteers precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cell in germinal centers.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072751395181,"sku":"103901","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072814834029,"sku":"103903","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20160302-CD10-Purified-FR4D11-39SU1.jpg?v=1772634833"},{"product_id":"cd1a-pe-cyanine5-bha19900011","title":"CD1a PE-Cyanine5","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a PE-Cyanine5 is a Mouse monoclonal targeting CD1a, supplied as a PE-Cyanine5 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine5 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751427949,"sku":"111574","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072808608109,"sku":"111575","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072808640877,"sku":"111576","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20210504-CD1a-OKT6-PE-Cyanine5-115A3T1-Molt-4-FV.jpg?v=1772634836"},{"product_id":"cd1c-unconjugated-bha19900015","title":"CD1c Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1c Unconjugated is a Mouse monoclonal targeting CD1c, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-M241 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-M241, a mouse monoclonal antibody, specifically binds to 43 kD member of the five CD1 antigens (CD1a-e) in humans also known as R7 or M241. The CD1 molecules are type I glycoprotein with structural similarities to MHC class I and are non-covalently associated with β 2 -microglobulin, belonging to the Ig superfamily, it is expressed on the surface of B cells in lymph nodes, spleen, and blood. CD1C expression can also be induced in activated monocytes. Furthermore, CD1c is a defined marker of subsets of conventional dendritic cells (cDC2 and cDC3).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1c with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1c-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1c-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072751460717,"sku":"118501","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072816144749,"sku":"118503","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_c198a217-96e7-438b-94c0-61a9915af2d1.png?v=1772634831"},{"product_id":"cd11b-pe-bha19900071","title":"CD11b PE","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD11b PE is a Mouse monoclonal targeting CD11b, supplied as a PE format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKM1 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKM1, a mouse monoclonal antibody, binds with a 165 kDa adhesion glycoprotein present in human cells known as CD11b. CD11b associates with the 95 kDa integrin β2 (CD18) to form the CD11b\/CD18 complex, also known as Mac-1 or CR3. CD11b is expressed on activated lymphocytes, monocytes, granulocytes, and a subset of NK cells. CD11b functions in cell-cell and cell-substrate interactions and is a receptor for iC3b, CD54 (ICAM-1), CD102 (ICAM-2), and CD50 (ICAM-3).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD11b with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD11b-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD11b-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751493485,"sku":"100724","price":105.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810082669,"sku":"100725","price":230.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810115437,"sku":"100726","price":370.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/100724.jpg?v=1772634826"},{"product_id":"cd10-ifluor700-bha19900035","title":"CD10 iFluor700","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 iFluor700 is a Mouse monoclonal targeting CD10, supplied as a iFluor™ 700 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e iFluor™ 700 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (638nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751526253,"sku":"1149194","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072815784301,"sku":"1149195","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072815817069,"sku":"1149196","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_cceb371d-d4fd-4798-a65c-5ba421c7b000.png?v=1772634827"},{"product_id":"cd1a-apc-cyanine7-bha19900013","title":"CD1a APC-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a APC-Cyanine7 is a Mouse monoclonal targeting CD1a, supplied as a APC-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (638nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751559021,"sku":"111594","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072814375277,"sku":"111595","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072814408045,"sku":"111596","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_83cae5a9-d2c9-45aa-a909-50df70aeb2c7.png?v=1772634832"},{"product_id":"cd10-pe-ifluor647-bha19900036","title":"CD10 PE-iFluor647","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 PE-iFluor647 is a Mouse monoclonal targeting CD10, supplied as a PE-iFluor™ 647 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-iFluor™ 647 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751591789,"sku":"1149234","price":135.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072811753837,"sku":"1149235","price":285.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072811786605,"sku":"1149236","price":485.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_fc2b51ae-4882-486e-92a2-f20abf988ae4.png?v=1772634831"},{"product_id":"cd10-apc-ifluor700-bha19900026","title":"CD10 APC-iFluor700","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 APC-iFluor700 is a Mouse monoclonal targeting CD10, supplied as a APC-iFluor™ 700 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-iFluor™ 700 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone FR4D11, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. It is also known as common acute lymphoblastic leukemia antigen (CALLA). CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). Normal, healthy precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cells the in germinal center.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751624557,"sku":"1039174","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813719917,"sku":"1039175","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813752685,"sku":"1039176","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD10-FR4D11-APC-iFluor700.jpg?v=1772634834"},{"product_id":"cd1a-fitc-bha19900007","title":"CD1a FITC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a FITC is a Mouse monoclonal targeting CD1a, supplied as a FITC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e FITC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751657325,"sku":"111514","price":80.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813293933,"sku":"111515","price":165.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813326701,"sku":"111516","price":280.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD1a-FITC-OKT6-Figure.jpg?v=1772634834"},{"product_id":"cd1a-ifluor647-bha19900014","title":"CD1a iFluor647","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a iFluor647 is a Mouse monoclonal targeting CD1a, supplied as a iFluor™ 647 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e iFluor™ 647 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751690093,"sku":"1115124","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072809787757,"sku":"1115125","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072809820525,"sku":"1115126","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD1a-OKT6-iFluor647-1.jpg?v=1772634831"},{"product_id":"cd13-pe-cyanine5-bha19900098","title":"CD13 PE-Cyanine5","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD13 PE-Cyanine5 is a Mouse monoclonal targeting CD13, supplied as a PE-Cyanine5 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e APN\/1464 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine5 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eClone APN\/1464 recognizes cell surface CD13 antigen, a 150kDa membrane glycoprotein. The CD13 antigen is highly expressed on myeloid-derived hematopoietic cells including granulocytes, monocytes, mast cells, and GM-progenitor cells. CD13 abundantly expresses on most of the malignant cells of myeloid origin such as AML, CML and on a smaller subset of cancer cells of lymphoid origin. Normal lymphocytes, platelets and erythrocytes do not express CD13. CD13 plays and important role in phagocytosis, in the bactericidal\/tumoricidal immune process, and in the metabolism of biologically active peptides. It also serves as a receptor for human coronaviruses (HCV).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD13 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD13-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD13-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751722861,"sku":"103874","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072812343661,"sku":"103875","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072812376429,"sku":"103876","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20220509-CD13-APN-1464-PE-Cyanine5-38A3T1-in-PBMC-FV.jpg?v=1772634833"},{"product_id":"cd103-unconjugated-bha19900037","title":"CD103 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD103 Unconjugated is a Mouse monoclonal targeting CD103, supplied as a Unconjugated format for FC \/ IHC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-2474 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2a, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-2474, a monoclonal antibody specifically binds to the 150 kDa type I transmembrane glycoprotein known as integrin, alpha E (ITGAE) and human mucosal lymphocyte antigen 1. The CD103 is expressed mainly on intraepithelial lymphocytes and a small subset of peripheral lymphocytes. The expression of CD103 on lymphocytes can be induced upon activation and TGF-β stimulation. It is also expressed by hairy cell leukemia (HCL) and by some chronic B cell lymphocytic leukemias.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD103 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD103-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD103-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003cli\u003eImmunohistochemistry: assess spatial patterns of CD103 expression in tissue sections and compare regions or cell types.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072751755629,"sku":"122701","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072814440813,"sku":"122703","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_4909f7a7-10c6-4c6e-9aaa-9ceb8e2aba48.png?v=1772634831"},{"product_id":"cd11b-mfluor-450-bha19900075","title":"CD11b mFluor™ 450","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD11b mFluor™ 450 is a Mouse monoclonal targeting CD11b, supplied as a mFluor450 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKM1 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e mFluor450 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Violet (405nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKM1, a mouse monoclonal antibody, binds with a 165 kDa adhesion glycoprotein present in human cells known as CD11b. CD11b associates with the 95 kDa integrin β2 (CD18) to form the CD11b\/CD18 complex, also known as Mac-1 or CR3. CD11b is expressed on activated lymphocytes, monocytes, granulocytes, and a subset of NK cells. CD11b functions in cell-cell and cell-substrate interactions and is a receptor for iC3b, CD54 (ICAM-1), CD102 (ICAM-2), and CD50 (ICAM-3).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD11b with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD11b-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD11b-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751788397,"sku":"1007144","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072811819373,"sku":"1007145","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072811852141,"sku":"1007146","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/1007144.jpg?v=1772634839"},{"product_id":"cd1a-pe-bha19900008","title":"CD1a PE","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a PE is a Mouse monoclonal targeting CD1a, supplied as a PE format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751821165,"sku":"111524","price":105.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072809263469,"sku":"111525","price":230.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072809296237,"sku":"111526","price":370.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20200917-CD1a-OKT6-PE-in-MOLT4-FV.jpg?v=1772634834"},{"product_id":"cd1c-percp-cyanine5-5-bha19900016","title":"CD1c PerCP-Cyanine5.5","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1c PerCP-Cyanine5.5 is a Mouse monoclonal targeting CD1c, supplied as a PerCP-Cyanine5.5 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-M241 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PerCP-Cyanine5.5 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-M241, a mouse monoclonal antibody, specifically binds to 43 kD member of the five CD1 antigens (CD1a-e) in humans also known as R7 or M241. The CD1 molecules are type I glycoprotein with structural similarities to MHC class I and are non-covalently associated with β 2 -microglobulin, belonging to the Ig superfamily, it is expressed on the surface of B cells in lymph nodes, spleen, and blood. CD1C expression can also be induced in activated monocytes. Furthermore, CD1c is a defined marker of subsets of conventional dendritic cells (cDC2 and cDC3).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1c with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1c-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1c-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751853933,"sku":"118564","price":135.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813654381,"sku":"118565","price":285.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813687149,"sku":"118566","price":485.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_0d736f2b-0f86-49e4-9a24-7f8e55ce2ef6.png?v=1772634829"},{"product_id":"cd127-fitc-bha19900055","title":"CD127 FITC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD127 FITC is a Mouse monoclonal targeting CD127, supplied as a FITC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 4G8 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e FITC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 4G8, a mouse monoclonal antibody selectively recognizes a 60-90 kDa surface type 1 transmembrane glycoprotein antigen known as CD127 or IL-7 receptor α chain (IL-7Rα). CD127 forms a heterodimer with the common γ chain of the receptors of several cytokines such as IL-2, IL-4, IL-9, IL-13, IL-15, and IL-21. It is widely expressed on different subsets of B cells, peripheral T cells and bone marrow stromal cells. CD127 plays important role in the generation of memory and effector T cells as well as functional B cells.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD127 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD127-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD127-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751886701,"sku":"123414","price":80.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813818221,"sku":"123415","price":165.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813850989,"sku":"123416","price":280.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_2f3ef862-fa68-49b9-bb57-885d27b078bc.png?v=1772634834"},{"product_id":"cd10-pe-cyanine7-bha19900022","title":"CD10 PE-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 PE-Cyanine7 is a Mouse monoclonal targeting CD10, supplied as a PE-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eCD10 also known as common acute lymphoblastic leukemia antigen (CALLA), is a 100 kD protein having neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides. CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). In normal healthy volunteers precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cell in germinal centers.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751919469,"sku":"103984","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810475885,"sku":"103985","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810508653,"sku":"103986","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103984-CD10FR4D11PECy7-1.jpg?v=1772634834"},{"product_id":"cd10-apc-bha19900020","title":"CD10 APC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 APC is a Mouse monoclonal targeting CD10, supplied as a APC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eCD10 also known as common acute lymphoblastic leukemia antigen (CALLA), is a 100 kD protein having neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides. CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). In normal healthy volunteers precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cell in germinal centers.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751952237,"sku":"103944","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072807985517,"sku":"103945","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072808018285,"sku":"103946","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103944.jpg?v=1772634832"},{"product_id":"cd10-fitc-bha19900030","title":"CD10 FITC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 FITC is a Mouse monoclonal targeting CD10, supplied as a FITC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e FITC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752017773,"sku":"114914","price":80.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072809001325,"sku":"114915","price":165.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072809034093,"sku":"114916","price":280.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20220408-CD10-C-1A12-FITC-149AF1-REH-FV.jpg?v=1772634825"},{"product_id":"cd11b-apc-bha19900072","title":"CD11b APC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD11b APC is a Mouse monoclonal targeting CD11b, supplied as a APC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKM1 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKM1, a mouse monoclonal antibody, binds with a 165 kDa adhesion glycoprotein present in human cells known as CD11b. CD11b associates with the 95 kDa integrin β2 (CD18) to form the CD11b\/CD18 complex, also known as Mac-1 or CR3. CD11b is expressed on activated lymphocytes, monocytes, granulocytes, and a subset of NK cells. CD11b functions in cell-cell and cell-substrate interactions and is a receptor for iC3b, CD54 (ICAM-1), CD102 (ICAM-2), and CD50 (ICAM-3).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD11b with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD11b-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD11b-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072751985005,"sku":"100744","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072816570733,"sku":"100745","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072816603501,"sku":"100746","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/100744.jpg?v=1772634829"},{"product_id":"cd117-apc-cyanine7-bha19900049","title":"CD117 APC-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD117 APC-Cyanine7 is a Mouse monoclonal targeting CD117, supplied as a APC-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e BA7.3C.9 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2a, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eClone BA7.3C.9 reacts with CD117, a 145 kDa type I transmembrane glycoprotein in the receptor tyrosine kinase (RTK) family. The CD117 antigen is also known as c-kit and stem cell factor receptor (SCFR). The CD117 antigen is expressed primarily on hematopoietic progenitor cells, mast cells and neural crest-derived melanocytes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD117 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD117-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD117-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752050541,"sku":"103594","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072814473581,"sku":"103595","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072814506349,"sku":"103596","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20210823-CD117-BA7.3C.9-APC-Cyanine7-35A4T1-K562-FV.jpg?v=1772634835"},{"product_id":"cd117-pe-bha19900044","title":"CD117 PE","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD117 PE is a Mouse monoclonal targeting CD117, supplied as a PE format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e BA7.3C.9 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2a, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eClone BA7.3C.9 reacts with CD117, a 145 kDa type I transmembrane glycoprotein in the receptor tyrosine kinase (RTK) family. The CD117 antigen is also known as c-kit and stem cell factor receptor (SCFR). The CD117 antigen is expressed primarily on hematopoietic progenitor cells, mast cells and neural crest-derived melanocytes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD117 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD117-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD117-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752083309,"sku":"103524","price":105.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810934637,"sku":"103525","price":230.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810967405,"sku":"103526","price":370.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103524.jpg?v=1772634828"},{"product_id":"cd10-pe-bha19900019","title":"CD10 PE","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 PE is a Mouse monoclonal targeting CD10, supplied as a PE format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone FR4D11, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. It is also known as common acute lymphoblastic leukemia antigen (CALLA). CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). Normal, healthy precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cells the in germinal center.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752116077,"sku":"103924","price":105.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072815915373,"sku":"103925","price":230.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072815948141,"sku":"103926","price":370.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103924.jpg?v=1772634833"},{"product_id":"cd11b-unconjugated-bha19900069","title":"CD11b Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD11b Unconjugated is a Mouse monoclonal targeting CD11b, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKM1 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKM1, a mouse monoclonal antibody, binds with a 165 kDa adhesion glycoprotein present in human cells known as CD11b. CD11b associates with the 95 kDa integrin β2 (CD18) to form the CD11b\/CD18 complex, also known as Mac-1 or CR3. CD11b is expressed on activated lymphocytes, monocytes, granulocytes, and a subset of NK cells. CD11b functions in cell-cell and cell-substrate interactions and is a receptor for iC3b, CD54 (ICAM-1), CD102 (ICAM-2), and CD50 (ICAM-3).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD11b with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD11b-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD11b-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752148845,"sku":"100701","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072809492845,"sku":"100703","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/100701.jpg?v=1772634829"},{"product_id":"cd13-unconjugated-bha19900099","title":"CD13 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD13 Unconjugated is a Mouse monoclonal targeting CD13, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e WM15 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eCD13 also known as alanyl aminopeptidase (AAP) and gp150. The clone WM15, a mouse monoclonal antibody recognizes a 150 kD type II integral membrane protein. It widely expressed in all cells of the myeloid lineage, activated endothelial cells, hematopoietic progenitor, and stem cells and not on platelets or erythrocytes. The latter enzyme was thought to be involved in the metabolism of regulatory peptides by diverse cell types. AAP is also used by some viruses as a receptor to which these viruses bind to and then enter cells.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD13 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD13-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD13-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752181613,"sku":"123901","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072812671341,"sku":"123903","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_d6eeca78-bcc9-4e37-a5d9-1b11c2bb525b.png?v=1772634829"},{"product_id":"cd10-apc-cyanine7-bha19900023","title":"CD10 APC-Cyanine7","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 APC-Cyanine7 is a Mouse monoclonal targeting CD10, supplied as a APC-Cyanine7 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-Cyanine7 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone FR4D11, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. It is also known as common acute lymphoblastic leukemia antigen (CALLA). CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). Normal, healthy precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cells the in germinal center.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752214381,"sku":"103994","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072813097325,"sku":"103995","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072813130093,"sku":"103996","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20211104-CD10-FR4D11-APC-Cyanine7-39A4T1-20uL-REH-FV.jpg?v=1772634832"},{"product_id":"cd138-unconjugated-bha19900104","title":"CD138 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD138 Unconjugated is a Mouse monoclonal targeting CD138, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e B-A38 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone B-A38, a mouse monoclonal antibody, recognizes an 85-92kDa single chain transmembrane proteoglycan known as CD138 or Syndecan-1. CD138 is commonly expressed on pre-B cells, immature B cells, plasma cells, and on some non-hematopoietic cells, including embryonic mesenchymal cells, vascular smooth muscle cells, endothelial and neural cells, on differentiating keratinocytes and in the epidermis of injured tissue. The presence of soluble CD138 (sCD138) in serum is considered as an important prognostic factor of cancerogenesis in some samples.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD138 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD138-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD138-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752247149,"sku":"113501","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072810901869,"sku":"113503","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_9636e5fe-30e9-4624-868f-dc36f17afb69.png?v=1772634832"},{"product_id":"cd105-pe-bha19900041","title":"CD105 PE","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD105 PE is a Mouse monoclonal targeting CD105, supplied as a PE format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e SN6h — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone SN6h, a mouse monoclonal antibody selectively binds to a ~95 kDa type I transmembrane homodimer glycoprotein known as CD105. It is also encoded by END (Endoglin) and belongs to the TGF-β type III receptor family. CD105 mostly expressed on vascular endothelial cells, placental syncytiotrophoblasts, mesenchymal stem cells, erythroid precursors, activated macrophages, pre-B cells, and some tumor cells and cell lines including U937 cells. CD105 works as an important regulatory component of the TGF-β receptor system. CD105 expression is increased on activated endothelium tissues undergoing angiogenesis and also in cases of wound healing or dermal inflammation. CD105 may also be involved in the solid tumor metastasis, in regulation of cytoskeletal cellular organization as well as migration.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD105 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD105-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD105-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752279917,"sku":"112524","price":105.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072808673645,"sku":"112525","price":230.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072808706413,"sku":"112526","price":370.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20210223-CD105-SN6H-PE-125AE1-Hela-FV.jpg?v=1772634831"},{"product_id":"cd15-apc-ifluor700-bha19900142","title":"CD15 APC-iFluor700","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD15 APC-iFluor700 is a Mouse monoclonal targeting CD15, supplied as a APC-iFluor™ 700 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FUT4\/815 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgM, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-iFluor™ 700 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone FUT4\/815 recognizes CD15, a cell surface protein (~220kDa) abundantly expressed by granulocytes and monocytes. CD15 plays important role in mediating phagocytosis, bactericidal activity, and also chemotaxis. CD15 is also expressed by Reed-Sternberg cells and some other epithelial cells. CD15 is very useful in the identification of Hodgkin s disease and also large cell lymphomas of both B and T phenotypes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD15 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD15-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD15-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752312685,"sku":"1050174","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072815849837,"sku":"1050175","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072815882605,"sku":"1050176","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20220919-CD15-FUT4-815-APC-iFluor700-50A7T1-20uL-PBMC-FV.jpg?v=1772634832"},{"product_id":"cd14-percp-bha19900116","title":"CD14 PerCP","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD14 PerCP is a Mouse monoclonal targeting CD14, supplied as a PerCP format for FC workflows. It supports measurement of Baboon, Cynomolgus monkey, Human, Rhesus target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 26ic — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PerCP — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Baboon, Cynomolgus monkey, Human, Rhesus — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 26ic, a mouse monoclonal antibody, reacts with a human 53-55 kDa glycosylphosphatidylinositol (GPI)-anchored single chain cell surface antigen known as CD14. The CD14 expression is commonly observed on monocytes, interfollicular macrophages, reticular dendritic cells and some Langerhans cells. 26ic binds with a complex of LPS and lipopolysaccharide binding protein, and blockade of CD14 with monoclonal antibodies prevented the synthesis of TNF-alpha by LPS activated leukocytes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD14 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD14-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD14-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752345453,"sku":"103434","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072811950445,"sku":"103435","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072811983213,"sku":"103436","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD14-PerCP-26ic-34AC1-1.jpg?v=1772634832"},{"product_id":"cd1a-unconjugated-bha19900006","title":"CD1a Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a Unconjugated is a Mouse monoclonal targeting CD1a, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752378221,"sku":"111501","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072811917677,"sku":"111503","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_e7a502fb-ce16-4651-91f2-a13435414149.png?v=1772634828"},{"product_id":"cd127-pe-cyanine5-bha19900058","title":"CD127 PE-Cyanine5","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD127 PE-Cyanine5 is a Mouse monoclonal targeting CD127, supplied as a PE-Cyanine5 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 4G8 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE-Cyanine5 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 4G8, a mouse monoclonal antibody selectively recognizes a 60-90 kDa surface type 1 transmembrane glycoprotein antigen known as CD127 or IL-7 receptor α chain (IL-7Rα). CD127 forms a heterodimer with the common γ chain of the receptors of several cytokines such as IL-2, IL-4, IL-9, IL-13, IL-15, and IL-21. It is widely expressed on different subsets of B cells, peripheral T cells and bone marrow stromal cells. CD127 plays important role in the generation of memory and effector T cells as well as functional B cells.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD127 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD127-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD127-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752410989,"sku":"123474","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072808378733,"sku":"123475","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072808411501,"sku":"123476","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20211005-CD127-PE-Cy5-234A3T1-FV.jpg?v=1772634830"},{"product_id":"cd1a-apc-bha19900009","title":"CD1a APC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD1a APC is a Mouse monoclonal targeting CD1a, supplied as a APC format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e OKT6 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone OKT6, a mouse monoclonal antibody selectively recognizes 49-kDa type I transmembrane glycoprotein non-covalently associated with β2-microglobulin known as CD1a. The CD1a glycoprotein has structural similarities to MHC class I molecule and plays important role in antigen-presenting mechanism to T-cell receptors present on NK T-cells. It is expressed on cortical double positive and single positive thymocytes, Langerhans cells, and dendritic cells. In addition to antigen presentation NK T-cells, CD1a has been implicated in thymic T cell development. CD1a has been used as a marker for DCs in a range of human tumors and the density of CD1a DC has been associated with clinical outcome in samples with lung, colon, gastric, nasopharyngeal, laryngeal and tongue carcinomas.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD1a with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD1a-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD1a-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752443757,"sku":"111544","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810836333,"sku":"111545","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810869101,"sku":"111546","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20220421-CD1a-OKT6-APC-115AA1-20uL-Molt-4-FV.jpg?v=1772634838"},{"product_id":"cd14-apc-bha19900108","title":"CD14 APC","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD14 APC is a Mouse monoclonal targeting CD14, supplied as a APC format for FC workflows. It supports measurement of Baboon, Cynomolgus monkey, Human, Rhesus target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 26ic — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Baboon, Cynomolgus monkey, Human, Rhesus — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eClone 26ic reacts with a nonfunctional domain of human CD14, a 53-55 kDa glycosylphosphatidylinositol (GPI)-anchored and single chain glycoprotein expressed at high levels on monocytes. Additionally, CD14 reacts with interfollicular macrophages, reticular dendritic cells and some Langerhans cells. The binding of CD14 does not inhibit CD14 mediated activities, and is useful for detecting CD14 expression by immunofluorescence and or immunocytochemical methods.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD14 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD14-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD14-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752476525,"sku":"103444","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810705261,"sku":"103445","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810738029,"sku":"103446","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103444.jpg?v=1772634832"},{"product_id":"cd14-ifluor-647-bha19900125","title":"CD14 iFluor™ 647","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD14 iFluor™ 647 is a Mouse monoclonal targeting CD14, supplied as a iFluor™ 647 format for FC workflows. It supports measurement of Baboon, Cynomolgus monkey, Human, Rhesus target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e M5E2 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2a, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e iFluor™ 647 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (633nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Baboon, Cynomolgus monkey, Human, Rhesus — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone M5E2, a mouse monoclonal antibody, specifically recognizes a human 53-55 kDa glycosylphosphatidylinositol (GPI)-anchored single chain cell surface antigen known as CD14. The expression of CD14 is commonly observed on monocytes, interfollicular macrophages, reticular dendritic cells and some Langerhans cells. M5E2 binds with a complex of LPS and lipopolysaccharide binding protein, and blockade of CD14 with monoclonal antibodies prevented the synthesis of TNF-alpha by LPS activated leukocytes. M5E2 has cross-reactivity with various species including non-human rhesus macaques.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD14 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD14-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD14-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752509293,"sku":"1074124","price":110.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072811262317,"sku":"1074125","price":240.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072811295085,"sku":"1074126","price":405.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD14-iFluour647M5E2.jpg?v=1772634832"},{"product_id":"cd10-apc-ifluor750-bha19900001","title":"CD10 APC-iFluor750","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 APC-iFluor750 is a Mouse monoclonal targeting CD10, supplied as a APC-iFluor™ 750 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e APC-iFluor™ 750 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Red (638nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752542061,"sku":"1149104","price":125.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072808542573,"sku":"1149105","price":265.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072808575341,"sku":"1149106","price":445.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_dec40ad4-4a7c-4bc9-8ab8-4c42d501e20d.png?v=1772634835"},{"product_id":"cd14-unconjugated-bha19900107","title":"CD14 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD14 Unconjugated is a Mouse monoclonal targeting CD14, supplied as a Unconjugated format for FC workflows. It supports measurement of Baboon, Cynomolgus monkey, Human, Rhesus target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 26ic — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Baboon, Cynomolgus monkey, Human, Rhesus — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 26ic, a mouse monoclonal antibody, reacts with a human 53-55 kDa glycosylphosphatidylinositol (GPI)- anchored single chain cell surface antigen known as CD14. The CD14 expression is commonly observed on monocytes, interfollicular macrophages, reticular dendritic cells and some Langerhans cells. 26ic binds with a complex of LPS and lipopolysaccharide binding protein, and blockade of CD14 with monoclonal antibodies prevented the synthesis of TNF-alpha by LPS activated leukocytes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD14 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD14-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD14-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752574829,"sku":"103401","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072808444269,"sku":"103403","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/20191127-CD14-Purified-26ic-34AU5-1.jpg?v=1772634837"},{"product_id":"cd127-unconjugated-bha19900054","title":"CD127 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD127 Unconjugated is a Mouse monoclonal targeting CD127, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 4G8 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 4G8, a mouse monoclonal antibody selectively recognizes a 60-90 kDa surface type 1 transmembrane glycoprotein antigen known as CD127 or IL-7 receptor α chain (IL-7Rα). CD127 forms a heterodimer with the common γ chain of the receptors of several cytokines such as IL-2, IL-4, IL-9, IL-13, IL-15, and IL-21. It is widely expressed on different subsets of B cells, peripheral T cells and bone marrow stromal cells. CD127 plays important role in the generation of memory and effector T cells as well as functional B cells.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD127 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD127-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD127-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752640365,"sku":"123401","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072816177517,"sku":"123403","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_16057939-c462-4954-8248-d9ba4d128dea.png?v=1772634828"},{"product_id":"cd10-percp-cyanine5-5-bha19900021","title":"CD10 PerCP-Cyanine5.5","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 PerCP-Cyanine5.5 is a Mouse monoclonal targeting CD10, supplied as a PerCP-Cyanine5.5 format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e FR4D11 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PerCP-Cyanine5.5 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eCD10 also known as common acute lymphoblastic leukemia antigen (CALLA), is a 100 kD protein having neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides. CD10 is a type II cell surface glycoprotein typically expressed on acute lymphoblastic leukemias (ALL). In normal healthy volunteers precursors of B and T cells and granulocytes also express CD10. CD10 plays important role in the development process of B cell in germinal centers.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752607597,"sku":"103964","price":135.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072812966253,"sku":"103965","price":285.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072812999021,"sku":"103966","price":485.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103964.jpg?v=1772634827"},{"product_id":"cd10-unconjugated-bha19900029","title":"CD10 Unconjugated","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD10 Unconjugated is a Mouse monoclonal targeting CD10, supplied as a Unconjugated format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e C-1A12 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e Unconjugated — enables direct detection in fluorescence-based assays.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone C-1A12, a mouse monoclonal antibody recognizes a 100 kDa protein that has neutral metalloendopeptidase activity and inactivates a variety of biologically active peptides known as CD10. CD10 is type II transmembrane glycoprotein and a common acute lymphocytic leukemia antigen that is an important cell surface marker in the classification of human acute lymphocytic leukemia (ALL). The protein is present on leukemic cells of pre-B phenotype, which represent 85% of cases of ALL. CD10 plays important role in the development process of B cells the in germinal center. This protein is not restricted to leukemic cells. Normal, healthy precursors of B and T cells and granulocytes also express CD10.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD10 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD10-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD10-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"100 ug","offer_id":53072752673133,"sku":"114901","price":110.0,"currency_code":"USD","in_stock":true},{"title":"500 ug","offer_id":53072809329005,"sku":"114903","price":390.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/caprico_logo_0b659a8a-61f9-4185-a9c5-7a91ba473f79.png?v=1772634836"},{"product_id":"cd13-pe-bha19900091","title":"CD13 PE","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD13 PE is a Mouse monoclonal targeting CD13, supplied as a PE format for FC workflows. It supports measurement of Human target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e APN\/1464 — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG1, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PE — enables direct detection in fluorescence-based assays. Excitation is typically matched to Yellow (561nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Human — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eClone APN1464 recognizes cell surface CD13 antigen, a 150kDa membrane glycoprotein. The CD13 antigen is highly expressed mostly on myeloid-derived hematopoietic cells including granulocytes, monocytes, mast cells, and GM-progenitor cells. CD13 abundantly expresses on most of the malignant cells of myeloid origin such as AML, CML and also on smaller subset of cancer cells of lymphoid origin. Normal lymphocytes, platelets and erythrocytes do not express CD13. CD13 plays important role in metabolism of biologically active peptides, in phagocytosis, and in bactericidal\/tumoricidal immune process. It also serves as a receptor for human coronaviruses (HCV).\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD13 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD13-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD13-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752705901,"sku":"103824","price":105.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072810770797,"sku":"103825","price":230.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072810803565,"sku":"103826","price":370.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/103824.jpg?v=1772634831"},{"product_id":"cd14-percp-cyanine5-5-bha19900117","title":"CD14 PerCP-Cyanine5.5","description":"\u003ch2\u003eOverview\u003c\/h2\u003e\u003cp\u003eCD14 PerCP-Cyanine5.5 is a Mouse monoclonal targeting CD14, supplied as a PerCP-Cyanine5.5 format for FC workflows. It supports measurement of Baboon, Cynomolgus monkey, Human, Rhesus target expression in common experimental systems.\u003c\/p\u003e\u003ch2\u003eKey elements and design rationale\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eClone:\u003c\/strong\u003e 26ic — consistent clone identity can support panel reproducibility and cross-study comparisons.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eIsotype:\u003c\/strong\u003e IgG2b, k — informs selection of matched controls and secondary reagents when relevant.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eConjugate:\u003c\/strong\u003e PerCP-Cyanine5.5 — enables direct detection in fluorescence-based assays. Excitation is typically matched to Blue (488nm) lasers in cytometer configurations.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eHost species:\u003c\/strong\u003e Mouse — useful for panel design and control strategy planning.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eReactivity:\u003c\/strong\u003e Baboon, Cynomolgus monkey, Human, Rhesus — interpret staining in the context of species-specific sequence and expression differences.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eKey specifications such as clone identity, isotype, and fluorophore conjugation help researchers align panel design, control selection, and instrument configuration with the biological question and sample type.\u003c\/p\u003e\u003ch2\u003eBiological background\u003c\/h2\u003e\u003cp\u003eThe clone 26ic, a mouse monoclonal antibody, reacts with a human 53-55 kDa glycosylphosphatidylinositol (GPI)- anchored single chain cell surface antigen known as CD14. The CD14 expression is commonly observed on monocytes, interfollicular macrophages, reticular dendritic cells and some Langerhans cells. 26ic binds with a complex of LPS and lipopolysaccharide binding protein, and blockade of CD14 with monoclonal antibodies prevented the synthesis of TNF-alpha by LPS activated leukocytes.\u003c\/p\u003e\u003ch2\u003eResearch relevance and current trends\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eHigh-parameter immunophenotyping: combining CD14 with complementary lineage and activation markers to resolve complex cell states.\u003c\/li\u003e\n\u003cli\u003ePanel standardization and data comparability: increasing emphasis on consistent reagents, compensation-aware fluorophore choices, and shared gating strategies.\u003c\/li\u003e\n\u003cli\u003eIntegration with single-cell multi-omics: pairing surface marker profiling with transcriptomic or proteomic readouts to connect phenotype to function.\u003c\/li\u003e\n\u003c\/ul\u003e\u003ch2\u003eCommon research applications\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFlow cytometry: quantify CD14-positive populations and compare expression distributions across conditions or time points.\u003c\/li\u003e\n\u003cli\u003eCell sorting: enrich CD14-defined subsets for downstream RNA\/protein assays or functional readouts.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eChanges in measured signal are typically interpreted in the context of cell subset frequency, activation\/differentiation state, and sample processing effects rather than as a standalone readout.\u003c\/p\u003e\u003ch2\u003eNotes for experimental interpretation\u003c\/h2\u003e\u003cul\u003e\n\u003cli\u003eFluorophore selection: consider brightness, spectral overlap, and instrument configuration; compensation and spillover can affect apparent population boundaries.\u003c\/li\u003e\n\u003cli\u003eBiology-driven confounders: activation state, differentiation, and isoform\/PTM variation can shift epitope accessibility and apparent expression.\u003c\/li\u003e\n\u003cli\u003eControl concepts: include matched isotype and fluorescence-minus-one (FMO) controls where appropriate, and interpret results alongside biological positive\/negative reference samples.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eFor antibody-based assays, monoclonal versus polyclonal format can influence epitope recognition breadth and signal consistency. Conjugated antibodies support direct detection and can simplify multicolor panel design when paired with appropriate controls and instrument settings.\u003c\/p\u003e\u003c!-- Sources (internal): - UniProt Knowledgebase — UniProt — https:\/\/www.uniprot.org\/ - NCBI Gene — NCBI — https:\/\/www.ncbi.nlm.nih.gov\/gene\/ - HGNC gene nomenclature — HUGO Gene Nomenclature Committee — https:\/\/www.genenames.org\/ - Flow cytometry basics — NIH\/NCI (overview resources) — https:\/\/www.cancer.gov\/research\/resources - High-dimensional cytometry overview — Nature Methods (journal) — https:\/\/www.nature.com\/nmeth\/ --\u003e","brand":"Caprico","offers":[{"title":"25 Tests","offer_id":53072752771437,"sku":"103464","price":135.0,"currency_code":"USD","in_stock":true},{"title":"100 Tests","offer_id":53072816767341,"sku":"103465","price":285.0,"currency_code":"USD","in_stock":true},{"title":"200 Tests","offer_id":53072816800109,"sku":"103466","price":485.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0949\/7424\/7277\/files\/CD1426ic-PerCP-Cy5.5-1.jpg?v=1772634833"}],"url":"https:\/\/www.ebiohippo.com\/collections\/caprico-biotechnologies.oembed?page=27","provider":"BioHippo","version":"1.0","type":"link"}