Journal: Scientific Reports

Article Title: Application across species of a one health approach to liquid sample handling for respiratory based -omics analysis

doi: 10.1038/s41598-021-93839-9

Figure Lengend Snippet: Analysis of tracheal wash derived macrophages. Flow cytometry results showing cross-reactivity of mouse anti-human CD163 antibody against equine tracheal macrophages. (a) Isotype control, (b) CD163 stained cells (c) overlay of CD163+ population on top of total cells. (d) Leishman stained cytospin preparations of CD163+ cells by light microscopy (× 20, scale bar = 50 μm). Data and image analysis was performed in FlowJo ® v10.5.3 https://www.flowjo.com/ .

Article Snippet: Briefly, the cells were first stained with a R-Phycoerythrin (PE)-conjugated CD163 primary antibody; subsequently, the cells were magnetically labelled with anti-PE MicroBeads (Miltenyi Biotec, cat no 130-105-639) before the cell suspension was loaded on a MACS ® LS Column (Miltenyi Biotec Ltd., cat n0 130-042-401), placed in the magnetic field of a MACS Separator.

Techniques: Derivative Assay, Flow Cytometry, Control, Staining, Light Microscopy

Journal: Cell

Article Title: Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches

doi: 10.1016/j.cell.2021.12.018

Figure Lengend Snippet: Combination of CITE-seq, scRNA-seq, snRNA-seq, and spatial analyses enables generation of a human liver atlas and identification of bona fide human KCs, related to Figure 4 (A and B) Top DEGs (A) and DEPs (B) for the cell types from Figure 4 B. (C) Distinct profiles of cells or nuclei within the UMAP depending on isolation protocol used; 152,535 cells from ex vivo digestions and 15,063 nuclei. (D) Proportion of each cell type per patient profiled. (E) Proportion of indicated cell types as a % of total CD45 + cells calculated from ex vivo digested samples per surgery type. Ch; cholecystectomy, Re; resection, GB; gastric bypass. ∗ p < 0.05; one-way ANOVA with Bonferroni post-test. (F) Mapping of Visium UMAP zonation patterns onto tissue sections from patient H35 and H37. (G) Expression of indicated zonation genes in patients H35–H38 assessed by Molecular Cartography. (H and I) Expression of indicated proteins by MICS 100-plex protein analysis in the healthy (H) and steatotic (I) human liver. (J) Murine myeloid cells (cDC1s, cDC2s, Mig. cDCs, Macs, monocytes, and monocyte-derived cells; 42,922 cells) from mice fed the SD or WD for 24 or 36 weeks were isolated from Figure S5 J and re-clustered with TotalVI. (K) Distribution of cells in UMAP originating from SD- (purple) or WD- (yellow) fed mice. (L) Proportion of indicated cell types arising from mice fed the SD (purple) or WD (yellow). (M and N) Flow cytometry analysis of indicated cell populations in SD and WD-fed mice (24 weeks). Representative gating strategies (M) and absolute number of indicated populations (N). ∗ p < 0.05, ∗∗ p < 0.01 Student’s t test. Data are from 2 independent experiments with n = 5–6 per diet. (O and P) Top DEGs (O) and DEPs (P) for cell types from Figure 4 H. (Q) Top 25 Murine KC genes as expressed by the human myeloid cell clusters. (R) Mapping of KC signature onto Visium trajectory for healthy (purple) and steatotic (orange) livers. (S) Expression of VSIG4 mRNA within human myeloid cells. (T) Expression of VSIG4 (red) and CD163 (gray, top) or CD169 (gray, bottom) by MICS analysis in healthy human liver. (U) Representative images showing KC location (red) as assessed by MICS analysis in the healthy (left) and steatotic (right) human liver. PV, portal vein; CV, central Vein, dashed line indicates zones of steatosis. (V) Representative image of CD68 and CD163 staining in 10–15-year-old human liver paraffin sections. Image is representative of 6 different patients. (W) In silico gating strategy to isolate distinct myeloid cell populations identified from CITE-seq data. (X) Expression of VSIG4 and FOLR2 by live CD45 + cells also expressing CD14 in indicated human liver biopsies by flow cytometry. Data are representative of 21 biopsy samples analyzed.

Article Snippet: Anti-Human CD163 (REA406) PE , Miltenyi Biotec , 130-121-316; RRID: AB_2857545.

Techniques: Isolation, Ex Vivo, Expressing, Derivative Assay, Flow Cytometry, Staining, In Silico

Journal: Cell

Article Title: Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches

doi: 10.1016/j.cell.2021.12.018

Figure Lengend Snippet:

Article Snippet: Anti-Human CD163 (REA406) PE , Miltenyi Biotec , 130-121-316; RRID: AB_2857545.

Techniques: Purification, Recombinant, Staining, cDNA Synthesis, Gene Expression, Software, Microscopy

Journal: Frontiers in Immunology

Article Title: Increased expression of CD36 and CD163 in clear cell renal cell carcinoma suggests an association between lipid transport and an “M2-like” macrophage phenotype

doi: 10.3389/fimmu.2026.1773666

Figure Lengend Snippet: Expression of CD68 and CD163 in ccRCC samples. (A) CD68 was assessed using immunohistochemistry. (B) Expression of CD68 was assessed using the available TCGA data (KIRC dataset). Tumors were grouped by the pathological tumor size (pT). (C) CD163 was assessed using immunohistochemistry. (D) Expression of CD163 was assessed using the available TCGA data (KIRC dataset). Tumors were grouped by the pathological tumor size (pT). Student’s t-test for two groups and one-way ANOVA for four groups; *p<0.05, **p<0.01, ***p<0.001,****p<0.0001. (E) Multiplex immunofluorescence imaging of ccRCC tumor tissues (representative of three patients) depicting CK (cytokeratin), CD163 and CD68 expression. White bar represents 200 μm (left) and 10 μm (right). (F) UMAP depicting clusters of single-cell data showing the expression of CD68 and CD163. Cell type annotations were adopted from the original publication . (G) Fraction of CD68+ cells co-expressing CD163 in RCC tumor tissue macrophage population. Positivity in scRNA-seq for CD68 and CD163 was defined from raw UMI counts as ≥1 UMI per gene (F) . (H) Flow cytometric analysis of CD45 on cells from central and peripheral ccRCC tumor tissue and adjacent kidney. (I) As in (H) , analysis of CD163 on CD68+ cells from central and peripheral ccRCC tumor tissue and adjacent kidney. Values were normalized to kidney controls. Representative histogram with geometric mean fluorescence intensities on the right. One-way ANOVA with Dunnett post-test comparing to kidney. *p<0.05, **p<0.01, ***p<0.001. (J) Data from (I) , tumor periphery, plotted as individual patients, depicting the portion of CD163+ and CD163neg cells.

Article Snippet: Reagents and antibodies used included FcR Blocking Reagent (Cat# 130-059-901), CD36 PE (Cat# 130-110-877), CD147 APC (Cat# 130-124-295), CD8a PE (Cat# 130-117-201), CD45 PE (Cat# 130-113-118), CD68 PE (Cat# 130-128-345), CD163 PE (Cat# 130-127-908), and pan-Cytokeratin APC (Cat# 130-123-091), all from Miltenyi Biotec.

Techniques: Expressing, Immunohistochemistry, Multiplex Assay, Immunofluorescence, Imaging, Single Cell, Fluorescence

Journal: Frontiers in Immunology

Article Title: Increased expression of CD36 and CD163 in clear cell renal cell carcinoma suggests an association between lipid transport and an “M2-like” macrophage phenotype

doi: 10.3389/fimmu.2026.1773666

Figure Lengend Snippet: Correlations of CD36 and Oil Red O with immunological markers. Data was obtained as in Figures 1 , . Observer-based histological scores were used to calculate the correlations. As these scores are ordinal, individual data points may overlap in scatter plots. The number of overlapping values is indicated by numbers in parentheses. Correlation statistics were performed using Pearson´s correlation coefficients, and p-values were two-tailed. (A) Correlations of CD36 with CD68, CD163 and CD3. (B) Correlations of Oil Red O scores to CD68, CD163 and CD3. (C) Multiplex immunofluorescence imaging of ccRCC tumor tissues (representative of three patients) depicting CD68 and CD36 expression. (D) Flow cytometric analysis of CD36 on CD68+ cells from central and peripheral ccRCC tumor tissue and adjacent kidney. Values were normalized to kidney controls. Representative histogram with geometric mean fluorescence intensities on the right. One-way ANOVA with Dunnett post-test comparing to kidney, n.s. (E) As in (D) , correlation of CD36 and CD163 expression on CD68+ cells. (F) UMAP depicting macrophage cluster with expression of CD68, CD163 and CD36 . (G-I) Flow cytometric analysis of peripheral tumor tissues, correlating the expression of CD36 on CD45neg cells to (G) CD163 on CD68+ cells, (H) the CD68+ cell frequencies and (I) the frequencies of CD3+ CD8+ cells. Pearson´s correlation, two-tailed p-value. (J, K) Lipidomics performed on five ccRCC tumors with correlations of CD163 expression (IHC, area staining intensity in J; histological score in K) and the levels of triacylglycerol (TG).

Article Snippet: Reagents and antibodies used included FcR Blocking Reagent (Cat# 130-059-901), CD36 PE (Cat# 130-110-877), CD147 APC (Cat# 130-124-295), CD8a PE (Cat# 130-117-201), CD45 PE (Cat# 130-113-118), CD68 PE (Cat# 130-128-345), CD163 PE (Cat# 130-127-908), and pan-Cytokeratin APC (Cat# 130-123-091), all from Miltenyi Biotec.

Techniques: Two Tailed Test, Multiplex Assay, Immunofluorescence, Imaging, Expressing, Fluorescence, Staining

Journal: Frontiers in Immunology

Article Title: Increased expression of CD36 and CD163 in clear cell renal cell carcinoma suggests an association between lipid transport and an “M2-like” macrophage phenotype

doi: 10.3389/fimmu.2026.1773666

Figure Lengend Snippet: Expression of CD147 in ccRCC samples. (A) CD147 was assessed using immunohistochemistry. Student’s t-test, *p<0.05. (B) Expression of CD147 was assessed using the available TCGA data (KIRC dataset). (C) Correlations of CD147 expression to CD36 and CD163 using area staining intensity. (D) Correlations of CD147 expression to CD36 and CD163 using observer-based histological scores. As these scores are ordinal, individual data points may overlap in scatter plots. The number of overlapping values is indicated by numbers in parentheses. Correlation statistics were performed using Pearson´s correlation coefficients, and p-values were two-tailed. (E) Flow cytometric analysis of CD147 on CD45neg cells from central and peripheral ccRCC tumor tissue and adjacent kidney. Values were normalized to kidney controls. Representative histogram with geometric mean fluorescence intensities on the right. (F) As in (E) , correlations of CD147 expression on CD45neg cells to CD36 in tumor periphery and tumor center. (G) Multiplex immunofluorescence imaging of ccRCC tumor tissues (representative of three patients) depicting CD36 and CD147 expression. White bar represents 200 µm (left) and 10 µm (right). (H) UMAP depicting clusters of single-cell data from ccRCC patients showing the expression of CD147. Cell type annotations were adopted from the original publication . (I) . Flow cytometric analysis of CD147 on CD68+ cells from central and peripheral ccRCC tumor tissue and adjacent kidney. Values were normalized to kidney controls. Representative histogram with geometric mean fluorescence intensities on the right. (J) As in (I) , correlation of CD163 and CD147 expression on CD68+ cells. Pearson´s correlation, two-tailed p-value. (K) UMAP visualization of CD163 and BSG (CD147) expression on myeloid cells from ccRCC tumors, cell type annotations were adopted from the original publication .

Article Snippet: Reagents and antibodies used included FcR Blocking Reagent (Cat# 130-059-901), CD36 PE (Cat# 130-110-877), CD147 APC (Cat# 130-124-295), CD8a PE (Cat# 130-117-201), CD45 PE (Cat# 130-113-118), CD68 PE (Cat# 130-128-345), CD163 PE (Cat# 130-127-908), and pan-Cytokeratin APC (Cat# 130-123-091), all from Miltenyi Biotec.

Techniques: Expressing, Immunohistochemistry, Staining, Two Tailed Test, Fluorescence, Multiplex Assay, Immunofluorescence, Imaging, Single Cell

Journal: Frontiers in Immunology

Article Title: Increased expression of CD36 and CD163 in clear cell renal cell carcinoma suggests an association between lipid transport and an “M2-like” macrophage phenotype

doi: 10.3389/fimmu.2026.1773666

Figure Lengend Snippet: Single cell RNA seq of ccRCC tumors. Data by Bi et al. was visualized and via the Single Cell Portal . Cell types, including immune subpopulations, were annotated as defined by the original authors. Expression of metabolic (ACAA2, SQLE, ACSL3, CD36) and immunologic (CD68, CD163, CD147) genes was examined across these distinct immune compartments. For the characterization of the immune cell populations, please refer to Bi et al. .

Article Snippet: Reagents and antibodies used included FcR Blocking Reagent (Cat# 130-059-901), CD36 PE (Cat# 130-110-877), CD147 APC (Cat# 130-124-295), CD8a PE (Cat# 130-117-201), CD45 PE (Cat# 130-113-118), CD68 PE (Cat# 130-128-345), CD163 PE (Cat# 130-127-908), and pan-Cytokeratin APC (Cat# 130-123-091), all from Miltenyi Biotec.

Techniques: Single Cell, RNA Sequencing, Expressing

Journal: Viruses

Article Title: Serum-Derived Extracellular Vesicles from African Swine Fever Virus-Infected Pigs Selectively Recruit Viral and Porcine Proteins

doi: 10.3390/v11100882

Figure Lengend Snippet: FACS analysis of EV-enriched fractions derived from infected and control animals. ( a ) EVs from representative sera of an infected animal with OURT 88/3 at 24 days post infection, ( b ) EV profiles from a representative of uninfected swine sera, ( c ) EV FACS profile from a representative animal infected with Benin ΔMGF virus. In all samples, molecular markers CD5 and CD163 were used as control markers for EVs and three different viral proteins were evaluated (p30, p54 and p72).

Article Snippet: Fractions were incubated in microtest conical-bottom 96-well plates for 30 min at 4 °C with anti-CD63 (Clone H5C6) and anti-CD81 (Clone JS-81) antibodies (BD Biosciences, San Jose, CA, USA) at 1:100 dilution, anti-CD5 (clone PG114A, Kingfisher Biotech, St Paul, MN, USA) at 1:200 or anti-CD163 (clone 2A10 gently given by Dr. Javier Dominguez).

Techniques: Derivative Assay, Infection

Journal: International Journal of Molecular Medicine

Article Title: Margatoxin mitigates CCl4-induced hepatic fibrosis in mice via macrophage polarization, cytokine secretion and STAT signaling

doi: 10.3892/ijmm.2019.4395

Figure Lengend Snippet: Sequences of primers used for RT-qPCR.

Article Snippet: Primary antibodies against δ-catenin (1:300, cat. no. bs-7000R, Bioss), α-SMA (1:300, cat. no. bs-0189R, Bioss), collagen I (1:300, cat. no. bs-10423R, Bioss), MMP12 (1:600, cat. no. 22989-1-AP, Proteintech), MMP13 (1:300, cat. no. bs-10581R, Bioss), POSTN (1:300, cat. no. bs-4994R, Bioss), CCL2 (1:500, cat. no. bs1101R, Bioss), Kv1.3 (1:300, cat. no. bs-10229R, Bioss), iNOS (1:1,000, cat. no. ab4999, Abcam), TNF-α (1:500, cat. no. BS1857, Bioworld), IL-β (1:300, cat. no. bs0812R, Bioss), IL-10 (1:1,000, cat. no. bs0698R, Bioss), CD163 (1:300, cat. no. bs2527R, Bioss), Arg-1 (1:200, cat. no. sc-47715, Santa Cruz Biotechnology), Mrc2 (1:500, cat. no. ab70132, Abcam) and β-actin (1:500, cat. no. TA-09, Zs-BIO) were used.

Techniques: Amplification

Journal: International Journal of Molecular Medicine

Article Title: Margatoxin mitigates CCl4-induced hepatic fibrosis in mice via macrophage polarization, cytokine secretion and STAT signaling

doi: 10.3892/ijmm.2019.4395

Figure Lengend Snippet: MgTX regulates macrophage polarization in vitro . Reverse transcription-quantitative PCR and western blot analysis were performed to detect the expression of M1 markers and M2 markers in RAW264.7 cells. (A-H) mRNA expression levels of iNOS, CCL2, TNF-α and IL-1β were downregulated by MgTX in M1 phenotype macrophages. mRNA expression levels of IL-10, CD163, Arg-1, MAC-2 were upregulated in M2 phenotype macrophages treated with MgTX compared with M2 phenotype macrophages. (I-Q) protein expression levels of M1 markers (iNOS, CCL2, TNF-α and IL-1β) and protein expression levels of M2 markers (IL-10, CD163, Arg-1, Mrc2) were measured by western blot analysis. * P<0.05, ** P<0.01, M1 vs. M1 + MgTX group, M2 vs. M2 + MgTX group. control group (N), n=3. MgTX, margatoxin; CCL2, C-C motif chemokine ligand 2; TNF-α, tumor necrosis factor-α; IL, interleukin; CD, cluster of differentiation.

Article Snippet: Primary antibodies against δ-catenin (1:300, cat. no. bs-7000R, Bioss), α-SMA (1:300, cat. no. bs-0189R, Bioss), collagen I (1:300, cat. no. bs-10423R, Bioss), MMP12 (1:600, cat. no. 22989-1-AP, Proteintech), MMP13 (1:300, cat. no. bs-10581R, Bioss), POSTN (1:300, cat. no. bs-4994R, Bioss), CCL2 (1:500, cat. no. bs1101R, Bioss), Kv1.3 (1:300, cat. no. bs-10229R, Bioss), iNOS (1:1,000, cat. no. ab4999, Abcam), TNF-α (1:500, cat. no. BS1857, Bioworld), IL-β (1:300, cat. no. bs0812R, Bioss), IL-10 (1:1,000, cat. no. bs0698R, Bioss), CD163 (1:300, cat. no. bs2527R, Bioss), Arg-1 (1:200, cat. no. sc-47715, Santa Cruz Biotechnology), Mrc2 (1:500, cat. no. ab70132, Abcam) and β-actin (1:500, cat. no. TA-09, Zs-BIO) were used.

Techniques: In Vitro, Real-time Polymerase Chain Reaction, Western Blot, Expressing