digital spatial profiling spatial transcriptomics sequencing Search Results


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New England Biolabs nebnext small rna library prep set
a Overview of the Mosquito <t>Small</t> <t>RNA</t> Genomics (MSRG) pipeline applied to a survey of whole mosquitoes from Americas, Asia, Africa and laboratory strains. b Implementation of the VirusDetect program with updated GBVRL and custom databases for comprehensive mosquito virus detection. c Summary tabulation of the samples and RNA libraries analyzed in this study.
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Thermo Fisher sterile phosphate buffered solution
Data obtained from the chosen articles.
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Qiagen dsp virus spin kit
Data obtained from the chosen articles.
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Novus Biologicals ndst3
Identification of regenerating factor as a regulator of therapeutic genes for Parkinson's disease therapy. A) Conceptual diagram outlining the basis of an epigenetic regulator. B) Comparative gene expression heatmap of substantia nigra (SN) in wild type control versus 6‐OHDA‐induced Parkinson's disease (PD) mouse model. C) Heatmap showing gene expression profiles in the caudate and putamen regions of healthy individuals (HI) and a cohort of human PD patients. BG: Basal Ganglia. D) Immunofluorescence images showing TUJ1‐ and MAP2‐positive cells under each condition. Scale bar = 50 µm. E) Immunochemistry and Sholl analysis of TH‐labeled neurons. Left panel: morphology of individual neurons. Right panel: Sholl analysis showing the number of neurite intersections as a function of distance from the soma. Scale bar = 100 µm. The data are presented as mean ± SEM ( n = 5 – 6 cells per group). F) Representative traces of action potentials evoked by depolarizing current injections under each condition (sham, 6‐OHDA, <t>6‐OHDA+NDST3).</t> G) Dot plot showing the top 14 GO Biological Process terms from enrichment analyses: 6‐OHDA versus Sham (left side) and 6‐OHDA+NDST3 versus 6‐OHDA (right side). H) Pearson correlation matrix of transcriptomic among samples.
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Spatial Transcriptomics Inc visium spatial transcriptomics sequencing
Single‐cell and spatial transcriptome landscape of healthy and fibrotic kidneys after unilateral ischemia‐reperfusion injury (UIRI). a) Schematic representation of single‐cell RNA <t>sequencing</t> (scRNA‐seq) and spatial <t>transcriptomics</t> (ST) of kidneys from the sham and 10‐day UIRI mice, graphically designed with Biorender ( https://www.biorender.com/ ). b) t‐SNE plot illustrating the intricate cellular diversity in fibrotic kidneys, demonstrating distinct clusters representing glomerular endothelial cells (GEC), podocytes (Podo), mesangial cells (Mesa), Bowman's capsule epithelium (BC), proximal tubules (PT), descending limbs of Henle (DLOH), ascending limbs of Henle (ALOH), distal tubules (DT), principal cells (PC), intercalated cells (IC), fibroblasts (Fib), smooth muscle cells (SMC), extraglomerular endothelial cells (EGEC), monocytes (Mono), dendritic cells (DC), macrophages (Mϕ), plasmacytoid dendritic cells (pDC), proliferating mononuclear lineage (Prolif mono_L), and neutrophils (Neu), B cells (B), T cells (T), proliferating T cells (prolif T), and natural killer cells (NK). These cell types were further categorized into four major compartments: Glomerular, Renal, Interstitium, and Immune, as indicated by color grouping in the plot. c) Bubble plot illustrating the relative proportions of major kidney cell types in sham and UIRI samples. Each dot represents the proportion of a given cell type in a specific sample group, with dot size corresponding to its relative proportion. d) A comprehensive heatmap depicting the unique marker gene signature of major renal cell types. e) UMAP plot illustrating the inferred renal cell region distribution based on integrated spatial transcriptomics data from normal (Sham) and UIRI 10D mouse kidneys, generated using the 10x Genomics <t>Visium</t> platform. The identified regions include glomerular cells (Glom), distinct segments of the proximal tubule (PTS1, PTS1S2, PTS2), injured proximal tubules (InjPT), ascending limbs of Henle in cortex (ALOH(C)), distal tubules (DT), connecting tubules and collecting ducts (CNT_CD), cells at the corticomedullary junction (CMJ), fibrogenic niche regions (Niche1, Niche2), the inner stripe of the outer medulla (IOM), inner medulla (IM), renal capsule (RC), and perirenal tissue (Perirenal). f) Spatial maps illustrating the anatomical distribution of renal cell regions in Sham and UIRI 10D mouse kidneys. Region colors correspond to the classifications defined in panel (e). g) Bubble plot illustrating the relative proportions of major renal cell regions in spatial transcriptomics data from sham and UIRI 10D mouse kidneys. h) Bubble plot depicting the expression patterns of marker genes across distinct renal cell regions in spatial transcriptomics data. Dot color indicates the average gene expression level within each region, while dot size represents the proportion of spatial spots expressing the gene. i) Schematic diagram of nephron segmentation by cell types. j) Comparison of kidney anatomical regions and spatial transcriptomic clusters, showing clusters in kidney tissue (top) and the corresponding Visium H&E‐stained section (bottom). k) Renal tissue structure alterations at the corticomedullary junction (CMJ) in UIRI samples, showing the formation of two distinct fibrogenic niches, Niche1 and Niche2. l) A heatmap showing the deconvolution scores of cell type compositions across different regions in Visium spatial transcriptomics data, obtained using the RCTD method. m) Spatial FeaturePlots of RCTD‐derived cell type scores in the sham (top) and UIRI (bottom) groups, with paired panels sharing a common legend.
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Spatial Transcriptomics Inc spatial transcriptomics st sequencing
Single‐cell and spatial transcriptome landscape of healthy and fibrotic kidneys after unilateral ischemia‐reperfusion injury (UIRI). a) Schematic representation of single‐cell RNA <t>sequencing</t> (scRNA‐seq) and spatial <t>transcriptomics</t> (ST) of kidneys from the sham and 10‐day UIRI mice, graphically designed with Biorender ( https://www.biorender.com/ ). b) t‐SNE plot illustrating the intricate cellular diversity in fibrotic kidneys, demonstrating distinct clusters representing glomerular endothelial cells (GEC), podocytes (Podo), mesangial cells (Mesa), Bowman's capsule epithelium (BC), proximal tubules (PT), descending limbs of Henle (DLOH), ascending limbs of Henle (ALOH), distal tubules (DT), principal cells (PC), intercalated cells (IC), fibroblasts (Fib), smooth muscle cells (SMC), extraglomerular endothelial cells (EGEC), monocytes (Mono), dendritic cells (DC), macrophages (Mϕ), plasmacytoid dendritic cells (pDC), proliferating mononuclear lineage (Prolif mono_L), and neutrophils (Neu), B cells (B), T cells (T), proliferating T cells (prolif T), and natural killer cells (NK). These cell types were further categorized into four major compartments: Glomerular, Renal, Interstitium, and Immune, as indicated by color grouping in the plot. c) Bubble plot illustrating the relative proportions of major kidney cell types in sham and UIRI samples. Each dot represents the proportion of a given cell type in a specific sample group, with dot size corresponding to its relative proportion. d) A comprehensive heatmap depicting the unique marker gene signature of major renal cell types. e) UMAP plot illustrating the inferred renal cell region distribution based on integrated spatial transcriptomics data from normal (Sham) and UIRI 10D mouse kidneys, generated using the 10x Genomics <t>Visium</t> platform. The identified regions include glomerular cells (Glom), distinct segments of the proximal tubule (PTS1, PTS1S2, PTS2), injured proximal tubules (InjPT), ascending limbs of Henle in cortex (ALOH(C)), distal tubules (DT), connecting tubules and collecting ducts (CNT_CD), cells at the corticomedullary junction (CMJ), fibrogenic niche regions (Niche1, Niche2), the inner stripe of the outer medulla (IOM), inner medulla (IM), renal capsule (RC), and perirenal tissue (Perirenal). f) Spatial maps illustrating the anatomical distribution of renal cell regions in Sham and UIRI 10D mouse kidneys. Region colors correspond to the classifications defined in panel (e). g) Bubble plot illustrating the relative proportions of major renal cell regions in spatial transcriptomics data from sham and UIRI 10D mouse kidneys. h) Bubble plot depicting the expression patterns of marker genes across distinct renal cell regions in spatial transcriptomics data. Dot color indicates the average gene expression level within each region, while dot size represents the proportion of spatial spots expressing the gene. i) Schematic diagram of nephron segmentation by cell types. j) Comparison of kidney anatomical regions and spatial transcriptomic clusters, showing clusters in kidney tissue (top) and the corresponding Visium H&E‐stained section (bottom). k) Renal tissue structure alterations at the corticomedullary junction (CMJ) in UIRI samples, showing the formation of two distinct fibrogenic niches, Niche1 and Niche2. l) A heatmap showing the deconvolution scores of cell type compositions across different regions in Visium spatial transcriptomics data, obtained using the RCTD method. m) Spatial FeaturePlots of RCTD‐derived cell type scores in the sham (top) and UIRI (bottom) groups, with paired panels sharing a common legend.
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Thermo Fisher gene exp gapdh hs02758991 g1
ACTB and <t>GAPDH</t> mRNA expression variation in sections from 13 primary melanoma tumors. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. (e) Displays variable length of GAPDH fragments amplified by RT-PCR. Base pair (bp) markers of 100 bps and 200 bps are shown at the left. Bottom panels showing corresponding Cq values for ACTB and GAPDH in qRT-PCR. Cq, quantification cycle.
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Vector Laboratories s080983 2 vectashield vibrance antifade mounting medium vector laboratories
ACTB and <t>GAPDH</t> mRNA expression variation in sections from 13 primary melanoma tumors. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. (e) Displays variable length of GAPDH fragments amplified by RT-PCR. Base pair (bp) markers of 100 bps and 200 bps are shown at the left. Bottom panels showing corresponding Cq values for ACTB and GAPDH in qRT-PCR. Cq, quantification cycle.
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10X Genomics quantitative whole transcriptome rna sequencing
ACTB and <t>GAPDH</t> mRNA expression variation in sections from 13 primary melanoma tumors. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. (e) Displays variable length of GAPDH fragments amplified by RT-PCR. Base pair (bp) markers of 100 bps and 200 bps are shown at the left. Bottom panels showing corresponding Cq values for ACTB and GAPDH in qRT-PCR. Cq, quantification cycle.
Quantitative Whole Transcriptome Rna Sequencing, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Cyagen Biosciences s ko 03334 morrbid
ACTB and <t>GAPDH</t> mRNA expression variation in sections from 13 primary melanoma tumors. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. (e) Displays variable length of GAPDH fragments amplified by RT-PCR. Base pair (bp) markers of 100 bps and 200 bps are shown at the left. Bottom panels showing corresponding Cq values for ACTB and GAPDH in qRT-PCR. Cq, quantification cycle.
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Bio X Cell invivomab anti mouse cd40
(A) Representative images and quantification of CCR7 + DCs (panCK − HLA-DR + LAMP3 + , yellow) near BVs (CD31 + PDPN − , magenta), or LVs (CD31 + PDPN + , cyan) in human tumors (HNSCC, NSCLC, and EC). Scale bar represents 20 μm. Whole-tumor sections were analyzed for EC and NSCLC. Numbers of fields of view (FOVs) analyzed per HNSCC sample are as follows: HNSCC1–04 n = 7; HNSCC1–06 n = 16; HNSCC1–07 n = 11; HNSCC2–01 n = 126; HNSCC2–06 n = 455; HNSCC2–09 n = 180; HNSCC2–11 n = 122; HNSCC2–12 n = 79; HNSCC2–15 n = 205; HNSCC2–26 n = 293; HNSCC2–35 n = 175. One bar = one patient . (B) Representative images and quantification of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) or LVs (CD31 + LYVE-1 + ; cyan) in mouse tumors (MC38, B16F10, and D4M3.A-OVA). Scale bar represents 10 μm. Whole-tumor sections were analyzed. One bar = one mouse. (C) Frequencies of BV-, LV- and non-vessel-associated CCR7 + DCs in mouse MC38 tumors 3 days post <t>anti-CD40</t> or anti-PD-1 treatment. Whole-tumor sections were analyzed. One bar = one mouse. (D) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccr7 ko/wt and Ccr7 ko/ko mice, 3 days post anti-PD-1 treatment. (Right) Distribution of the area of CCR7 + DC surfaces in clusters relative to their distance to closest BVs and plotted as percentage of total CCR7 + DC cluster area. CCR7 + DC surfaces from clusters associated with LVs and those not in clusters were excluded from the analysis. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = average value of all clusters in each genotype ( Ccr7 ko/ko n = 5 mice, 56 clusters; Ccr7 wt /ko n = 6 mice, 28 clusters; and Ccr7 wt /wt n = 3 mice, 19 clusters). Two-way ANOVA with multiple comparisons, mean with SEM; **** p < 0.0001 for comparison at 10 and 20 μm from closest BVs. (E) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) and Ccl19 ( Ccl19 -eYFP + Tomato + ; white) in Ccl19 -ieYFP reporter mice (left image) or CCL21 (white, right image) in MC38 tumors. (Right) Frequencies of perivascular CCR7 + DC clusters associated with Ccl19 -covered BVs or within CCL21 + areas of the tumors among total perivascular CCR7 + DC clusters. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse. Unpaired t test, mean with SEM; *** p < 0.001. (F) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccl19 wt/wt and Ccl19 ko/ko mice, 2 days post anti-PD-1treatment. (Right) Quantification of BV- or LV-associated CCR7 + DC clusters in MC38 tumors from Ccl19 wt/wt and Ccl19 ko/ko mice. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse, whiskers represent min to max. Unpaired t test; * p < 0.05. (G) Heatmap depicts log 2 -transformed averaged expression of Ccl19 in indicated immune and non-immune populations in the TME of multiple mouse tumor models (breast, , lung [and GSE201247 ], and pancreatic , ). (H) (Left) Synthetic images of CCR7 + DCs (yellow), blood endothelial cells (BECs; magenta), lymphatic endothelial cells (LECs; cyan), and CCL19 + fibroblasts (green) in one representative NSCLC patient analyzed by spatial transcriptomics. (Right) Box plots depict the enrichment scores of CCL19 + fibroblasts within the neighborhood of BV-associated CCR7 + DCs, in four human NSCLC. Data are shown for both permuted (median enrichment scores from 1,000 permutations) and observed datasets. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one sample. Paired t test, whiskers represent mean to max; * p < 0.05. (I) Heatmap depicts log 2 -transformed averaged expression of CCL19 in indicated immune and non-immune populations in the TME of multiple human cancer types (HNSCC, n = 40, n = 18 patients; CRC, n = 23, n = 64 patients; ESCC, n = 58 patients ; NSCLC, n = 32, n = 7 patients; BRCA, n = 29 patients ; and PRCA, n = 18 patients ). A cross indicates that the cellular population was not detected. See also – .
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Spatial Transcriptomics Inc single cell rna sequencing scrna seq data
(A) Representative images and quantification of CCR7 + DCs (panCK − HLA-DR + LAMP3 + , yellow) near BVs (CD31 + PDPN − , magenta), or LVs (CD31 + PDPN + , cyan) in human tumors (HNSCC, NSCLC, and EC). Scale bar represents 20 μm. Whole-tumor sections were analyzed for EC and NSCLC. Numbers of fields of view (FOVs) analyzed per HNSCC sample are as follows: HNSCC1–04 n = 7; HNSCC1–06 n = 16; HNSCC1–07 n = 11; HNSCC2–01 n = 126; HNSCC2–06 n = 455; HNSCC2–09 n = 180; HNSCC2–11 n = 122; HNSCC2–12 n = 79; HNSCC2–15 n = 205; HNSCC2–26 n = 293; HNSCC2–35 n = 175. One bar = one patient . (B) Representative images and quantification of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) or LVs (CD31 + LYVE-1 + ; cyan) in mouse tumors (MC38, B16F10, and D4M3.A-OVA). Scale bar represents 10 μm. Whole-tumor sections were analyzed. One bar = one mouse. (C) Frequencies of BV-, LV- and non-vessel-associated CCR7 + DCs in mouse MC38 tumors 3 days post <t>anti-CD40</t> or anti-PD-1 treatment. Whole-tumor sections were analyzed. One bar = one mouse. (D) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccr7 ko/wt and Ccr7 ko/ko mice, 3 days post anti-PD-1 treatment. (Right) Distribution of the area of CCR7 + DC surfaces in clusters relative to their distance to closest BVs and plotted as percentage of total CCR7 + DC cluster area. CCR7 + DC surfaces from clusters associated with LVs and those not in clusters were excluded from the analysis. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = average value of all clusters in each genotype ( Ccr7 ko/ko n = 5 mice, 56 clusters; Ccr7 wt /ko n = 6 mice, 28 clusters; and Ccr7 wt /wt n = 3 mice, 19 clusters). Two-way ANOVA with multiple comparisons, mean with SEM; **** p < 0.0001 for comparison at 10 and 20 μm from closest BVs. (E) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) and Ccl19 ( Ccl19 -eYFP + Tomato + ; white) in Ccl19 -ieYFP reporter mice (left image) or CCL21 (white, right image) in MC38 tumors. (Right) Frequencies of perivascular CCR7 + DC clusters associated with Ccl19 -covered BVs or within CCL21 + areas of the tumors among total perivascular CCR7 + DC clusters. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse. Unpaired t test, mean with SEM; *** p < 0.001. (F) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccl19 wt/wt and Ccl19 ko/ko mice, 2 days post anti-PD-1treatment. (Right) Quantification of BV- or LV-associated CCR7 + DC clusters in MC38 tumors from Ccl19 wt/wt and Ccl19 ko/ko mice. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse, whiskers represent min to max. Unpaired t test; * p < 0.05. (G) Heatmap depicts log 2 -transformed averaged expression of Ccl19 in indicated immune and non-immune populations in the TME of multiple mouse tumor models (breast, , lung [and GSE201247 ], and pancreatic , ). (H) (Left) Synthetic images of CCR7 + DCs (yellow), blood endothelial cells (BECs; magenta), lymphatic endothelial cells (LECs; cyan), and CCL19 + fibroblasts (green) in one representative NSCLC patient analyzed by spatial transcriptomics. (Right) Box plots depict the enrichment scores of CCL19 + fibroblasts within the neighborhood of BV-associated CCR7 + DCs, in four human NSCLC. Data are shown for both permuted (median enrichment scores from 1,000 permutations) and observed datasets. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one sample. Paired t test, whiskers represent mean to max; * p < 0.05. (I) Heatmap depicts log 2 -transformed averaged expression of CCL19 in indicated immune and non-immune populations in the TME of multiple human cancer types (HNSCC, n = 40, n = 18 patients; CRC, n = 23, n = 64 patients; ESCC, n = 58 patients ; NSCLC, n = 32, n = 7 patients; BRCA, n = 29 patients ; and PRCA, n = 18 patients ). A cross indicates that the cellular population was not detected. See also – .
Single Cell Rna Sequencing Scrna Seq Data, supplied by Spatial Transcriptomics Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


a Overview of the Mosquito Small RNA Genomics (MSRG) pipeline applied to a survey of whole mosquitoes from Americas, Asia, Africa and laboratory strains. b Implementation of the VirusDetect program with updated GBVRL and custom databases for comprehensive mosquito virus detection. c Summary tabulation of the samples and RNA libraries analyzed in this study.

Journal: Nature Communications

Article Title: Small RNA genomics of Aedes aegypti mosquitoes discovers infectious viruses that trigger an RNA interference response

doi: 10.1038/s41467-026-71964-1

Figure Lengend Snippet: a Overview of the Mosquito Small RNA Genomics (MSRG) pipeline applied to a survey of whole mosquitoes from Americas, Asia, Africa and laboratory strains. b Implementation of the VirusDetect program with updated GBVRL and custom databases for comprehensive mosquito virus detection. c Summary tabulation of the samples and RNA libraries analyzed in this study.

Article Snippet: Small RNA libraries were made using NEBNext Small RNA Library Prep Set (NEB #E7330) with up to 5 μg of RNA input.

Techniques: Virus

a Bubble plot of vsmRNAs from Africa Ae. aegypti colony strains. Number of reads per million is reflected by bubble diameter, and color represents strand bias of reads, red is plus strand biased, blue is minus strand biased. Dashed pink line boxes mark the PCLV and FORMV noted in panels ( c ) and ( d ), respectively. b Map of Africa locations where the Ae. aegypti colonies or samples originated. Map data ©2025 Google. c Coverage plots of PCLV small RNAs from a selection of African Ae. aegypti showing high M-fragment piRNAs rivaling the S-fragment piRNAs. d The FORMV vsmRNA coverage from African Ae. aegypti colonies from the McBride lab and an independent Kedougou, Senegal sample from Olmo et al. . The black arrow points to male-specific viral piRNA species. e Three examples of FORMV long RNAs sequenced from matched samples in ( d ).

Journal: Nature Communications

Article Title: Small RNA genomics of Aedes aegypti mosquitoes discovers infectious viruses that trigger an RNA interference response

doi: 10.1038/s41467-026-71964-1

Figure Lengend Snippet: a Bubble plot of vsmRNAs from Africa Ae. aegypti colony strains. Number of reads per million is reflected by bubble diameter, and color represents strand bias of reads, red is plus strand biased, blue is minus strand biased. Dashed pink line boxes mark the PCLV and FORMV noted in panels ( c ) and ( d ), respectively. b Map of Africa locations where the Ae. aegypti colonies or samples originated. Map data ©2025 Google. c Coverage plots of PCLV small RNAs from a selection of African Ae. aegypti showing high M-fragment piRNAs rivaling the S-fragment piRNAs. d The FORMV vsmRNA coverage from African Ae. aegypti colonies from the McBride lab and an independent Kedougou, Senegal sample from Olmo et al. . The black arrow points to male-specific viral piRNA species. e Three examples of FORMV long RNAs sequenced from matched samples in ( d ).

Article Snippet: Small RNA libraries were made using NEBNext Small RNA Library Prep Set (NEB #E7330) with up to 5 μg of RNA input.

Techniques: Selection

a Bubble plot of vsmRNAs from lab strains. Reads per million represented by bubble diameter, strand bias represented by color, red is plus strand biased, blue is minus strand biased. See Supplementary Data for sample details. Lab initials: BZL=Benzon Research, MY = M. Younger, DB = D. Brackney, JM = J. Marques, ZT = Z. Tu, GH = G. Hughes, TC = T. Colpitts, BH = B. Hay, GP = G. Pijlman labs. b Coverage plots of long RNAs compared to small RNAs for viruses from the BZL strain of Ae. aegypti females and dormant eggs. c Coverage plots of TMBTLV small RNAs from GP lab strains also infected with Zika virus (ZIKV). d Scatterplot comparing matched small and long RNA libraries from Ae. aegypti . Sequencing RPM are plotted on a logarithmic scale. Sample dots are colored by sex, and clustered samples are in labeled ovals. e Coverage plots of two Florida exhibiting abundant long RNA signal for the Toti-like virus but negligible vsmRNAs in the upper plots that contrast both long and small RNAs against an R1-Ele4 TE. f Coverage plots of long RNAs versus small RNAs for the Formosus virus and R1-Ele4 TE from both males and females of the ENT African colony.

Journal: Nature Communications

Article Title: Small RNA genomics of Aedes aegypti mosquitoes discovers infectious viruses that trigger an RNA interference response

doi: 10.1038/s41467-026-71964-1

Figure Lengend Snippet: a Bubble plot of vsmRNAs from lab strains. Reads per million represented by bubble diameter, strand bias represented by color, red is plus strand biased, blue is minus strand biased. See Supplementary Data for sample details. Lab initials: BZL=Benzon Research, MY = M. Younger, DB = D. Brackney, JM = J. Marques, ZT = Z. Tu, GH = G. Hughes, TC = T. Colpitts, BH = B. Hay, GP = G. Pijlman labs. b Coverage plots of long RNAs compared to small RNAs for viruses from the BZL strain of Ae. aegypti females and dormant eggs. c Coverage plots of TMBTLV small RNAs from GP lab strains also infected with Zika virus (ZIKV). d Scatterplot comparing matched small and long RNA libraries from Ae. aegypti . Sequencing RPM are plotted on a logarithmic scale. Sample dots are colored by sex, and clustered samples are in labeled ovals. e Coverage plots of two Florida exhibiting abundant long RNA signal for the Toti-like virus but negligible vsmRNAs in the upper plots that contrast both long and small RNAs against an R1-Ele4 TE. f Coverage plots of long RNAs versus small RNAs for the Formosus virus and R1-Ele4 TE from both males and females of the ENT African colony.

Article Snippet: Small RNA libraries were made using NEBNext Small RNA Library Prep Set (NEB #E7330) with up to 5 μg of RNA input.

Techniques: Infection, Virus, Sequencing, Labeling

a Our methodology to molecularly validate the small RNA detection of ISVs are true viruses that can be isolated and verified for triggering the RNAi response in mosquito cells. b RT-PCR detection of TMBTLV RNAs S1 and S2 during multiple rounds of blind passaging, starting with BZL mosquito homogenate as the initial virus infection source placed onto C6/36-NL and Aag2 mosquito cells. The ladder is the 1KbPlus DNA ladder, and uncropped gels are in the source data files. c Virus infection kinetics measured in C6/36-NL and Aag2 cells over 12 days using droplet digital PCR (ddPCR). Flasks with 1 million cells were infected on Day 0 with 20 K viral copies per infection. Virus stocks are from filtered media from subsequent passage from the experiment in (a). Error bars correspond to the 95% confidence interval from Poisson Distribution in the ddPCR analysis algorithm centered around the mean from each reading that contained >15 K droplets replicates. Additional virus infection kinetics measurements are shown in Supplementary Fig. . T-flask illustration from NIAID NIH BioArt Source (bioart.niaid.nih.gov/bioart/303).

Journal: Nature Communications

Article Title: Small RNA genomics of Aedes aegypti mosquitoes discovers infectious viruses that trigger an RNA interference response

doi: 10.1038/s41467-026-71964-1

Figure Lengend Snippet: a Our methodology to molecularly validate the small RNA detection of ISVs are true viruses that can be isolated and verified for triggering the RNAi response in mosquito cells. b RT-PCR detection of TMBTLV RNAs S1 and S2 during multiple rounds of blind passaging, starting with BZL mosquito homogenate as the initial virus infection source placed onto C6/36-NL and Aag2 mosquito cells. The ladder is the 1KbPlus DNA ladder, and uncropped gels are in the source data files. c Virus infection kinetics measured in C6/36-NL and Aag2 cells over 12 days using droplet digital PCR (ddPCR). Flasks with 1 million cells were infected on Day 0 with 20 K viral copies per infection. Virus stocks are from filtered media from subsequent passage from the experiment in (a). Error bars correspond to the 95% confidence interval from Poisson Distribution in the ddPCR analysis algorithm centered around the mean from each reading that contained >15 K droplets replicates. Additional virus infection kinetics measurements are shown in Supplementary Fig. . T-flask illustration from NIAID NIH BioArt Source (bioart.niaid.nih.gov/bioart/303).

Article Snippet: Small RNA libraries were made using NEBNext Small RNA Library Prep Set (NEB #E7330) with up to 5 μg of RNA input.

Techniques: RNA Detection, Isolation, Reverse Transcription Polymerase Chain Reaction, Passaging, Virus, Infection, Digital PCR

Data obtained from the chosen articles.

Journal: The Science of the Total Environment

Article Title: Sampling methods and assays applied in SARS-CoV-2 exposure assessment

doi: 10.1016/j.scitotenv.2021.145903

Figure Lengend Snippet: Data obtained from the chosen articles.

Article Snippet: , 34. SARS-CoV-2 RNA contamination on surfaces of a COVID-19 ward in a hospital of Northern Italy: what risk of transmission? , Italy , No , Surface samples from ward in University Hospital of Ferrara , Sampling performed with sterile rayon swabs pre-moistened in sterile phosphate-buffered solution , Viral RNA extraction with Patho Gene-spin Extraction kit (Generon) RT-qPCR targeted the RNA-dependent RNA polymerase ( RdRp ) gene (Generon), and the orf1ab , spike ( S ), and nucleocapsid ( N ) genes (ThermoFisher) , • SARS-CoV-2 was only detected in 3 samples of two floors and one-bathroom sink. • Reported to persist for a longer duration on surfaces under controlled laboratory conditions. , ( ) .

Techniques: Sampling, Lysis, RNA Extraction, Environmental Monitoring, Virus, Multiplex Assay, Northern Blot, Marker, RNA Detection, Isolation, Membrane, Control, Environmental Sampling, Amplification, Transmission Assay, Aerosol, Diagnostic Assay, Infection, Sterility, Real-time Polymerase Chain Reaction, Nested PCR, Reverse Transcription, Extraction, Purification, Digital PCR, Preserving, Quantitative RT-PCR, cDNA Synthesis, Magnetic Beads, Incubation, Modification, One Step RT-PCR, Cell Culture, Sequencing

Data obtained from the chosen articles.

Journal: The Science of the Total Environment

Article Title: Sampling methods and assays applied in SARS-CoV-2 exposure assessment

doi: 10.1016/j.scitotenv.2021.145903

Figure Lengend Snippet: Data obtained from the chosen articles.

Article Snippet: , 43. Aerosol and surface contamination of SARS-CoV-2 observed in quarantine and isolation care , USA , No , Surface and air samples from COVID-19 patient rooms , Air sampling: Sartorius Airport MD8 air sampler operating at 50 Lpm for 15 min. Surface samples: sterile swabs , Viral RNA Extractions: using a Qiagen DSP Virus Spin Kit. RT-qPCR: using Invitrogen Superscript III Platinum One-Step Quantitative RT-qPCR System. Primers and probe used target the E gene of SARS-CoV-2. , • We detected viral contamination among all samples. , ( ) .

Techniques: Sampling, Lysis, RNA Extraction, Environmental Monitoring, Virus, Multiplex Assay, Northern Blot, Marker, RNA Detection, Isolation, Membrane, Control, Environmental Sampling, Amplification, Transmission Assay, Aerosol, Diagnostic Assay, Infection, Sterility, Real-time Polymerase Chain Reaction, Nested PCR, Reverse Transcription, Extraction, Purification, Digital PCR, Preserving, Quantitative RT-PCR, cDNA Synthesis, Magnetic Beads, Incubation, Modification, One Step RT-PCR, Cell Culture, Sequencing

Identification of regenerating factor as a regulator of therapeutic genes for Parkinson's disease therapy. A) Conceptual diagram outlining the basis of an epigenetic regulator. B) Comparative gene expression heatmap of substantia nigra (SN) in wild type control versus 6‐OHDA‐induced Parkinson's disease (PD) mouse model. C) Heatmap showing gene expression profiles in the caudate and putamen regions of healthy individuals (HI) and a cohort of human PD patients. BG: Basal Ganglia. D) Immunofluorescence images showing TUJ1‐ and MAP2‐positive cells under each condition. Scale bar = 50 µm. E) Immunochemistry and Sholl analysis of TH‐labeled neurons. Left panel: morphology of individual neurons. Right panel: Sholl analysis showing the number of neurite intersections as a function of distance from the soma. Scale bar = 100 µm. The data are presented as mean ± SEM ( n = 5 – 6 cells per group). F) Representative traces of action potentials evoked by depolarizing current injections under each condition (sham, 6‐OHDA, 6‐OHDA+NDST3). G) Dot plot showing the top 14 GO Biological Process terms from enrichment analyses: 6‐OHDA versus Sham (left side) and 6‐OHDA+NDST3 versus 6‐OHDA (right side). H) Pearson correlation matrix of transcriptomic among samples.

Journal: Advanced Science

Article Title: NDST3‐Induced Epigenetic Reprogramming Reverses Neurodegeneration in Parkinson's Disease

doi: 10.1002/advs.202507323

Figure Lengend Snippet: Identification of regenerating factor as a regulator of therapeutic genes for Parkinson's disease therapy. A) Conceptual diagram outlining the basis of an epigenetic regulator. B) Comparative gene expression heatmap of substantia nigra (SN) in wild type control versus 6‐OHDA‐induced Parkinson's disease (PD) mouse model. C) Heatmap showing gene expression profiles in the caudate and putamen regions of healthy individuals (HI) and a cohort of human PD patients. BG: Basal Ganglia. D) Immunofluorescence images showing TUJ1‐ and MAP2‐positive cells under each condition. Scale bar = 50 µm. E) Immunochemistry and Sholl analysis of TH‐labeled neurons. Left panel: morphology of individual neurons. Right panel: Sholl analysis showing the number of neurite intersections as a function of distance from the soma. Scale bar = 100 µm. The data are presented as mean ± SEM ( n = 5 – 6 cells per group). F) Representative traces of action potentials evoked by depolarizing current injections under each condition (sham, 6‐OHDA, 6‐OHDA+NDST3). G) Dot plot showing the top 14 GO Biological Process terms from enrichment analyses: 6‐OHDA versus Sham (left side) and 6‐OHDA+NDST3 versus 6‐OHDA (right side). H) Pearson correlation matrix of transcriptomic among samples.

Article Snippet: Slices were incubated with primary antibodies targeting dopaminergic neuron markers TH (Merck Millipore, AB152, Lot# 4127053; Merck Millipore, MAB318, Lot#3990619), GIRK2 (Abcam, ab259909, Lot# GR3401320‐4), NDST3 (Novus Biologicals, NBP2‐19501, Lot# 40723), DAT (Merck Millipore, MAB369) and histone modification marker H3K27ac (Abcam, AB4729, Lot# 1059037‐6).

Techniques: Gene Expression, Control, Immunofluorescence, Labeling

Therapeutic efficacy of NDST3 and retrograde tracing with CTB in mice. A) Schematic diagram of in vivo experimental design involving CTB injection in the PD mouse model. B) Representative immunofluorescence images of CTB, TH, and NDST3 expression in the SN of Sham, 6‐OHDA‐induced PD mice, and NDST3‐treated PD mice. Scale bar = 50 µm and 10 µm (Magnified image). C) Quantification of CTB‐, TH‐, and NDST3‐positive cells shown in Figure . Data are presented as mean ± SEM ( n = 6 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. ** p < 0.01, *** p < 0.001, **** p < 0.0001, and ns = not significant. D) Immunofluorescence images showing GIRK2‐ and TH‐positive cells in the Sham, 6‐OHDA‐induced PD mice, and NDST3‐treated PD mice. Scale bar = 50 µm and 10 µm (Magnified image). E) 3D Z‐stack analysis (IMARIS) of TH‐positive neurons obtained via confocal microscopy. F) DAB‐DAT staining in the SN.

Journal: Advanced Science

Article Title: NDST3‐Induced Epigenetic Reprogramming Reverses Neurodegeneration in Parkinson's Disease

doi: 10.1002/advs.202507323

Figure Lengend Snippet: Therapeutic efficacy of NDST3 and retrograde tracing with CTB in mice. A) Schematic diagram of in vivo experimental design involving CTB injection in the PD mouse model. B) Representative immunofluorescence images of CTB, TH, and NDST3 expression in the SN of Sham, 6‐OHDA‐induced PD mice, and NDST3‐treated PD mice. Scale bar = 50 µm and 10 µm (Magnified image). C) Quantification of CTB‐, TH‐, and NDST3‐positive cells shown in Figure . Data are presented as mean ± SEM ( n = 6 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. ** p < 0.01, *** p < 0.001, **** p < 0.0001, and ns = not significant. D) Immunofluorescence images showing GIRK2‐ and TH‐positive cells in the Sham, 6‐OHDA‐induced PD mice, and NDST3‐treated PD mice. Scale bar = 50 µm and 10 µm (Magnified image). E) 3D Z‐stack analysis (IMARIS) of TH‐positive neurons obtained via confocal microscopy. F) DAB‐DAT staining in the SN.

Article Snippet: Slices were incubated with primary antibodies targeting dopaminergic neuron markers TH (Merck Millipore, AB152, Lot# 4127053; Merck Millipore, MAB318, Lot#3990619), GIRK2 (Abcam, ab259909, Lot# GR3401320‐4), NDST3 (Novus Biologicals, NBP2‐19501, Lot# 40723), DAT (Merck Millipore, MAB369) and histone modification marker H3K27ac (Abcam, AB4729, Lot# 1059037‐6).

Techniques: Drug discovery, Retrograde Tracing, In Vivo, Injection, Immunofluorescence, Expressing, Confocal Microscopy, Staining

Efficacy and electrophysiological properties of NDST3 in chemical‐induced PD model. A) Representative traces of spontaneous firing currents recorded from DA neurons of the SNpc in brain slices from each group. B) Cumulative fractions curves showing shortened inter‐event intervals, indicating a higher frequency of spontaneous firing in the 6‐OHDA + NDST3 group compared to the 6‐OHDA group. The inner bar graph showed mean inter‐event intervals in the ipsilateral of SNpc of each group. Data are presented as mean ± SEM ( n = 6 – 8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. *** p < 0.001. C) Quantification of DA neuronal firing rates in the ipsilateral SNpc of each group. The data are presented as mean ± SEM ( n = 6–8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. * p < 0.05, and ** p < 0.01. D) Representative in vivo recording traces from the SNpc of live animals in each condition. E) Instantaneous firing frequencies during the recorded period. ( n = 4–6 independent animals per group; repeated measures) Two‐way ANOVA with Tukey's multiple comparisons test, * p < 0.05. F) Comparison of action potential waveforms among DA neurons across conditions. G) Representative image of DAB‐TH staining in ST and SN. Scale bar = 1 mm. H) Immunofluorescence images showing GIRK2‐ and TH‐positive cells in the Sham, MPTP‐induced PD mice, NDST3‐treated PD mice, and NDST3 only‐treated mice. Scale bar = 50 µm and 10 µm (Magnified image). I) Error count during the challenging beam traversal test for each experimental condition. The data are presented as mean ± SEM. ( n = 7 – 8 independent animals per group) Two‐way ANOVA with Tukey's multiple comparisons test. **** p < 0.0001. J) Errors per step during the challenging beam traversal test across conditions. The data are presented as mean ± SEM ( n = 7 – 8 independent animal per group). One‐way ANOVA with Tukey's multiple comparisons test. **** p < 0.0001. K) Fall latency in the wire‐hanging test. The data are presented as mean ± SEM ( n = 7–8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. *** p < 0.001 and **** p < 0.0001. L) Time to orient downward (T‐turn) and M) time to descend to the base (T‐total). The data are presented as mean ± SEM ( n = 7–8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. * p < 0.05, *** p < 0.001 and **** p < 0.0001.

Journal: Advanced Science

Article Title: NDST3‐Induced Epigenetic Reprogramming Reverses Neurodegeneration in Parkinson's Disease

doi: 10.1002/advs.202507323

Figure Lengend Snippet: Efficacy and electrophysiological properties of NDST3 in chemical‐induced PD model. A) Representative traces of spontaneous firing currents recorded from DA neurons of the SNpc in brain slices from each group. B) Cumulative fractions curves showing shortened inter‐event intervals, indicating a higher frequency of spontaneous firing in the 6‐OHDA + NDST3 group compared to the 6‐OHDA group. The inner bar graph showed mean inter‐event intervals in the ipsilateral of SNpc of each group. Data are presented as mean ± SEM ( n = 6 – 8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. *** p < 0.001. C) Quantification of DA neuronal firing rates in the ipsilateral SNpc of each group. The data are presented as mean ± SEM ( n = 6–8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. * p < 0.05, and ** p < 0.01. D) Representative in vivo recording traces from the SNpc of live animals in each condition. E) Instantaneous firing frequencies during the recorded period. ( n = 4–6 independent animals per group; repeated measures) Two‐way ANOVA with Tukey's multiple comparisons test, * p < 0.05. F) Comparison of action potential waveforms among DA neurons across conditions. G) Representative image of DAB‐TH staining in ST and SN. Scale bar = 1 mm. H) Immunofluorescence images showing GIRK2‐ and TH‐positive cells in the Sham, MPTP‐induced PD mice, NDST3‐treated PD mice, and NDST3 only‐treated mice. Scale bar = 50 µm and 10 µm (Magnified image). I) Error count during the challenging beam traversal test for each experimental condition. The data are presented as mean ± SEM. ( n = 7 – 8 independent animals per group) Two‐way ANOVA with Tukey's multiple comparisons test. **** p < 0.0001. J) Errors per step during the challenging beam traversal test across conditions. The data are presented as mean ± SEM ( n = 7 – 8 independent animal per group). One‐way ANOVA with Tukey's multiple comparisons test. **** p < 0.0001. K) Fall latency in the wire‐hanging test. The data are presented as mean ± SEM ( n = 7–8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. *** p < 0.001 and **** p < 0.0001. L) Time to orient downward (T‐turn) and M) time to descend to the base (T‐total). The data are presented as mean ± SEM ( n = 7–8 independent animals per group). One‐way ANOVA with Tukey's multiple comparisons test. * p < 0.05, *** p < 0.001 and **** p < 0.0001.

Article Snippet: Slices were incubated with primary antibodies targeting dopaminergic neuron markers TH (Merck Millipore, AB152, Lot# 4127053; Merck Millipore, MAB318, Lot#3990619), GIRK2 (Abcam, ab259909, Lot# GR3401320‐4), NDST3 (Novus Biologicals, NBP2‐19501, Lot# 40723), DAT (Merck Millipore, MAB369) and histone modification marker H3K27ac (Abcam, AB4729, Lot# 1059037‐6).

Techniques: In Vivo, Comparison, Staining, Immunofluorescence

Molecular mechanisms of NDST3 in the PD model. A) One‐way hierarchical clustering heatmap based on Z‐score of normalized expression value for 5629 genes selected with fold change ≥ 2 and raw p ‐value < 0.05. B) Principal component analysis (PCA) analysis of RNA‐seq data to visualize sample‐to‐sample variation. C) Volcano plot showing differentially expressed genes between 6‐OHDA and Sham group; Down‐regulated genes marked in blue. D) Volcano plot showing differentially expressed genes between 6‐OHDA+NDST3 and 6‐OHDA; Up‐regulated genes marked in red. E) Dot plot of top 14 GO cellular component terms from GO enrichment analyses: 6‐OHDA+NDST3 versus 6‐OHDA. Heatmap showing gene expression patterns in F) pre‐synaptic neurons, G) post‐synaptic neurons, and H) glia compartments. I) UMAP visualizing cluster identity. J) UMAP representation comparing cellular composition in 6‐OHDA and 6‐OHDA+NDST3. K) Branched trajectory analysis illustrating cell state transitions in a 2D state‐space, where each dot represents a single cell, color‐coded by group identity.

Journal: Advanced Science

Article Title: NDST3‐Induced Epigenetic Reprogramming Reverses Neurodegeneration in Parkinson's Disease

doi: 10.1002/advs.202507323

Figure Lengend Snippet: Molecular mechanisms of NDST3 in the PD model. A) One‐way hierarchical clustering heatmap based on Z‐score of normalized expression value for 5629 genes selected with fold change ≥ 2 and raw p ‐value < 0.05. B) Principal component analysis (PCA) analysis of RNA‐seq data to visualize sample‐to‐sample variation. C) Volcano plot showing differentially expressed genes between 6‐OHDA and Sham group; Down‐regulated genes marked in blue. D) Volcano plot showing differentially expressed genes between 6‐OHDA+NDST3 and 6‐OHDA; Up‐regulated genes marked in red. E) Dot plot of top 14 GO cellular component terms from GO enrichment analyses: 6‐OHDA+NDST3 versus 6‐OHDA. Heatmap showing gene expression patterns in F) pre‐synaptic neurons, G) post‐synaptic neurons, and H) glia compartments. I) UMAP visualizing cluster identity. J) UMAP representation comparing cellular composition in 6‐OHDA and 6‐OHDA+NDST3. K) Branched trajectory analysis illustrating cell state transitions in a 2D state‐space, where each dot represents a single cell, color‐coded by group identity.

Article Snippet: Slices were incubated with primary antibodies targeting dopaminergic neuron markers TH (Merck Millipore, AB152, Lot# 4127053; Merck Millipore, MAB318, Lot#3990619), GIRK2 (Abcam, ab259909, Lot# GR3401320‐4), NDST3 (Novus Biologicals, NBP2‐19501, Lot# 40723), DAT (Merck Millipore, MAB369) and histone modification marker H3K27ac (Abcam, AB4729, Lot# 1059037‐6).

Techniques: Expressing, RNA Sequencing, Gene Expression, Single Cell

Comprehensive analysis of spatial transcriptomics and epigenetic modulation following NDST3 treatment in a PD model. A) Heatmap showing gene expression patterns in each cluster. ** p < 0.01, and **** p < 0.0001. B) Gene concept network plot displaying genes enriched in catabolic, metabolic, and wound healing GO categories. The top 30 most differentially expressed genes comparing 6‐OHDA versus Sham and 6‐OHDA+NDST3 versus 6‐OHDA. Node color intensity represents the log2 fold‐change of gene expression. C) Cell‐cell communication network plot illustrating interactions among three distinct cell clusters in 6‐OHDA‐induced PD model (left panel) and NDST3‐treated PD model (right panel), based on ligand–receptor pair probabilities using the CellChat database. Line thickness indicates proportionality to the number of interactions. D) Spatial localization of dopamine‐related markers. E) Spatial mapping of dopaminergic lineage markers identified via scRNA‐Seq. F) Heatmap visualization of CUT&RUN and ATAC‐Seq signal intensity ±2 kb around the TSS. G) Immunofluorescence images showing H3K27ac and TH‐positive cells in the Sham, 6‐OHDA‐induced PD mice, and NDST3‐treated PD mice. Scale bar = 50 µm. H) Venn diagram illustrating overlapping genes among DEGs from RNA‐Seq, scRNA‐Seq Cluster 9, CUT&RUN peak, and ATAC‐Seq peak. Average signal plot of I) CUT&RUN and J) ATAC‐seq signals at over‐enriched TSS regions of the Ncoa7 gene. K) Structure of NDST3‐NCOA7‐H3K27ac complex. Blue – NDST3, Green – NCOA7, and Red – H3K27ac. The yellow boundary represents the interaction region.

Journal: Advanced Science

Article Title: NDST3‐Induced Epigenetic Reprogramming Reverses Neurodegeneration in Parkinson's Disease

doi: 10.1002/advs.202507323

Figure Lengend Snippet: Comprehensive analysis of spatial transcriptomics and epigenetic modulation following NDST3 treatment in a PD model. A) Heatmap showing gene expression patterns in each cluster. ** p < 0.01, and **** p < 0.0001. B) Gene concept network plot displaying genes enriched in catabolic, metabolic, and wound healing GO categories. The top 30 most differentially expressed genes comparing 6‐OHDA versus Sham and 6‐OHDA+NDST3 versus 6‐OHDA. Node color intensity represents the log2 fold‐change of gene expression. C) Cell‐cell communication network plot illustrating interactions among three distinct cell clusters in 6‐OHDA‐induced PD model (left panel) and NDST3‐treated PD model (right panel), based on ligand–receptor pair probabilities using the CellChat database. Line thickness indicates proportionality to the number of interactions. D) Spatial localization of dopamine‐related markers. E) Spatial mapping of dopaminergic lineage markers identified via scRNA‐Seq. F) Heatmap visualization of CUT&RUN and ATAC‐Seq signal intensity ±2 kb around the TSS. G) Immunofluorescence images showing H3K27ac and TH‐positive cells in the Sham, 6‐OHDA‐induced PD mice, and NDST3‐treated PD mice. Scale bar = 50 µm. H) Venn diagram illustrating overlapping genes among DEGs from RNA‐Seq, scRNA‐Seq Cluster 9, CUT&RUN peak, and ATAC‐Seq peak. Average signal plot of I) CUT&RUN and J) ATAC‐seq signals at over‐enriched TSS regions of the Ncoa7 gene. K) Structure of NDST3‐NCOA7‐H3K27ac complex. Blue – NDST3, Green – NCOA7, and Red – H3K27ac. The yellow boundary represents the interaction region.

Article Snippet: Slices were incubated with primary antibodies targeting dopaminergic neuron markers TH (Merck Millipore, AB152, Lot# 4127053; Merck Millipore, MAB318, Lot#3990619), GIRK2 (Abcam, ab259909, Lot# GR3401320‐4), NDST3 (Novus Biologicals, NBP2‐19501, Lot# 40723), DAT (Merck Millipore, MAB369) and histone modification marker H3K27ac (Abcam, AB4729, Lot# 1059037‐6).

Techniques: Spatial Transcriptomics, Gene Expression, Immunofluorescence, RNA Sequencing

Single‐cell and spatial transcriptome landscape of healthy and fibrotic kidneys after unilateral ischemia‐reperfusion injury (UIRI). a) Schematic representation of single‐cell RNA sequencing (scRNA‐seq) and spatial transcriptomics (ST) of kidneys from the sham and 10‐day UIRI mice, graphically designed with Biorender ( https://www.biorender.com/ ). b) t‐SNE plot illustrating the intricate cellular diversity in fibrotic kidneys, demonstrating distinct clusters representing glomerular endothelial cells (GEC), podocytes (Podo), mesangial cells (Mesa), Bowman's capsule epithelium (BC), proximal tubules (PT), descending limbs of Henle (DLOH), ascending limbs of Henle (ALOH), distal tubules (DT), principal cells (PC), intercalated cells (IC), fibroblasts (Fib), smooth muscle cells (SMC), extraglomerular endothelial cells (EGEC), monocytes (Mono), dendritic cells (DC), macrophages (Mϕ), plasmacytoid dendritic cells (pDC), proliferating mononuclear lineage (Prolif mono_L), and neutrophils (Neu), B cells (B), T cells (T), proliferating T cells (prolif T), and natural killer cells (NK). These cell types were further categorized into four major compartments: Glomerular, Renal, Interstitium, and Immune, as indicated by color grouping in the plot. c) Bubble plot illustrating the relative proportions of major kidney cell types in sham and UIRI samples. Each dot represents the proportion of a given cell type in a specific sample group, with dot size corresponding to its relative proportion. d) A comprehensive heatmap depicting the unique marker gene signature of major renal cell types. e) UMAP plot illustrating the inferred renal cell region distribution based on integrated spatial transcriptomics data from normal (Sham) and UIRI 10D mouse kidneys, generated using the 10x Genomics Visium platform. The identified regions include glomerular cells (Glom), distinct segments of the proximal tubule (PTS1, PTS1S2, PTS2), injured proximal tubules (InjPT), ascending limbs of Henle in cortex (ALOH(C)), distal tubules (DT), connecting tubules and collecting ducts (CNT_CD), cells at the corticomedullary junction (CMJ), fibrogenic niche regions (Niche1, Niche2), the inner stripe of the outer medulla (IOM), inner medulla (IM), renal capsule (RC), and perirenal tissue (Perirenal). f) Spatial maps illustrating the anatomical distribution of renal cell regions in Sham and UIRI 10D mouse kidneys. Region colors correspond to the classifications defined in panel (e). g) Bubble plot illustrating the relative proportions of major renal cell regions in spatial transcriptomics data from sham and UIRI 10D mouse kidneys. h) Bubble plot depicting the expression patterns of marker genes across distinct renal cell regions in spatial transcriptomics data. Dot color indicates the average gene expression level within each region, while dot size represents the proportion of spatial spots expressing the gene. i) Schematic diagram of nephron segmentation by cell types. j) Comparison of kidney anatomical regions and spatial transcriptomic clusters, showing clusters in kidney tissue (top) and the corresponding Visium H&E‐stained section (bottom). k) Renal tissue structure alterations at the corticomedullary junction (CMJ) in UIRI samples, showing the formation of two distinct fibrogenic niches, Niche1 and Niche2. l) A heatmap showing the deconvolution scores of cell type compositions across different regions in Visium spatial transcriptomics data, obtained using the RCTD method. m) Spatial FeaturePlots of RCTD‐derived cell type scores in the sham (top) and UIRI (bottom) groups, with paired panels sharing a common legend.

Journal: Advanced Science

Article Title: Single Cell and Spatial Transcriptomics Define a Proinflammatory and Profibrotic Niche After Kidney Injury

doi: 10.1002/advs.202503691

Figure Lengend Snippet: Single‐cell and spatial transcriptome landscape of healthy and fibrotic kidneys after unilateral ischemia‐reperfusion injury (UIRI). a) Schematic representation of single‐cell RNA sequencing (scRNA‐seq) and spatial transcriptomics (ST) of kidneys from the sham and 10‐day UIRI mice, graphically designed with Biorender ( https://www.biorender.com/ ). b) t‐SNE plot illustrating the intricate cellular diversity in fibrotic kidneys, demonstrating distinct clusters representing glomerular endothelial cells (GEC), podocytes (Podo), mesangial cells (Mesa), Bowman's capsule epithelium (BC), proximal tubules (PT), descending limbs of Henle (DLOH), ascending limbs of Henle (ALOH), distal tubules (DT), principal cells (PC), intercalated cells (IC), fibroblasts (Fib), smooth muscle cells (SMC), extraglomerular endothelial cells (EGEC), monocytes (Mono), dendritic cells (DC), macrophages (Mϕ), plasmacytoid dendritic cells (pDC), proliferating mononuclear lineage (Prolif mono_L), and neutrophils (Neu), B cells (B), T cells (T), proliferating T cells (prolif T), and natural killer cells (NK). These cell types were further categorized into four major compartments: Glomerular, Renal, Interstitium, and Immune, as indicated by color grouping in the plot. c) Bubble plot illustrating the relative proportions of major kidney cell types in sham and UIRI samples. Each dot represents the proportion of a given cell type in a specific sample group, with dot size corresponding to its relative proportion. d) A comprehensive heatmap depicting the unique marker gene signature of major renal cell types. e) UMAP plot illustrating the inferred renal cell region distribution based on integrated spatial transcriptomics data from normal (Sham) and UIRI 10D mouse kidneys, generated using the 10x Genomics Visium platform. The identified regions include glomerular cells (Glom), distinct segments of the proximal tubule (PTS1, PTS1S2, PTS2), injured proximal tubules (InjPT), ascending limbs of Henle in cortex (ALOH(C)), distal tubules (DT), connecting tubules and collecting ducts (CNT_CD), cells at the corticomedullary junction (CMJ), fibrogenic niche regions (Niche1, Niche2), the inner stripe of the outer medulla (IOM), inner medulla (IM), renal capsule (RC), and perirenal tissue (Perirenal). f) Spatial maps illustrating the anatomical distribution of renal cell regions in Sham and UIRI 10D mouse kidneys. Region colors correspond to the classifications defined in panel (e). g) Bubble plot illustrating the relative proportions of major renal cell regions in spatial transcriptomics data from sham and UIRI 10D mouse kidneys. h) Bubble plot depicting the expression patterns of marker genes across distinct renal cell regions in spatial transcriptomics data. Dot color indicates the average gene expression level within each region, while dot size represents the proportion of spatial spots expressing the gene. i) Schematic diagram of nephron segmentation by cell types. j) Comparison of kidney anatomical regions and spatial transcriptomic clusters, showing clusters in kidney tissue (top) and the corresponding Visium H&E‐stained section (bottom). k) Renal tissue structure alterations at the corticomedullary junction (CMJ) in UIRI samples, showing the formation of two distinct fibrogenic niches, Niche1 and Niche2. l) A heatmap showing the deconvolution scores of cell type compositions across different regions in Visium spatial transcriptomics data, obtained using the RCTD method. m) Spatial FeaturePlots of RCTD‐derived cell type scores in the sham (top) and UIRI (bottom) groups, with paired panels sharing a common legend.

Article Snippet: For the preparation of sections for Visium Spatial Transcriptomics sequencing, samples were equilibrated at −18 °C and a 10 μm thick section was cut onto the active sequencing area (6 mm x 6 mm) of a spatial barcoded slide.

Techniques: RNA Sequencing, Marker, Generated, Expressing, Gene Expression, Comparison, Staining, Derivative Assay

High‐resolution spatial transcriptomics and immunostaining reveal the TNC‐enriched fibroblast‐macrophage niche organization in fibrotic kidneys. a) Schematic diagram of the Visium HD workflow applied to kidney tissues from sham and UIRI model mice. b) UMAP visualization of integrated Visium HD spatial transcriptomics data from control mice (obtained from the 10x Genomics public dataset) and UIRI mice (this study), processed using canonical correlation analysis (CCA). This dimensionality reduction visualization reveals distinct clusters representing various renal parenchymal and stromal cell populations, including: Glomerulus, Vasculature, PTS1, PTS2, PTS1S2, InjPT, ascending limbs of Henle in cortex [ALOH(Cortex)], distal tubule and connecting tubule (DT_CNT), connecting tubule and collecting duct (CNT_CD), collecting duct in cortex [CD(Cortex)], PTS3, injured PTS3 (InjPTS3), Fibrogenic Niche, Vasa recta, loop of Henle in outer medulla [LOH(IOM)], collecting duct in outer medulla [CD(IOM)], collecting duct in inner medulla [CD(IM)], thin ascending limbs of Henle in inner medulla [tALOH(IM)], renal capsule (RC), Perirenal Fibrous tissue, and Perirenal Adipose tissue. c) Bubble plot comparing the regional distribution in Control versus UIRI 10d kidneys (Visium HD). d) Bubble plot depicting the expression patterns of marker genes across distinct renal cell regions in Visium HD data. e) Spatial maps generated using Visium HD illustrate the inferred anatomical distribution of renal cell regions in kidney tissues from Control and UIRI mice. f) Spatial Feature Plots of Visium HD data showing the spatial distribution of selected renal cell types in controls (top) and UIRI mice (bottom), based on cell‐type deconvolution using RCTD. g) A heatmap showing the correlation between NMF factors and cell‐type deconvolution scores in standard Visium spatial transcriptomics data. h) Spatial distribution of gene scores associated with the NMF factors most correlated with the fibrogenic niche, along with the contribution of key genes to each factor. i) Spatial FeaturePlots showing the anatomical distribution of Tnc expression in standard Visium. j) A heatmap showing the correlation between NMF factors and cell type deconvolution scores in Visium HD spatial transcriptomics data. k) Spatial distribution of NMF factors (NMF3 and NMF11) associated with the fibrogenic niche in Visium HD data, along with their corresponding high‐contributing genes. l) Spatial FeaturePlots showing the anatomical distribution of Tnc expression in Visium HD datasets. m) Immunofluorescence staining demonstrates colocalization of TNC with macrophages (F4/80⁺) in the CMJ interstitial region. From top to bottom: an overview merged image (Merge), followed by magnified views of TNC, Vimentin, and F4/80 staining in the same region, and an enlarged merged image (Enlarged Merge) at the bottom.

Journal: Advanced Science

Article Title: Single Cell and Spatial Transcriptomics Define a Proinflammatory and Profibrotic Niche After Kidney Injury

doi: 10.1002/advs.202503691

Figure Lengend Snippet: High‐resolution spatial transcriptomics and immunostaining reveal the TNC‐enriched fibroblast‐macrophage niche organization in fibrotic kidneys. a) Schematic diagram of the Visium HD workflow applied to kidney tissues from sham and UIRI model mice. b) UMAP visualization of integrated Visium HD spatial transcriptomics data from control mice (obtained from the 10x Genomics public dataset) and UIRI mice (this study), processed using canonical correlation analysis (CCA). This dimensionality reduction visualization reveals distinct clusters representing various renal parenchymal and stromal cell populations, including: Glomerulus, Vasculature, PTS1, PTS2, PTS1S2, InjPT, ascending limbs of Henle in cortex [ALOH(Cortex)], distal tubule and connecting tubule (DT_CNT), connecting tubule and collecting duct (CNT_CD), collecting duct in cortex [CD(Cortex)], PTS3, injured PTS3 (InjPTS3), Fibrogenic Niche, Vasa recta, loop of Henle in outer medulla [LOH(IOM)], collecting duct in outer medulla [CD(IOM)], collecting duct in inner medulla [CD(IM)], thin ascending limbs of Henle in inner medulla [tALOH(IM)], renal capsule (RC), Perirenal Fibrous tissue, and Perirenal Adipose tissue. c) Bubble plot comparing the regional distribution in Control versus UIRI 10d kidneys (Visium HD). d) Bubble plot depicting the expression patterns of marker genes across distinct renal cell regions in Visium HD data. e) Spatial maps generated using Visium HD illustrate the inferred anatomical distribution of renal cell regions in kidney tissues from Control and UIRI mice. f) Spatial Feature Plots of Visium HD data showing the spatial distribution of selected renal cell types in controls (top) and UIRI mice (bottom), based on cell‐type deconvolution using RCTD. g) A heatmap showing the correlation between NMF factors and cell‐type deconvolution scores in standard Visium spatial transcriptomics data. h) Spatial distribution of gene scores associated with the NMF factors most correlated with the fibrogenic niche, along with the contribution of key genes to each factor. i) Spatial FeaturePlots showing the anatomical distribution of Tnc expression in standard Visium. j) A heatmap showing the correlation between NMF factors and cell type deconvolution scores in Visium HD spatial transcriptomics data. k) Spatial distribution of NMF factors (NMF3 and NMF11) associated with the fibrogenic niche in Visium HD data, along with their corresponding high‐contributing genes. l) Spatial FeaturePlots showing the anatomical distribution of Tnc expression in Visium HD datasets. m) Immunofluorescence staining demonstrates colocalization of TNC with macrophages (F4/80⁺) in the CMJ interstitial region. From top to bottom: an overview merged image (Merge), followed by magnified views of TNC, Vimentin, and F4/80 staining in the same region, and an enlarged merged image (Enlarged Merge) at the bottom.

Article Snippet: For the preparation of sections for Visium Spatial Transcriptomics sequencing, samples were equilibrated at −18 °C and a 10 μm thick section was cut onto the active sequencing area (6 mm x 6 mm) of a spatial barcoded slide.

Techniques: Immunostaining, Control, Expressing, Marker, Generated, Immunofluorescence, Staining

TLR4 knockout in macrophages attenuates renal inflammation and renal fibrosis in vivo. a) The diagram shows the experimental protocol. Bone marrow chimera models were established by transplanting the WT bone marrow to WT mice, or TLR4 KO bone marrow to WT mice. Mice were irradiated at a single dose of 1100 Rads and then underwent bone marrow transplantation. After 8 weeks of successful transplantation, a unilateral ischemia‐reperfusion (UIRI) model was established. b) PCR‐based identification of kidney genotypes in the recipient mice of bone marrow transplantation models using TLR4 mutation site primers and wild‐type site primers, respectively. c,d) Graphic presentations show serum creatinine (Scr) (c) and blood urea nitrogen (BUN) (d) levels in different groups as indicated at 11 days after IRI. * p < 0.05 versus WT‐WT (n = 4–6). e,f) Western blot analyses show renal expression of TLR4, p‐P65, and P65 in different groups as indicated. Representative Western blot (e) and quantitative data (f) are shown. * p < 0.05 versus WT‐WT (n = 4–6). g) Representative micrographs show renal expression and co‐localization of TLR4 and F4/80 by immunofluorescence staining in different groups as indicated. The areas between the dashed lines represent the corticomedullary junction of the kidney. h,i) Western blot analyses show renal expression of MR, Arg‐1, iNOS, TNF‐α, and CCL2 in different groups as indicated. Representative Western blot (h) and quantitative data (i) are shown. * p < 0.05 versus WT‐WT (n = 4–6). j,k) Western blot analyses show renal expression of TNC, FN, and α‐SMA in different groups as indicated. Representative Western blot (j) and quantitative data (k) are shown. * p < 0.05 versus WT‐WT (n = 4–6). l) A schematic diagram shows a crucial role of TNC in organizing the proinflammatory and profibrotic niche. By integrating single‐cell RNA sequencing and spatial transcriptomics, we unveil TNC as a central organizer of the proinflammatory and profibrotic niche in kidney fibrosis. TNC promotes macrophage activation through TLR4/NF‐κB signaling, leading to macrophage activation, proliferation, and cytokine production.

Journal: Advanced Science

Article Title: Single Cell and Spatial Transcriptomics Define a Proinflammatory and Profibrotic Niche After Kidney Injury

doi: 10.1002/advs.202503691

Figure Lengend Snippet: TLR4 knockout in macrophages attenuates renal inflammation and renal fibrosis in vivo. a) The diagram shows the experimental protocol. Bone marrow chimera models were established by transplanting the WT bone marrow to WT mice, or TLR4 KO bone marrow to WT mice. Mice were irradiated at a single dose of 1100 Rads and then underwent bone marrow transplantation. After 8 weeks of successful transplantation, a unilateral ischemia‐reperfusion (UIRI) model was established. b) PCR‐based identification of kidney genotypes in the recipient mice of bone marrow transplantation models using TLR4 mutation site primers and wild‐type site primers, respectively. c,d) Graphic presentations show serum creatinine (Scr) (c) and blood urea nitrogen (BUN) (d) levels in different groups as indicated at 11 days after IRI. * p < 0.05 versus WT‐WT (n = 4–6). e,f) Western blot analyses show renal expression of TLR4, p‐P65, and P65 in different groups as indicated. Representative Western blot (e) and quantitative data (f) are shown. * p < 0.05 versus WT‐WT (n = 4–6). g) Representative micrographs show renal expression and co‐localization of TLR4 and F4/80 by immunofluorescence staining in different groups as indicated. The areas between the dashed lines represent the corticomedullary junction of the kidney. h,i) Western blot analyses show renal expression of MR, Arg‐1, iNOS, TNF‐α, and CCL2 in different groups as indicated. Representative Western blot (h) and quantitative data (i) are shown. * p < 0.05 versus WT‐WT (n = 4–6). j,k) Western blot analyses show renal expression of TNC, FN, and α‐SMA in different groups as indicated. Representative Western blot (j) and quantitative data (k) are shown. * p < 0.05 versus WT‐WT (n = 4–6). l) A schematic diagram shows a crucial role of TNC in organizing the proinflammatory and profibrotic niche. By integrating single‐cell RNA sequencing and spatial transcriptomics, we unveil TNC as a central organizer of the proinflammatory and profibrotic niche in kidney fibrosis. TNC promotes macrophage activation through TLR4/NF‐κB signaling, leading to macrophage activation, proliferation, and cytokine production.

Article Snippet: For the preparation of sections for Visium Spatial Transcriptomics sequencing, samples were equilibrated at −18 °C and a 10 μm thick section was cut onto the active sequencing area (6 mm x 6 mm) of a spatial barcoded slide.

Techniques: Knock-Out, In Vivo, Irradiation, Transplantation Assay, Mutagenesis, Western Blot, Expressing, Immunofluorescence, Staining, RNA Sequencing, Activation Assay

ACTB and GAPDH mRNA expression variation in sections from 13 primary melanoma tumors. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. (e) Displays variable length of GAPDH fragments amplified by RT-PCR. Base pair (bp) markers of 100 bps and 200 bps are shown at the left. Bottom panels showing corresponding Cq values for ACTB and GAPDH in qRT-PCR. Cq, quantification cycle.

Journal: Melanoma Research

Article Title: Identification of robust reference genes for studies of gene expression in FFPE melanoma samples and melanoma cell lines

doi: 10.1097/CMR.0000000000000644

Figure Lengend Snippet: ACTB and GAPDH mRNA expression variation in sections from 13 primary melanoma tumors. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. (e) Displays variable length of GAPDH fragments amplified by RT-PCR. Base pair (bp) markers of 100 bps and 200 bps are shown at the left. Bottom panels showing corresponding Cq values for ACTB and GAPDH in qRT-PCR. Cq, quantification cycle.

Article Snippet: The following TaqMan assays were applied: Candidate reference genes: ACTB: Hs01060665_g1, B2M: Hs99999907_m1, CASC3: Hs00201226_m1, CLTA: Hs01125777_g1, EEF1A1: Hs00265885_g1, GAPDH: Hs02758991_g1, GUSB: Hs00939627_m1, HMBS: Hs00609296_g1, HPRT1: Hs02800695_m1, IPO8: Hs00183533_m1, MRPL19: Hs01040217_m1, RBM23: Hs01016973_m1, POLR2A: Hs01108265_m1, PPIA: Hs04194521_s1, RPLP0: Hs02992885_s1, PUM1: Hs00472881_m1, SAP130: Hs00368617_m1, TBP: Hs00427620_m1, TFRC: Hs00951083_m1, UBC: Hs01867132_s1, PEX16: Hs00191337_m1, ENGASE: Hs00224267_m1, RPS2: Hs01034573_g1, ZNF70: Hs01934521_s1.

Techniques: Expressing, Amplification, Reverse Transcription Polymerase Chain Reaction, Quantitative RT-PCR

ACTB and GAPDH expression variation in macro-dissected non-cancerous epidermal tissue samples. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. The epidermal sections were prepared from patient samples of a selected subgroup of patients in the cohort presented in Fig. (corresponding numbers between melanomas/patients and cutaneous sections are shown below each diagram). (e) Displays variable length of GAPDH fragments detected by RT-PCR. Bp markers are shown at the left. Bottom panels show corresponding Cq values for ACTB and GAPDH . The epidermal sections are from a selected group of patients from Fig. (corresponding numbers between tumors and cutaneous sections are shown). Cq, quantification cycle.

Journal: Melanoma Research

Article Title: Identification of robust reference genes for studies of gene expression in FFPE melanoma samples and melanoma cell lines

doi: 10.1097/CMR.0000000000000644

Figure Lengend Snippet: ACTB and GAPDH expression variation in macro-dissected non-cancerous epidermal tissue samples. (a and c) Display the raw inter-tumor Cq variation and (b and d) display the raw intra-tumor Cq variation of ACTB and GAPDH , respectively. The epidermal sections were prepared from patient samples of a selected subgroup of patients in the cohort presented in Fig. (corresponding numbers between melanomas/patients and cutaneous sections are shown below each diagram). (e) Displays variable length of GAPDH fragments detected by RT-PCR. Bp markers are shown at the left. Bottom panels show corresponding Cq values for ACTB and GAPDH . The epidermal sections are from a selected group of patients from Fig. (corresponding numbers between tumors and cutaneous sections are shown). Cq, quantification cycle.

Article Snippet: The following TaqMan assays were applied: Candidate reference genes: ACTB: Hs01060665_g1, B2M: Hs99999907_m1, CASC3: Hs00201226_m1, CLTA: Hs01125777_g1, EEF1A1: Hs00265885_g1, GAPDH: Hs02758991_g1, GUSB: Hs00939627_m1, HMBS: Hs00609296_g1, HPRT1: Hs02800695_m1, IPO8: Hs00183533_m1, MRPL19: Hs01040217_m1, RBM23: Hs01016973_m1, POLR2A: Hs01108265_m1, PPIA: Hs04194521_s1, RPLP0: Hs02992885_s1, PUM1: Hs00472881_m1, SAP130: Hs00368617_m1, TBP: Hs00427620_m1, TFRC: Hs00951083_m1, UBC: Hs01867132_s1, PEX16: Hs00191337_m1, ENGASE: Hs00224267_m1, RPS2: Hs01034573_g1, ZNF70: Hs01934521_s1.

Techniques: Expressing, Reverse Transcription Polymerase Chain Reaction

Evaluation of reference genes stability in melanoma cell lines. Expression variation of candidate reference genes in melanoma cell lines is displayed in (a–c). (a) Raw Cq values of the 24 candidate reference genes across the cultured melanoma cell lines; FM3, FM82, FM88 and FM92, measured by qRT-PCR. (b) Gene expression of the most stable genes from (a) across nine additional melanoma cell lines. (c) Differences in gene expression (ΔCq values) across all 13 melanoma cell lines. Cq, quantification cycle. For each gene, the total variation between measured Cq’s across all 13 melanoma cell lines is shown. In (d), the geNorm evaluation of reference genes is displayed. The seven candidate reference genes evaluated using the geNorm algorithm. The average stability measure M is displayed in gray for the two most stable genes, RPS2 and CASC3 , and in black for the remaining genes. Gene names are indicated below the bars. In (e), NormFinder evaluation of reference genes is displayed. Stability of the seven selected candidate reference genes across 13 melanoma cell lines without regard to genetic subgroup evaluated using the NormFinder algorithm. The most stable genes, CASC3 and RPS2 , are displayed in gray, and the remaining genes are shown in black. (f) RNAseq-based validation of qRT-PCR-based relative gene expression levels of LRP1 , ACTB and GAPDH in 31-D3 and 35-G7 melanoma cells. qRT-PCR-based gene expression levels were normalized using reference genes CASC3 and RPS2 . RNAseq reads per gene were normalized to gene length. RNAseq expression ratios were calculated as the normalized gene read for each gene in 31-D3 divided by the normalized gene read for each gene in 35-G7. qRT-PCR expression ratios equals RQ values. (g) Upper panel: qRT-PCR ΔCqs for LRP1 across 13 melanoma cell lines. Mid panel: ddPCR ratios for LRP1 across 13 melanoma cell lines. Lower panel: correlation between qRT-PCR ΔCqs and ddPCR ratios. P < 0.0001. (h) Upper panel: qRT-PCR ΔCqs for ACTB across 13 melanoma cell lines. Mid panel: ddPCR ratios for ACTB across 13 melanoma cell lines. Lower panel: correlation between qRT-PCR ΔCqs and ddPCR ratios. P < 0.0001. (i) Upper panel: qRT-PCR ΔCqs for GAPDH across 13 melanoma cell lines. Mid panel: ddPCR ratios for GAPDH across 13 melanoma cell lines. Lower panel: correlation between qRT-PCR ΔCqs and ddPCR ratios. P < 0.0001. qRT-PCR- and ddPCR-based gene expression levels were normalized using a geometric mean of the expression of reference genes CASC3 and RPS2 . ddPCR, droplet digital-PCR; RNAseq, RNA sequencing; RQ, relative quantification.

Journal: Melanoma Research

Article Title: Identification of robust reference genes for studies of gene expression in FFPE melanoma samples and melanoma cell lines

doi: 10.1097/CMR.0000000000000644

Figure Lengend Snippet: Evaluation of reference genes stability in melanoma cell lines. Expression variation of candidate reference genes in melanoma cell lines is displayed in (a–c). (a) Raw Cq values of the 24 candidate reference genes across the cultured melanoma cell lines; FM3, FM82, FM88 and FM92, measured by qRT-PCR. (b) Gene expression of the most stable genes from (a) across nine additional melanoma cell lines. (c) Differences in gene expression (ΔCq values) across all 13 melanoma cell lines. Cq, quantification cycle. For each gene, the total variation between measured Cq’s across all 13 melanoma cell lines is shown. In (d), the geNorm evaluation of reference genes is displayed. The seven candidate reference genes evaluated using the geNorm algorithm. The average stability measure M is displayed in gray for the two most stable genes, RPS2 and CASC3 , and in black for the remaining genes. Gene names are indicated below the bars. In (e), NormFinder evaluation of reference genes is displayed. Stability of the seven selected candidate reference genes across 13 melanoma cell lines without regard to genetic subgroup evaluated using the NormFinder algorithm. The most stable genes, CASC3 and RPS2 , are displayed in gray, and the remaining genes are shown in black. (f) RNAseq-based validation of qRT-PCR-based relative gene expression levels of LRP1 , ACTB and GAPDH in 31-D3 and 35-G7 melanoma cells. qRT-PCR-based gene expression levels were normalized using reference genes CASC3 and RPS2 . RNAseq reads per gene were normalized to gene length. RNAseq expression ratios were calculated as the normalized gene read for each gene in 31-D3 divided by the normalized gene read for each gene in 35-G7. qRT-PCR expression ratios equals RQ values. (g) Upper panel: qRT-PCR ΔCqs for LRP1 across 13 melanoma cell lines. Mid panel: ddPCR ratios for LRP1 across 13 melanoma cell lines. Lower panel: correlation between qRT-PCR ΔCqs and ddPCR ratios. P < 0.0001. (h) Upper panel: qRT-PCR ΔCqs for ACTB across 13 melanoma cell lines. Mid panel: ddPCR ratios for ACTB across 13 melanoma cell lines. Lower panel: correlation between qRT-PCR ΔCqs and ddPCR ratios. P < 0.0001. (i) Upper panel: qRT-PCR ΔCqs for GAPDH across 13 melanoma cell lines. Mid panel: ddPCR ratios for GAPDH across 13 melanoma cell lines. Lower panel: correlation between qRT-PCR ΔCqs and ddPCR ratios. P < 0.0001. qRT-PCR- and ddPCR-based gene expression levels were normalized using a geometric mean of the expression of reference genes CASC3 and RPS2 . ddPCR, droplet digital-PCR; RNAseq, RNA sequencing; RQ, relative quantification.

Article Snippet: The following TaqMan assays were applied: Candidate reference genes: ACTB: Hs01060665_g1, B2M: Hs99999907_m1, CASC3: Hs00201226_m1, CLTA: Hs01125777_g1, EEF1A1: Hs00265885_g1, GAPDH: Hs02758991_g1, GUSB: Hs00939627_m1, HMBS: Hs00609296_g1, HPRT1: Hs02800695_m1, IPO8: Hs00183533_m1, MRPL19: Hs01040217_m1, RBM23: Hs01016973_m1, POLR2A: Hs01108265_m1, PPIA: Hs04194521_s1, RPLP0: Hs02992885_s1, PUM1: Hs00472881_m1, SAP130: Hs00368617_m1, TBP: Hs00427620_m1, TFRC: Hs00951083_m1, UBC: Hs01867132_s1, PEX16: Hs00191337_m1, ENGASE: Hs00224267_m1, RPS2: Hs01034573_g1, ZNF70: Hs01934521_s1.

Techniques: Expressing, Cell Culture, Quantitative RT-PCR, Gene Expression, Biomarker Discovery, Digital PCR, RNA Sequencing, Quantitative Proteomics

(A) Representative images and quantification of CCR7 + DCs (panCK − HLA-DR + LAMP3 + , yellow) near BVs (CD31 + PDPN − , magenta), or LVs (CD31 + PDPN + , cyan) in human tumors (HNSCC, NSCLC, and EC). Scale bar represents 20 μm. Whole-tumor sections were analyzed for EC and NSCLC. Numbers of fields of view (FOVs) analyzed per HNSCC sample are as follows: HNSCC1–04 n = 7; HNSCC1–06 n = 16; HNSCC1–07 n = 11; HNSCC2–01 n = 126; HNSCC2–06 n = 455; HNSCC2–09 n = 180; HNSCC2–11 n = 122; HNSCC2–12 n = 79; HNSCC2–15 n = 205; HNSCC2–26 n = 293; HNSCC2–35 n = 175. One bar = one patient . (B) Representative images and quantification of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) or LVs (CD31 + LYVE-1 + ; cyan) in mouse tumors (MC38, B16F10, and D4M3.A-OVA). Scale bar represents 10 μm. Whole-tumor sections were analyzed. One bar = one mouse. (C) Frequencies of BV-, LV- and non-vessel-associated CCR7 + DCs in mouse MC38 tumors 3 days post anti-CD40 or anti-PD-1 treatment. Whole-tumor sections were analyzed. One bar = one mouse. (D) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccr7 ko/wt and Ccr7 ko/ko mice, 3 days post anti-PD-1 treatment. (Right) Distribution of the area of CCR7 + DC surfaces in clusters relative to their distance to closest BVs and plotted as percentage of total CCR7 + DC cluster area. CCR7 + DC surfaces from clusters associated with LVs and those not in clusters were excluded from the analysis. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = average value of all clusters in each genotype ( Ccr7 ko/ko n = 5 mice, 56 clusters; Ccr7 wt /ko n = 6 mice, 28 clusters; and Ccr7 wt /wt n = 3 mice, 19 clusters). Two-way ANOVA with multiple comparisons, mean with SEM; **** p < 0.0001 for comparison at 10 and 20 μm from closest BVs. (E) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) and Ccl19 ( Ccl19 -eYFP + Tomato + ; white) in Ccl19 -ieYFP reporter mice (left image) or CCL21 (white, right image) in MC38 tumors. (Right) Frequencies of perivascular CCR7 + DC clusters associated with Ccl19 -covered BVs or within CCL21 + areas of the tumors among total perivascular CCR7 + DC clusters. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse. Unpaired t test, mean with SEM; *** p < 0.001. (F) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccl19 wt/wt and Ccl19 ko/ko mice, 2 days post anti-PD-1treatment. (Right) Quantification of BV- or LV-associated CCR7 + DC clusters in MC38 tumors from Ccl19 wt/wt and Ccl19 ko/ko mice. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse, whiskers represent min to max. Unpaired t test; * p < 0.05. (G) Heatmap depicts log 2 -transformed averaged expression of Ccl19 in indicated immune and non-immune populations in the TME of multiple mouse tumor models (breast, , lung [and GSE201247 ], and pancreatic , ). (H) (Left) Synthetic images of CCR7 + DCs (yellow), blood endothelial cells (BECs; magenta), lymphatic endothelial cells (LECs; cyan), and CCL19 + fibroblasts (green) in one representative NSCLC patient analyzed by spatial transcriptomics. (Right) Box plots depict the enrichment scores of CCL19 + fibroblasts within the neighborhood of BV-associated CCR7 + DCs, in four human NSCLC. Data are shown for both permuted (median enrichment scores from 1,000 permutations) and observed datasets. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one sample. Paired t test, whiskers represent mean to max; * p < 0.05. (I) Heatmap depicts log 2 -transformed averaged expression of CCL19 in indicated immune and non-immune populations in the TME of multiple human cancer types (HNSCC, n = 40, n = 18 patients; CRC, n = 23, n = 64 patients; ESCC, n = 58 patients ; NSCLC, n = 32, n = 7 patients; BRCA, n = 29 patients ; and PRCA, n = 18 patients ). A cross indicates that the cellular population was not detected. See also – .

Journal: Immunity

Article Title: Positioning and reversible suppression of CCR7 + dendritic cells in perivascular tumor niches shape cancer immunity

doi: 10.1016/j.immuni.2025.11.020

Figure Lengend Snippet: (A) Representative images and quantification of CCR7 + DCs (panCK − HLA-DR + LAMP3 + , yellow) near BVs (CD31 + PDPN − , magenta), or LVs (CD31 + PDPN + , cyan) in human tumors (HNSCC, NSCLC, and EC). Scale bar represents 20 μm. Whole-tumor sections were analyzed for EC and NSCLC. Numbers of fields of view (FOVs) analyzed per HNSCC sample are as follows: HNSCC1–04 n = 7; HNSCC1–06 n = 16; HNSCC1–07 n = 11; HNSCC2–01 n = 126; HNSCC2–06 n = 455; HNSCC2–09 n = 180; HNSCC2–11 n = 122; HNSCC2–12 n = 79; HNSCC2–15 n = 205; HNSCC2–26 n = 293; HNSCC2–35 n = 175. One bar = one patient . (B) Representative images and quantification of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) or LVs (CD31 + LYVE-1 + ; cyan) in mouse tumors (MC38, B16F10, and D4M3.A-OVA). Scale bar represents 10 μm. Whole-tumor sections were analyzed. One bar = one mouse. (C) Frequencies of BV-, LV- and non-vessel-associated CCR7 + DCs in mouse MC38 tumors 3 days post anti-CD40 or anti-PD-1 treatment. Whole-tumor sections were analyzed. One bar = one mouse. (D) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccr7 ko/wt and Ccr7 ko/ko mice, 3 days post anti-PD-1 treatment. (Right) Distribution of the area of CCR7 + DC surfaces in clusters relative to their distance to closest BVs and plotted as percentage of total CCR7 + DC cluster area. CCR7 + DC surfaces from clusters associated with LVs and those not in clusters were excluded from the analysis. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = average value of all clusters in each genotype ( Ccr7 ko/ko n = 5 mice, 56 clusters; Ccr7 wt /ko n = 6 mice, 28 clusters; and Ccr7 wt /wt n = 3 mice, 19 clusters). Two-way ANOVA with multiple comparisons, mean with SEM; **** p < 0.0001 for comparison at 10 and 20 μm from closest BVs. (E) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) and Ccl19 ( Ccl19 -eYFP + Tomato + ; white) in Ccl19 -ieYFP reporter mice (left image) or CCL21 (white, right image) in MC38 tumors. (Right) Frequencies of perivascular CCR7 + DC clusters associated with Ccl19 -covered BVs or within CCL21 + areas of the tumors among total perivascular CCR7 + DC clusters. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse. Unpaired t test, mean with SEM; *** p < 0.001. (F) (Left) Representative images of CCR7 + DCs (FSCN1 + ; yellow) located near BVs (CD31 + LYVE-1 − ; magenta) in MC38 tumors inoculated in Ccl19 wt/wt and Ccl19 ko/ko mice, 2 days post anti-PD-1treatment. (Right) Quantification of BV- or LV-associated CCR7 + DC clusters in MC38 tumors from Ccl19 wt/wt and Ccl19 ko/ko mice. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one mouse, whiskers represent min to max. Unpaired t test; * p < 0.05. (G) Heatmap depicts log 2 -transformed averaged expression of Ccl19 in indicated immune and non-immune populations in the TME of multiple mouse tumor models (breast, , lung [and GSE201247 ], and pancreatic , ). (H) (Left) Synthetic images of CCR7 + DCs (yellow), blood endothelial cells (BECs; magenta), lymphatic endothelial cells (LECs; cyan), and CCL19 + fibroblasts (green) in one representative NSCLC patient analyzed by spatial transcriptomics. (Right) Box plots depict the enrichment scores of CCL19 + fibroblasts within the neighborhood of BV-associated CCR7 + DCs, in four human NSCLC. Data are shown for both permuted (median enrichment scores from 1,000 permutations) and observed datasets. Scale bar represents 20 μm. Whole-tumor sections were analyzed. One dot = one sample. Paired t test, whiskers represent mean to max; * p < 0.05. (I) Heatmap depicts log 2 -transformed averaged expression of CCL19 in indicated immune and non-immune populations in the TME of multiple human cancer types (HNSCC, n = 40, n = 18 patients; CRC, n = 23, n = 64 patients; ESCC, n = 58 patients ; NSCLC, n = 32, n = 7 patients; BRCA, n = 29 patients ; and PRCA, n = 18 patients ). A cross indicates that the cellular population was not detected. See also – .

Article Snippet: InVivoMAb anti-mouse CD40 (clone FGK45) , BioXcell , Cat#BE0016-2.

Techniques: Comparison, Transformation Assay, Expressing, Spatial Transcriptomics

(A) (Left) Scheme outlining the experimental setup for bulk RNA-seq analyses of tumor-derived CCR7 + DCs. (Right) GO pathway enrichment analyses performed on differentially expressed genes (DEGs) in CCR7 + DCs in MC38 tumors ( n = 4) from Treg-depleted ( FoxP3 -DTR) compared with Treg-sufficient (WT) mice. Bar plot indicates the −log 10 raw binomial p -values of the top 10 most enriched pathways in CCR7 + DCs. (B) (Left) Experimental setup for ex vivo stimulation of OT-I CD8 + T cells with tumor CCR7 + DCs. (Right) Percentage of OT-I CD8 + T cells that proliferated after 5-day culture with OVA 257–264 peptides-loaded CCR7 + DCs isolated from WT or Treg-depleted tumors. As a control, CCR7 + DCs without OVA 257–264 peptides were used. Two-way ANOVA with multiple comparisons, whiskers represent min to max; ** p < 0.01. (C) (Left) Relative gene expression levels analyzed by bulk RNA-seq. Each dot represents one mouse ( n = 4), whiskers represent mean to max. Unpaired t test with multiple comparisons; * p < 0.05. (Right) Representative histogram of CD40 protein expression and relative mean fluorescence intensity (MFI) measured by FACS and expressed both as normalized values and absolute MFI. Each dot represents one mouse ( n = 18), whiskers represent min to max. Unpaired t test; ** p < 0.01. (D) Analyses of cDCs in tumor-draining lymph nodes. Absolute cell counts (left, n = 10) and MFI of CD40 expression (right, n = 18) measured by FACS in migratory cDCs (CCR7 + CD8α − ) from WT or Treg-depleted mice. Whiskers represent mean to max. (E) (Left) Experimental setup for ex vivo analyses of tumor CCR7 + DCs isolated from anti-PD-1-treated mice that received or not αCD25 NIB mAbs. (Right) CD40 protein expression measured by FACS and expressed both as normalized values and absolute MFI. Each dot represents one mouse ( n = 4 WT and n = 6 FoxP3-DTR), whiskers represent min to max. Unpaired t test; ** p < 0.01. (F) (Left) Overall survival analyses of MC38 tumor-bearing mice treated, or not treated, with αPD-1 and αCD25 NIB mAbs, and in which CD4 + or CD8 + cells were depleted or not ( n = 8 or 9 mice/group). Log-rank Mantel-Cox test; * p < 0.05, *** p < 0.001, and *** p < 0.0001. (Right) Percentage of tumor-free mice on day 60 in the indicated treatment groups. (G) (Left) Experimental setup for ex vivo stimulation of OT-I CD8 + T cells with tumor CCR7 + DCs as in (B). The DCs were obtained from mice receiving anti-PD-1 immunotherapy and that were treated or not with αCD25 NIB mAbs. (Right) Percentage of OT-I CD8 + T cells that proliferated after 5-day culture with OVA 257–264 peptide-loaded CCR7 + DCs. Each dot represents one mouse ( n = 8 and n = 7), whiskers represent min to max. Two-way ANOVA with multiple comparisons; * p < 0.05. (H) (Left) Scheme outlining bone marrow chimeras with inducible Cd40 -deficiency in cDCs and the treatment schedule. (Right) Growth curves of MC38 tumors inoculated in zDC iDTR : Cd40 WT and zDC iDTR : Cd40 KO bone marrow chimeras treated with αPD-1, αCD25 NIB , or αPD-1 + αCD25NIB combination ( n = 8–10 mice/group). Mean with SEM. Two-way ANOVA with multiple comparisons; * p < 0.05 and **** p < 0.0001. See also and .

Journal: Immunity

Article Title: Positioning and reversible suppression of CCR7 + dendritic cells in perivascular tumor niches shape cancer immunity

doi: 10.1016/j.immuni.2025.11.020

Figure Lengend Snippet: (A) (Left) Scheme outlining the experimental setup for bulk RNA-seq analyses of tumor-derived CCR7 + DCs. (Right) GO pathway enrichment analyses performed on differentially expressed genes (DEGs) in CCR7 + DCs in MC38 tumors ( n = 4) from Treg-depleted ( FoxP3 -DTR) compared with Treg-sufficient (WT) mice. Bar plot indicates the −log 10 raw binomial p -values of the top 10 most enriched pathways in CCR7 + DCs. (B) (Left) Experimental setup for ex vivo stimulation of OT-I CD8 + T cells with tumor CCR7 + DCs. (Right) Percentage of OT-I CD8 + T cells that proliferated after 5-day culture with OVA 257–264 peptides-loaded CCR7 + DCs isolated from WT or Treg-depleted tumors. As a control, CCR7 + DCs without OVA 257–264 peptides were used. Two-way ANOVA with multiple comparisons, whiskers represent min to max; ** p < 0.01. (C) (Left) Relative gene expression levels analyzed by bulk RNA-seq. Each dot represents one mouse ( n = 4), whiskers represent mean to max. Unpaired t test with multiple comparisons; * p < 0.05. (Right) Representative histogram of CD40 protein expression and relative mean fluorescence intensity (MFI) measured by FACS and expressed both as normalized values and absolute MFI. Each dot represents one mouse ( n = 18), whiskers represent min to max. Unpaired t test; ** p < 0.01. (D) Analyses of cDCs in tumor-draining lymph nodes. Absolute cell counts (left, n = 10) and MFI of CD40 expression (right, n = 18) measured by FACS in migratory cDCs (CCR7 + CD8α − ) from WT or Treg-depleted mice. Whiskers represent mean to max. (E) (Left) Experimental setup for ex vivo analyses of tumor CCR7 + DCs isolated from anti-PD-1-treated mice that received or not αCD25 NIB mAbs. (Right) CD40 protein expression measured by FACS and expressed both as normalized values and absolute MFI. Each dot represents one mouse ( n = 4 WT and n = 6 FoxP3-DTR), whiskers represent min to max. Unpaired t test; ** p < 0.01. (F) (Left) Overall survival analyses of MC38 tumor-bearing mice treated, or not treated, with αPD-1 and αCD25 NIB mAbs, and in which CD4 + or CD8 + cells were depleted or not ( n = 8 or 9 mice/group). Log-rank Mantel-Cox test; * p < 0.05, *** p < 0.001, and *** p < 0.0001. (Right) Percentage of tumor-free mice on day 60 in the indicated treatment groups. (G) (Left) Experimental setup for ex vivo stimulation of OT-I CD8 + T cells with tumor CCR7 + DCs as in (B). The DCs were obtained from mice receiving anti-PD-1 immunotherapy and that were treated or not with αCD25 NIB mAbs. (Right) Percentage of OT-I CD8 + T cells that proliferated after 5-day culture with OVA 257–264 peptide-loaded CCR7 + DCs. Each dot represents one mouse ( n = 8 and n = 7), whiskers represent min to max. Two-way ANOVA with multiple comparisons; * p < 0.05. (H) (Left) Scheme outlining bone marrow chimeras with inducible Cd40 -deficiency in cDCs and the treatment schedule. (Right) Growth curves of MC38 tumors inoculated in zDC iDTR : Cd40 WT and zDC iDTR : Cd40 KO bone marrow chimeras treated with αPD-1, αCD25 NIB , or αPD-1 + αCD25NIB combination ( n = 8–10 mice/group). Mean with SEM. Two-way ANOVA with multiple comparisons; * p < 0.05 and **** p < 0.0001. See also and .

Article Snippet: InVivoMAb anti-mouse CD40 (clone FGK45) , BioXcell , Cat#BE0016-2.

Techniques: RNA Sequencing, Derivative Assay, Ex Vivo, Isolation, Control, Gene Expression, Expressing, Fluorescence