156gd anti cd14 Search Results


93
fluidigm 3156009b
Antibody master mix
3156009b, supplied by fluidigm, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/156gd+anti+cd14/pmc09136353-94-8-5?v=fluidigm
Average 93 stars, based on 1 article reviews
3156009b - by Bioz Stars, 2026-08
93/100 stars
  Buy from Supplier

93
fluidigm cd14
Experimental approach and sample processing workflow (A) Patient samples were obtained from a biobank constructed as a part of the Clinical Trials in Organ Transplantation-06 (CTOTC-06) study. Patients were classified as “stable” if they had no evidence of rejection for 12 months before and 12 months after sample collection; patients were classified as “rejection” if they developed biopsy-proven rejection 30 days or less after sample collection. (B) PBMCs from donors were thawed, “barcoded” with palladium isotopes, stained with a combination of intracellular and extracellular markers, and analyzed on a mass cytometer. Normalized and debarcoded mass cytometer data were analyzed as described in . (C) For each patient sample, live singlets were identified based on DNA content, event length, and live/dead staining. Twenty-nine subpopulations were identified using previously published combinations of surface and intracellular markers. (D) The events in the terminally differentiated branches of the tree outlined in (C) from all clinical samples were pooled and used to construct a single-cell UMAP (clustering markers CCR7, CD8, CD45RA, CD25, CD3, CD5, CD4, FOXP3, CD56, CD38, GzmB, CD16, CD19, CD20, <t>CD14,</t> TCRγδ, CD11c, CD25, LAG3) to show the phenotypic relationship between the terminally differentiated populations. Cells are colored by their manually gated population. (E) Hierarchically clustered heatmap visualizes the relationships between populations and correlations between marker expression. The median expression of each marker used for gating was then assessed for each of the populations identified in (C).
Cd14, supplied by fluidigm, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/156gd+anti+cd14/pmc10439249-26-0-6?v=fluidigm
Average 93 stars, based on 1 article reviews
cd14 - by Bioz Stars, 2026-08
93/100 stars
  Buy from Supplier

Image Search Results


Antibody master mix

Journal: STAR Protocols

Article Title: Murine brain tumor microenvironment immunophenotyping using mass cytometry

doi: 10.1016/j.xpro.2022.101357

Figure Lengend Snippet: Antibody master mix

Article Snippet: Anti-Mouse CD14 (Sa14-2)-156Gd—100 Tests , Fluidigm , SKU# 3156009B.

Techniques:

Journal: STAR Protocols

Article Title: Murine brain tumor microenvironment immunophenotyping using mass cytometry

doi: 10.1016/j.xpro.2022.101357

Figure Lengend Snippet:

Article Snippet: Anti-Mouse CD14 (Sa14-2)-156Gd—100 Tests , Fluidigm , SKU# 3156009B.

Techniques: Purification, Recombinant, Red Blood Cell Lysis, Centrifugation, Staining, Electron Microscopy, Antibody Labeling, Software, Sterility, Spectrophotometry

Experimental approach and sample processing workflow (A) Patient samples were obtained from a biobank constructed as a part of the Clinical Trials in Organ Transplantation-06 (CTOTC-06) study. Patients were classified as “stable” if they had no evidence of rejection for 12 months before and 12 months after sample collection; patients were classified as “rejection” if they developed biopsy-proven rejection 30 days or less after sample collection. (B) PBMCs from donors were thawed, “barcoded” with palladium isotopes, stained with a combination of intracellular and extracellular markers, and analyzed on a mass cytometer. Normalized and debarcoded mass cytometer data were analyzed as described in . (C) For each patient sample, live singlets were identified based on DNA content, event length, and live/dead staining. Twenty-nine subpopulations were identified using previously published combinations of surface and intracellular markers. (D) The events in the terminally differentiated branches of the tree outlined in (C) from all clinical samples were pooled and used to construct a single-cell UMAP (clustering markers CCR7, CD8, CD45RA, CD25, CD3, CD5, CD4, FOXP3, CD56, CD38, GzmB, CD16, CD19, CD20, CD14, TCRγδ, CD11c, CD25, LAG3) to show the phenotypic relationship between the terminally differentiated populations. Cells are colored by their manually gated population. (E) Hierarchically clustered heatmap visualizes the relationships between populations and correlations between marker expression. The median expression of each marker used for gating was then assessed for each of the populations identified in (C).

Journal: Cell Reports Medicine

Article Title: High-dimensional profiling of pediatric immune responses to solid organ transplantation

doi: 10.1016/j.xcrm.2023.101147

Figure Lengend Snippet: Experimental approach and sample processing workflow (A) Patient samples were obtained from a biobank constructed as a part of the Clinical Trials in Organ Transplantation-06 (CTOTC-06) study. Patients were classified as “stable” if they had no evidence of rejection for 12 months before and 12 months after sample collection; patients were classified as “rejection” if they developed biopsy-proven rejection 30 days or less after sample collection. (B) PBMCs from donors were thawed, “barcoded” with palladium isotopes, stained with a combination of intracellular and extracellular markers, and analyzed on a mass cytometer. Normalized and debarcoded mass cytometer data were analyzed as described in . (C) For each patient sample, live singlets were identified based on DNA content, event length, and live/dead staining. Twenty-nine subpopulations were identified using previously published combinations of surface and intracellular markers. (D) The events in the terminally differentiated branches of the tree outlined in (C) from all clinical samples were pooled and used to construct a single-cell UMAP (clustering markers CCR7, CD8, CD45RA, CD25, CD3, CD5, CD4, FOXP3, CD56, CD38, GzmB, CD16, CD19, CD20, CD14, TCRγδ, CD11c, CD25, LAG3) to show the phenotypic relationship between the terminally differentiated populations. Cells are colored by their manually gated population. (E) Hierarchically clustered heatmap visualizes the relationships between populations and correlations between marker expression. The median expression of each marker used for gating was then assessed for each of the populations identified in (C).

Article Snippet: CD14 , 156-Gd , HCD14 , Standard Biotools , 3156019B.

Techniques: Construct, Clinical Proteomics, Transplantation Assay, Staining, Cytometry, Marker, Expressing

Antibodies used for CyTOF staining

Journal: Cell Reports Medicine

Article Title: High-dimensional profiling of pediatric immune responses to solid organ transplantation

doi: 10.1016/j.xcrm.2023.101147

Figure Lengend Snippet: Antibodies used for CyTOF staining

Article Snippet: CD14 , 156-Gd , HCD14 , Standard Biotools , 3156019B.

Techniques:

Journal: Cell Reports Medicine

Article Title: High-dimensional profiling of pediatric immune responses to solid organ transplantation

doi: 10.1016/j.xcrm.2023.101147

Figure Lengend Snippet:

Article Snippet: CD14 , 156-Gd , HCD14 , Standard Biotools , 3156019B.

Techniques: Recombinant, Antibody Labeling, Staining, Blocking Assay, Software