Journal:

Article Title: A defect in bone marrow derived dendritic cell maturation in the nonobesediabetic mouse

doi: 10.1046/j.1365-2249.2001.01473.x

Figure Lengend Snippet: Surface phenotype of bone marrow derived DC. The DC consisting of 90–95% CD11c+ cells were analysed by flow cytometry for the expression of I-A, β2-microglobulin, CD80, CD86 and CD40 (▪) or by staining with secondary antibody alone (□). Two I-A specific mAbs, Ox-6 (shown here) or 10·2.16 were used with identical result. The results are representative of three different experiments carried out three weeks apart.

Article Snippet: The antibodies used in the study were the MHC class II specific rat antimouse I-A k clone MRC Ox-6 (Serotec, Oxford, UK) and anti-I-A g7 clone 10·2.16 (kindly provided by EP Reich, Anergen Inc), rat antimouse CD80 (B7·1) clone IG10 (Pharmingen, San Diego, USA), rat antimouse CD86 (B7·2) clone GL1 (Cambridge Bioscience, UK); rat antimouse CD40 clone 3/23 (Serotec, UK), hamster antimouse CD11c clone N-418 (produced by ICRF, London, UK); FITC-conjugated rabbit antirat Ig (Dako, Ely, UK); FITC-conjugated rabbit anti‐mouse Ig (Dako, Denmark); and mouse anti‐mouse β2-microglobulin clone S19·8 (kindly provided by M Millrain, CSC, UK).

Techniques: Derivative Assay, Flow Cytometry, Expressing, Staining

Journal: Oxidative Medicine and Cellular Longevity

Article Title: The Plant-Derived Chalcone 2,2′,5′-Trihydroxychalcone Provides Neuroprotection against Toll-Like Receptor 4 Triggered Inflammation in Microglia

doi: 10.1155/2016/6301712

Figure Lengend Snippet: 225THC treatment modulates inflammatory cell surface marker expression in LPS-treated BV2 microglia. Flow cytometric analysis of 225THC-treated BV2 microglia following LPS stimulation. (a) Representative histogram plots of BV2 cell surface CD11b, CD40, CD54, and CD68 expression following 2 μ g/mL LPS-treatment for 48 hours (unfilled histograms), versus isotype control (black-filled histograms), and in the presence of 10 μ M 225THC (grey-filled histograms). (b) Summary data showing fold changes in CD11b, CD40, CD54, or CD68 expression by mean fluorescence intensity (MFI) from 4 independent experiments. Data are mean values ± SEM where ∗ indicates p < 0.05 by Student's t -test.

Article Snippet: Cells were stained with anti-mouse CD11b-FITC, CD40-FITC, CD54-FITC, and CD68-FITC, or appropriate FITC-conjugated isotype control antibodies (Miltenyi Biotec, UK) as per the manufacturer's instructions and cell surface staining was assessed by flow cytometry (FACSCalibur running CellQuest Pro; Becton Dickinson, UK) and analysed using Flowing software v2.5.1.

Techniques: Marker, Expressing, Control, Fluorescence

Journal: iScience

Article Title: Temporal and spatial dynamics of immune cells in spontaneous liver transplant tolerance

doi: 10.1016/j.isci.2023.107691

Figure Lengend Snippet: List of metal-labeled antibodies used for mass cytometry

Article Snippet: Anti-CD40 , Fluidigm , 3161020C.

Techniques:

Journal: iScience

Article Title: Temporal and spatial dynamics of immune cells in spontaneous liver transplant tolerance

doi: 10.1016/j.isci.2023.107691

Figure Lengend Snippet:

Article Snippet: Anti-CD40 , Fluidigm , 3161020C.

Techniques: Transplantation Assay, Recombinant, Staining, Cell Isolation, Software, Cytometry, Flow Cytometry

Journal: Cell

Article Title: Single-cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment

doi: 10.1016/j.cell.2018.05.060

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: SEQC is available on https://github.com/ambrosejcarr/seqc.git and Biscuit is available on https://github.com/sandhya212/BISCUIT_SingleCell_IMM_ICML_2016 . table ft1 table-wrap mode="anchored" t5 REAGENT or RESOURCE SOURCE IDENTIFIER Biological Samples Breast carcinoma Fresh operative tissue samples at MSKCC N/A Normal breast tissue Fresh operative tissue samples at MSKCC N/A Lymph node Fresh operative tissue samples at MSKCC N/A Peripheral blood Patient venipuncture at MSKCC N/A Antibodies anti-CD45 ab Biolegend RRID:AB_2566372 DAPI Stain Calbiochem SCR_014366 anti-Foxp3 ab Thermo Fisher RRID:AB_1834364 anti-CD3 ab Biolegend RRID:AB_1575008 anti-CD4 ab Biolegend RRID:AB_571945 anti-CD16 ab Biolegend RRID:AB_314207 anti-CD56 ab BD Biosciences RRID:AB_396853 anti-CD8 ab Biolegend RRID:AB_528885 anti-CD19 ab Biolegend RRID:AB_2562015 anti-CD11b ab Biolegend RRID:AB_2563395 anti-CD45 Y89 Fluidigm RRID:AB_2261851 anti-CD235ab BioLegend RRID:AB_314620 anti-CD61 BioLegend RRID:AB_1227584 anti-CD196/CCR6 Pr141 Fluidigm Cat:3141014A anti-CD19 142Nd Fluidigm RRID:AB_2651155 anti-CD278/ICOS 143Nd Fluidigm Cat:3143025B anti-CD270 144Nd Fluidigm Cat:3144022B anti-CD4 145Nd Fluidigm RRID:AB_2661789 anti-CD8a 146Nd Fluidigm Cat:3146001B anti-CD11c 147Sm Fluidigm RRID:AB_2687850 anti-CD14 148Nd Fluidigm Cat:3148010B anti-CD127 149Sm Fluidigm RRID:AB_2661792 anti-TIGIT eBioscience Cat:16-9500-82 anti-CD123 151Eu Fluidigm RRID:AB_2661794 anti-CD95/Fas 152Sm Fluidigm Cat:3152017B anti-CD45RA 153Eu Fluidigm Cat:3153001B anti-TIM3 154Sm Fluidigm Cat:3154010B anti-CD39 BioLegend RRID:AB_940438 anti-CD274/PD-L1 156Gd Fluidigm Cat: 3156026B anti-CD27 158Gd Fluidigm Cat: 3158010B anti-CD357/GITR 159Tb Fluidigm Cat: 3159020B anti-CD28 160Gd Fluidigm Cat: 3160003B anti-CD152/CTLA4 161Dy Fluidigm Cat: 3161004B anti-FoxP3 162Dy Fluidigm RRID:AB_2687650 anti-CD33 163Dy Fluidigm RRID:AB_2687857 anti-CD45RO 164Dy Fluidigm Cat: 3164007B anti-CD223/LAG3 165Ho Fluidigm RRID:AB_2687859 anti-Ki67 BD RRID:AB_396287 anti-CD197/CCR7 167Er Fluidigm Cat:3167009A anti-CD154/CD40L 168Er Fluidigm Cat: 3170011B anti-CD25 169Tm Fluidigm RRID:AB_2661806 anti-CD3 170Er Fluidigm RRID:AB_2661807 anti-CD226 171Tb Fluidigm Cat: 3171013B anti-CD38 172Yb Fluidigm Cat: 3172007B anti-CD137/4–1BB 173Yb Fluidigm Cat: 3173015B anti-CD279/PD-1 174Yb Fluidigm Cat: 3174020B anti-CD194/CCR4 175Lu Fluidigm Cat: 3175021A anti-CD56 176Yb Fluidigm RRID:AB_2661813 anti-CD11b 209Bi Fluidigm Cat: 3209003B Critical Commercial Assays inDrop platform Custom-built droplet microfluidics platform; Klein et al., 2015 ; Zilionis et al., 2017 .

Techniques: Staining, Antibody Labeling, Software, Diffusion-based Assay