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recombinant human efna5  (Sino Biological)


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    Sino Biological recombinant human efna5
    Bone stromal drives divergent bone colonization and immune evasion mechanisms (A) Analysis of cell-cell communication signal flow. Outgoing signal strength is shown on the x axis and incoming signal strength on the y axis, comparing the Mφ-OC and Treg-Tex archetypes with healthy samples serving as references. (B) Identification of key ligand-receptor pairs that differentially regulate the OC populations. This analysis compares the relative signaling strengths between the Mφ-OC and Treg-Tex archetypes, focusing on osteoclasts as the signal receivers (from A). (C) Schematic illustration of in vitro experimental validation for estimated signaling molecules. CD14 + monocytes isolated from human peripheral blood were enriched for osteoclastogenesis induction, with selected factors added to the culture medium to test their predicted roles in regulating differential osteoclastogenesis. Osteoclastogenesis was then evaluated by both qPCR and TRAP staining. (D) qPCR analysis of osteoclast signature genes to validate differential osteoclastogenesis regulation by estimated signaling molecules. Each signaling factor was tested using graded concentrations: TWEAK (TNFSF12; 0.1, 1, 10 ng/μL), COMP (5, 50, 500 ng/μL), and NRG1 (10, 100, 1000 ng/μL), TNFSF10 (1, 10, 100 ng/μL), SEMA4A (1, 10, 100 ng/μL), <t>EFNA5</t> (1, 10, 100 ng/μL), BMP8A (1, 10, 100 ng/μL). Each condition has five replicates. Statistical significance was assessed using one-way ANOVA, with significance levels: ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.
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    Images

    1) Product Images from "Single-cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization"

    Article Title: Single-cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization

    Journal: Cell Genomics

    doi: 10.1016/j.xgen.2025.100888

    Bone stromal drives divergent bone colonization and immune evasion mechanisms (A) Analysis of cell-cell communication signal flow. Outgoing signal strength is shown on the x axis and incoming signal strength on the y axis, comparing the Mφ-OC and Treg-Tex archetypes with healthy samples serving as references. (B) Identification of key ligand-receptor pairs that differentially regulate the OC populations. This analysis compares the relative signaling strengths between the Mφ-OC and Treg-Tex archetypes, focusing on osteoclasts as the signal receivers (from A). (C) Schematic illustration of in vitro experimental validation for estimated signaling molecules. CD14 + monocytes isolated from human peripheral blood were enriched for osteoclastogenesis induction, with selected factors added to the culture medium to test their predicted roles in regulating differential osteoclastogenesis. Osteoclastogenesis was then evaluated by both qPCR and TRAP staining. (D) qPCR analysis of osteoclast signature genes to validate differential osteoclastogenesis regulation by estimated signaling molecules. Each signaling factor was tested using graded concentrations: TWEAK (TNFSF12; 0.1, 1, 10 ng/μL), COMP (5, 50, 500 ng/μL), and NRG1 (10, 100, 1000 ng/μL), TNFSF10 (1, 10, 100 ng/μL), SEMA4A (1, 10, 100 ng/μL), EFNA5 (1, 10, 100 ng/μL), BMP8A (1, 10, 100 ng/μL). Each condition has five replicates. Statistical significance was assessed using one-way ANOVA, with significance levels: ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.
    Figure Legend Snippet: Bone stromal drives divergent bone colonization and immune evasion mechanisms (A) Analysis of cell-cell communication signal flow. Outgoing signal strength is shown on the x axis and incoming signal strength on the y axis, comparing the Mφ-OC and Treg-Tex archetypes with healthy samples serving as references. (B) Identification of key ligand-receptor pairs that differentially regulate the OC populations. This analysis compares the relative signaling strengths between the Mφ-OC and Treg-Tex archetypes, focusing on osteoclasts as the signal receivers (from A). (C) Schematic illustration of in vitro experimental validation for estimated signaling molecules. CD14 + monocytes isolated from human peripheral blood were enriched for osteoclastogenesis induction, with selected factors added to the culture medium to test their predicted roles in regulating differential osteoclastogenesis. Osteoclastogenesis was then evaluated by both qPCR and TRAP staining. (D) qPCR analysis of osteoclast signature genes to validate differential osteoclastogenesis regulation by estimated signaling molecules. Each signaling factor was tested using graded concentrations: TWEAK (TNFSF12; 0.1, 1, 10 ng/μL), COMP (5, 50, 500 ng/μL), and NRG1 (10, 100, 1000 ng/μL), TNFSF10 (1, 10, 100 ng/μL), SEMA4A (1, 10, 100 ng/μL), EFNA5 (1, 10, 100 ng/μL), BMP8A (1, 10, 100 ng/μL). Each condition has five replicates. Statistical significance was assessed using one-way ANOVA, with significance levels: ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.

    Techniques Used: In Vitro, Biomarker Discovery, Isolation, Staining

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    Article Title: Identification and characterization of Nanobodies targeting the EphA4 receptor
    Article Snippet: .. To test the inhibition of EphA7 and ephrin-A5 interaction, His-tagged human ephrin-A5 (Sino Biological, Beijing, China) was biotinylated with a five-times molar excess of EZ link NHS biotin (Thermo Fisher Scientific) as is described for the Nbs. .. Briefly, ephrin-A5 was incubated with the biotin for 2 h on ice and dialyzed in PBS with the Slide-A-Lyzer mini dialysis device (10-kDa cutoff, Thermo Fisher Scientific) to remove unbound biotin.



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    Bone stromal drives divergent bone colonization and immune evasion mechanisms (A) Analysis of cell-cell communication signal flow. Outgoing signal strength is shown on the x axis and incoming signal strength on the y axis, comparing the Mφ-OC and Treg-Tex archetypes with healthy samples serving as references. (B) Identification of key ligand-receptor pairs that differentially regulate the OC populations. This analysis compares the relative signaling strengths between the Mφ-OC and Treg-Tex archetypes, focusing on osteoclasts as the signal receivers (from A). (C) Schematic illustration of in vitro experimental validation for estimated signaling molecules. CD14 + monocytes isolated from human peripheral blood were enriched for osteoclastogenesis induction, with selected factors added to the culture medium to test their predicted roles in regulating differential osteoclastogenesis. Osteoclastogenesis was then evaluated by both qPCR and TRAP staining. (D) qPCR analysis of osteoclast signature genes to validate differential osteoclastogenesis regulation by estimated signaling molecules. Each signaling factor was tested using graded concentrations: TWEAK (TNFSF12; 0.1, 1, 10 ng/μL), COMP (5, 50, 500 ng/μL), and NRG1 (10, 100, 1000 ng/μL), TNFSF10 (1, 10, 100 ng/μL), SEMA4A (1, 10, 100 ng/μL), <t>EFNA5</t> (1, 10, 100 ng/μL), BMP8A (1, 10, 100 ng/μL). Each condition has five replicates. Statistical significance was assessed using one-way ANOVA, with significance levels: ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.
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    (a) Schematic representation of the selection process for ephrin signaling interactions. Co-immunoprecipitation mass spectrometry identified 5157 proteins, of which 1327 were differentially bound (DB; p < 0.05, FC > 1 vs. GFP). In parallel, CellChat analysis of scRNA-seq data tested 229 ligand–receptor networks, identifying 16 differentially regulated (DR; p < 0.05) interactions based on signaling strength. Ephrin signaling was selected as a key candidate pathway by intersecting both datasets, guiding further analysis of its role in aDCHS1 and hDCHS1 organoids. (b) Significant signaling pathways ranked based on differences in overall information flow within the inferred networks between aDCHS1 and hDCHS1. Pathways enriched in aDCHS1 are shown in teal, equally enriched pathways in black, and pathways enriched in hDCHS1 in yellow. (c) Fold-change differences in protein abundance from immunoprecipitation (IP) analysis between aDCHS1 and hDCHS1. (d) Representative fluorescence images of DAPI (blue), DCHS1 (green), and EPHA4 (magenta) in control 60-day-old neural organoids. V = ventricle; scale bars: 25 µm (individual channels) and 10 µm (merged image). (e) Representative fluorescence images of 60-day-old hDCHS1 and aDCHS1 neural organoids subjected to proximity ligation assay (PLA) to detect DCHS1-EPHA4 interactions. Nuclei were stained with DAPI. Images were acquired at 63× magnification. V = ventricle; scale bar: 10 µm. (f) Differential expression analysis of cell-cell communication events potentially deregulated between aDCHS1 and hDCHS1 related to the EPHA4 receptor. Dot color indicates enrichment in hDCHS1 (yellow) or aDCHS1 (teal). (g) Representative immunohistochemistry (IHC) images and quantification of PAX6+ and MEIS2+ cells in 30-day-old neural organoids derived from human iPSCs, treated with <t>EFNA5,</t> EFNB2, or left untreated. Statistical significance was assessed using a binomial test by comparing each treated condition to the untreated condition individually. For PAX6 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 23, EFNA5 = 62, EFNB2 = 45. For MEIS2 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 30, EFNA5 = 35, EFNB2 = 49. (h) Dot plot showing the expression of EPHA4, EFNA5, EFNB2, EFNB3 and EFNB1 genes in the Excitatory, Inhibitory and Striatal lineage. Dot color represents the average expression level, and dot size indicates the proportion of cells expressing each gene.
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    (a) Schematic representation of the selection process for ephrin signaling interactions. Co-immunoprecipitation mass spectrometry identified 5157 proteins, of which 1327 were differentially bound (DB; p < 0.05, FC > 1 vs. GFP). In parallel, CellChat analysis of scRNA-seq data tested 229 ligand–receptor networks, identifying 16 differentially regulated (DR; p < 0.05) interactions based on signaling strength. Ephrin signaling was selected as a key candidate pathway by intersecting both datasets, guiding further analysis of its role in aDCHS1 and hDCHS1 organoids. (b) Significant signaling pathways ranked based on differences in overall information flow within the inferred networks between aDCHS1 and hDCHS1. Pathways enriched in aDCHS1 are shown in teal, equally enriched pathways in black, and pathways enriched in hDCHS1 in yellow. (c) Fold-change differences in protein abundance from immunoprecipitation (IP) analysis between aDCHS1 and hDCHS1. (d) Representative fluorescence images of DAPI (blue), DCHS1 (green), and EPHA4 (magenta) in control 60-day-old neural organoids. V = ventricle; scale bars: 25 µm (individual channels) and 10 µm (merged image). (e) Representative fluorescence images of 60-day-old hDCHS1 and aDCHS1 neural organoids subjected to proximity ligation assay (PLA) to detect DCHS1-EPHA4 interactions. Nuclei were stained with DAPI. Images were acquired at 63× magnification. V = ventricle; scale bar: 10 µm. (f) Differential expression analysis of cell-cell communication events potentially deregulated between aDCHS1 and hDCHS1 related to the EPHA4 receptor. Dot color indicates enrichment in hDCHS1 (yellow) or aDCHS1 (teal). (g) Representative immunohistochemistry (IHC) images and quantification of PAX6+ and MEIS2+ cells in 30-day-old neural organoids derived from human iPSCs, treated with <t>EFNA5,</t> EFNB2, or left untreated. Statistical significance was assessed using a binomial test by comparing each treated condition to the untreated condition individually. For PAX6 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 23, EFNA5 = 62, EFNB2 = 45. For MEIS2 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 30, EFNA5 = 35, EFNB2 = 49. (h) Dot plot showing the expression of EPHA4, EFNA5, EFNB2, EFNB3 and EFNB1 genes in the Excitatory, Inhibitory and Striatal lineage. Dot color represents the average expression level, and dot size indicates the proportion of cells expressing each gene.
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    (a) Schematic representation of the selection process for ephrin signaling interactions. Co-immunoprecipitation mass spectrometry identified 5157 proteins, of which 1327 were differentially bound (DB; p < 0.05, FC > 1 vs. GFP). In parallel, CellChat analysis of scRNA-seq data tested 229 ligand–receptor networks, identifying 16 differentially regulated (DR; p < 0.05) interactions based on signaling strength. Ephrin signaling was selected as a key candidate pathway by intersecting both datasets, guiding further analysis of its role in aDCHS1 and hDCHS1 organoids. (b) Significant signaling pathways ranked based on differences in overall information flow within the inferred networks between aDCHS1 and hDCHS1. Pathways enriched in aDCHS1 are shown in teal, equally enriched pathways in black, and pathways enriched in hDCHS1 in yellow. (c) Fold-change differences in protein abundance from immunoprecipitation (IP) analysis between aDCHS1 and hDCHS1. (d) Representative fluorescence images of DAPI (blue), DCHS1 (green), and EPHA4 (magenta) in control 60-day-old neural organoids. V = ventricle; scale bars: 25 µm (individual channels) and 10 µm (merged image). (e) Representative fluorescence images of 60-day-old hDCHS1 and aDCHS1 neural organoids subjected to proximity ligation assay (PLA) to detect DCHS1-EPHA4 interactions. Nuclei were stained with DAPI. Images were acquired at 63× magnification. V = ventricle; scale bar: 10 µm. (f) Differential expression analysis of cell-cell communication events potentially deregulated between aDCHS1 and hDCHS1 related to the EPHA4 receptor. Dot color indicates enrichment in hDCHS1 (yellow) or aDCHS1 (teal). (g) Representative immunohistochemistry (IHC) images and quantification of PAX6+ and MEIS2+ cells in 30-day-old neural organoids derived from human iPSCs, treated with <t>EFNA5,</t> EFNB2, or left untreated. Statistical significance was assessed using a binomial test by comparing each treated condition to the untreated condition individually. For PAX6 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 23, EFNA5 = 62, EFNB2 = 45. For MEIS2 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 30, EFNA5 = 35, EFNB2 = 49. (h) Dot plot showing the expression of EPHA4, EFNA5, EFNB2, EFNB3 and EFNB1 genes in the Excitatory, Inhibitory and Striatal lineage. Dot color represents the average expression level, and dot size indicates the proportion of cells expressing each gene.
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    (a) Schematic representation of the selection process for ephrin signaling interactions. Co-immunoprecipitation mass spectrometry identified 5157 proteins, of which 1327 were differentially bound (DB; p < 0.05, FC > 1 vs. GFP). In parallel, CellChat analysis of scRNA-seq data tested 229 ligand–receptor networks, identifying 16 differentially regulated (DR; p < 0.05) interactions based on signaling strength. Ephrin signaling was selected as a key candidate pathway by intersecting both datasets, guiding further analysis of its role in aDCHS1 and hDCHS1 organoids. (b) Significant signaling pathways ranked based on differences in overall information flow within the inferred networks between aDCHS1 and hDCHS1. Pathways enriched in aDCHS1 are shown in teal, equally enriched pathways in black, and pathways enriched in hDCHS1 in yellow. (c) Fold-change differences in protein abundance from immunoprecipitation (IP) analysis between aDCHS1 and hDCHS1. (d) Representative fluorescence images of DAPI (blue), DCHS1 (green), and EPHA4 (magenta) in control 60-day-old neural organoids. V = ventricle; scale bars: 25 µm (individual channels) and 10 µm (merged image). (e) Representative fluorescence images of 60-day-old hDCHS1 and aDCHS1 neural organoids subjected to proximity ligation assay (PLA) to detect DCHS1-EPHA4 interactions. Nuclei were stained with DAPI. Images were acquired at 63× magnification. V = ventricle; scale bar: 10 µm. (f) Differential expression analysis of cell-cell communication events potentially deregulated between aDCHS1 and hDCHS1 related to the EPHA4 receptor. Dot color indicates enrichment in hDCHS1 (yellow) or aDCHS1 (teal). (g) Representative immunohistochemistry (IHC) images and quantification of PAX6+ and MEIS2+ cells in 30-day-old neural organoids derived from human iPSCs, treated with <t>EFNA5,</t> EFNB2, or left untreated. Statistical significance was assessed using a binomial test by comparing each treated condition to the untreated condition individually. For PAX6 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 23, EFNA5 = 62, EFNB2 = 45. For MEIS2 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 30, EFNA5 = 35, EFNB2 = 49. (h) Dot plot showing the expression of EPHA4, EFNA5, EFNB2, EFNB3 and EFNB1 genes in the Excitatory, Inhibitory and Striatal lineage. Dot color represents the average expression level, and dot size indicates the proportion of cells expressing each gene.
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    RNase1‐induced T‐cell dysregulation may require the internalization of RNase1 into T cells. A) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in EphA4‐knockdown (sh‐EphA4#1), ALK‐knockdown (sh‐ALK#1), or control (sh‐Ctrl) activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). B) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with different concentrations of recombinant <t>EphrinA5</t> as indicated for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). C) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), Cpd1 (10 µ m ), or RNase1 combined to Cpd1 for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). D) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), crizotinib (0.5 µ m ), or RNase1 combined to crizotinib for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). E) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. Right: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. β‐actin served as a loading control. Representative data from three independent experiments. F) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. Right: Quantitative results of Western blot of RNase1 in the left panel of (F). Quantitative data were analyzed from three independent experiments. G) Left: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. β‐actin served as a loading control. Right: Quantitative results of Western blot of RNase1 in the left panel of (G). Quantitative data were analyzed from three independent experiments. H) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), dynasore (10 µ m for 1 h treatment), or RNase1 combined with dynasore (20 µ m for 1 h treatment) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). I) Western blot analysis of the whole cell lysate (WCL), cytoplasmic, and nuclear fractions in activated Jurkat T cells (JA) and 1 µg mL −1 RNase1‐treated activated Jurkat T cells (JAR). Representative data from three independent experiments. J) Immunocytochemistry staining of RNase1 in activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Nuclei were counterstained with DAPI. Representative images of n = 2 independent replicates. Scale bar: 10 µm. Data represent mean ± S.D. ** p , 0.001–0.01, and *** p < 0.001 by two‐sided unpaired Student's t ‐test.
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    93
    R&D Systems smpk3 374 ea ephrinb1 r d systems
    RNase1‐induced T‐cell dysregulation may require the internalization of RNase1 into T cells. A) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in EphA4‐knockdown (sh‐EphA4#1), ALK‐knockdown (sh‐ALK#1), or control (sh‐Ctrl) activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). B) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with different concentrations of recombinant <t>EphrinA5</t> as indicated for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). C) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), Cpd1 (10 µ m ), or RNase1 combined to Cpd1 for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). D) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), crizotinib (0.5 µ m ), or RNase1 combined to crizotinib for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). E) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. Right: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. β‐actin served as a loading control. Representative data from three independent experiments. F) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. Right: Quantitative results of Western blot of RNase1 in the left panel of (F). Quantitative data were analyzed from three independent experiments. G) Left: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. β‐actin served as a loading control. Right: Quantitative results of Western blot of RNase1 in the left panel of (G). Quantitative data were analyzed from three independent experiments. H) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), dynasore (10 µ m for 1 h treatment), or RNase1 combined with dynasore (20 µ m for 1 h treatment) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). I) Western blot analysis of the whole cell lysate (WCL), cytoplasmic, and nuclear fractions in activated Jurkat T cells (JA) and 1 µg mL −1 RNase1‐treated activated Jurkat T cells (JAR). Representative data from three independent experiments. J) Immunocytochemistry staining of RNase1 in activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Nuclei were counterstained with DAPI. Representative images of n = 2 independent replicates. Scale bar: 10 µm. Data represent mean ± S.D. ** p , 0.001–0.01, and *** p < 0.001 by two‐sided unpaired Student's t ‐test.
    Smpk3 374 Ea Ephrinb1 R D Systems, supplied by R&D Systems, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Bone stromal drives divergent bone colonization and immune evasion mechanisms (A) Analysis of cell-cell communication signal flow. Outgoing signal strength is shown on the x axis and incoming signal strength on the y axis, comparing the Mφ-OC and Treg-Tex archetypes with healthy samples serving as references. (B) Identification of key ligand-receptor pairs that differentially regulate the OC populations. This analysis compares the relative signaling strengths between the Mφ-OC and Treg-Tex archetypes, focusing on osteoclasts as the signal receivers (from A). (C) Schematic illustration of in vitro experimental validation for estimated signaling molecules. CD14 + monocytes isolated from human peripheral blood were enriched for osteoclastogenesis induction, with selected factors added to the culture medium to test their predicted roles in regulating differential osteoclastogenesis. Osteoclastogenesis was then evaluated by both qPCR and TRAP staining. (D) qPCR analysis of osteoclast signature genes to validate differential osteoclastogenesis regulation by estimated signaling molecules. Each signaling factor was tested using graded concentrations: TWEAK (TNFSF12; 0.1, 1, 10 ng/μL), COMP (5, 50, 500 ng/μL), and NRG1 (10, 100, 1000 ng/μL), TNFSF10 (1, 10, 100 ng/μL), SEMA4A (1, 10, 100 ng/μL), EFNA5 (1, 10, 100 ng/μL), BMP8A (1, 10, 100 ng/μL). Each condition has five replicates. Statistical significance was assessed using one-way ANOVA, with significance levels: ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.

    Journal: Cell Genomics

    Article Title: Single-cell profiling of bone metastasis ecosystems from multiple cancer types reveals convergent and divergent mechanisms of bone colonization

    doi: 10.1016/j.xgen.2025.100888

    Figure Lengend Snippet: Bone stromal drives divergent bone colonization and immune evasion mechanisms (A) Analysis of cell-cell communication signal flow. Outgoing signal strength is shown on the x axis and incoming signal strength on the y axis, comparing the Mφ-OC and Treg-Tex archetypes with healthy samples serving as references. (B) Identification of key ligand-receptor pairs that differentially regulate the OC populations. This analysis compares the relative signaling strengths between the Mφ-OC and Treg-Tex archetypes, focusing on osteoclasts as the signal receivers (from A). (C) Schematic illustration of in vitro experimental validation for estimated signaling molecules. CD14 + monocytes isolated from human peripheral blood were enriched for osteoclastogenesis induction, with selected factors added to the culture medium to test their predicted roles in regulating differential osteoclastogenesis. Osteoclastogenesis was then evaluated by both qPCR and TRAP staining. (D) qPCR analysis of osteoclast signature genes to validate differential osteoclastogenesis regulation by estimated signaling molecules. Each signaling factor was tested using graded concentrations: TWEAK (TNFSF12; 0.1, 1, 10 ng/μL), COMP (5, 50, 500 ng/μL), and NRG1 (10, 100, 1000 ng/μL), TNFSF10 (1, 10, 100 ng/μL), SEMA4A (1, 10, 100 ng/μL), EFNA5 (1, 10, 100 ng/μL), BMP8A (1, 10, 100 ng/μL). Each condition has five replicates. Statistical significance was assessed using one-way ANOVA, with significance levels: ∗ p < 0.05; ∗∗ p < 0.01; ∗∗∗ p < 0.001; ∗∗∗∗ p < 0.0001.

    Article Snippet: recombinant human EFNA5 , Sino Biological , Cat#10192-H08H-100.

    Techniques: In Vitro, Biomarker Discovery, Isolation, Staining

    (a) Schematic representation of the selection process for ephrin signaling interactions. Co-immunoprecipitation mass spectrometry identified 5157 proteins, of which 1327 were differentially bound (DB; p < 0.05, FC > 1 vs. GFP). In parallel, CellChat analysis of scRNA-seq data tested 229 ligand–receptor networks, identifying 16 differentially regulated (DR; p < 0.05) interactions based on signaling strength. Ephrin signaling was selected as a key candidate pathway by intersecting both datasets, guiding further analysis of its role in aDCHS1 and hDCHS1 organoids. (b) Significant signaling pathways ranked based on differences in overall information flow within the inferred networks between aDCHS1 and hDCHS1. Pathways enriched in aDCHS1 are shown in teal, equally enriched pathways in black, and pathways enriched in hDCHS1 in yellow. (c) Fold-change differences in protein abundance from immunoprecipitation (IP) analysis between aDCHS1 and hDCHS1. (d) Representative fluorescence images of DAPI (blue), DCHS1 (green), and EPHA4 (magenta) in control 60-day-old neural organoids. V = ventricle; scale bars: 25 µm (individual channels) and 10 µm (merged image). (e) Representative fluorescence images of 60-day-old hDCHS1 and aDCHS1 neural organoids subjected to proximity ligation assay (PLA) to detect DCHS1-EPHA4 interactions. Nuclei were stained with DAPI. Images were acquired at 63× magnification. V = ventricle; scale bar: 10 µm. (f) Differential expression analysis of cell-cell communication events potentially deregulated between aDCHS1 and hDCHS1 related to the EPHA4 receptor. Dot color indicates enrichment in hDCHS1 (yellow) or aDCHS1 (teal). (g) Representative immunohistochemistry (IHC) images and quantification of PAX6+ and MEIS2+ cells in 30-day-old neural organoids derived from human iPSCs, treated with EFNA5, EFNB2, or left untreated. Statistical significance was assessed using a binomial test by comparing each treated condition to the untreated condition individually. For PAX6 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 23, EFNA5 = 62, EFNB2 = 45. For MEIS2 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 30, EFNA5 = 35, EFNB2 = 49. (h) Dot plot showing the expression of EPHA4, EFNA5, EFNB2, EFNB3 and EFNB1 genes in the Excitatory, Inhibitory and Striatal lineage. Dot color represents the average expression level, and dot size indicates the proportion of cells expressing each gene.

    Journal: bioRxiv

    Article Title: DCHS1 Modulates Forebrain Proportions in Modern Humans via a Glycosylation Change

    doi: 10.1101/2025.05.14.654031

    Figure Lengend Snippet: (a) Schematic representation of the selection process for ephrin signaling interactions. Co-immunoprecipitation mass spectrometry identified 5157 proteins, of which 1327 were differentially bound (DB; p < 0.05, FC > 1 vs. GFP). In parallel, CellChat analysis of scRNA-seq data tested 229 ligand–receptor networks, identifying 16 differentially regulated (DR; p < 0.05) interactions based on signaling strength. Ephrin signaling was selected as a key candidate pathway by intersecting both datasets, guiding further analysis of its role in aDCHS1 and hDCHS1 organoids. (b) Significant signaling pathways ranked based on differences in overall information flow within the inferred networks between aDCHS1 and hDCHS1. Pathways enriched in aDCHS1 are shown in teal, equally enriched pathways in black, and pathways enriched in hDCHS1 in yellow. (c) Fold-change differences in protein abundance from immunoprecipitation (IP) analysis between aDCHS1 and hDCHS1. (d) Representative fluorescence images of DAPI (blue), DCHS1 (green), and EPHA4 (magenta) in control 60-day-old neural organoids. V = ventricle; scale bars: 25 µm (individual channels) and 10 µm (merged image). (e) Representative fluorescence images of 60-day-old hDCHS1 and aDCHS1 neural organoids subjected to proximity ligation assay (PLA) to detect DCHS1-EPHA4 interactions. Nuclei were stained with DAPI. Images were acquired at 63× magnification. V = ventricle; scale bar: 10 µm. (f) Differential expression analysis of cell-cell communication events potentially deregulated between aDCHS1 and hDCHS1 related to the EPHA4 receptor. Dot color indicates enrichment in hDCHS1 (yellow) or aDCHS1 (teal). (g) Representative immunohistochemistry (IHC) images and quantification of PAX6+ and MEIS2+ cells in 30-day-old neural organoids derived from human iPSCs, treated with EFNA5, EFNB2, or left untreated. Statistical significance was assessed using a binomial test by comparing each treated condition to the untreated condition individually. For PAX6 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 23, EFNA5 = 62, EFNB2 = 45. For MEIS2 (Batch=1), n = 4 organoids per condition; total number of ventricles: Untreated = 30, EFNA5 = 35, EFNB2 = 49. (h) Dot plot showing the expression of EPHA4, EFNA5, EFNB2, EFNB3 and EFNB1 genes in the Excitatory, Inhibitory and Striatal lineage. Dot color represents the average expression level, and dot size indicates the proportion of cells expressing each gene.

    Article Snippet: Human brain organoids were treated with either recombinant EFNA5 (MCE, Cat. No.: HY-P70379) or EFNB2 (MCE, Cat. No.: HY-P77645) protein to study their effects on organoid development.

    Techniques: Selection, Immunoprecipitation, Mass Spectrometry, Protein-Protein interactions, Quantitative Proteomics, Fluorescence, Control, Proximity Ligation Assay, Staining, Immunohistochemistry, Derivative Assay, Expressing

    RNase1‐induced T‐cell dysregulation may require the internalization of RNase1 into T cells. A) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in EphA4‐knockdown (sh‐EphA4#1), ALK‐knockdown (sh‐ALK#1), or control (sh‐Ctrl) activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). B) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with different concentrations of recombinant EphrinA5 as indicated for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). C) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), Cpd1 (10 µ m ), or RNase1 combined to Cpd1 for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). D) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), crizotinib (0.5 µ m ), or RNase1 combined to crizotinib for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). E) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. Right: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. β‐actin served as a loading control. Representative data from three independent experiments. F) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. Right: Quantitative results of Western blot of RNase1 in the left panel of (F). Quantitative data were analyzed from three independent experiments. G) Left: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. β‐actin served as a loading control. Right: Quantitative results of Western blot of RNase1 in the left panel of (G). Quantitative data were analyzed from three independent experiments. H) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), dynasore (10 µ m for 1 h treatment), or RNase1 combined with dynasore (20 µ m for 1 h treatment) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). I) Western blot analysis of the whole cell lysate (WCL), cytoplasmic, and nuclear fractions in activated Jurkat T cells (JA) and 1 µg mL −1 RNase1‐treated activated Jurkat T cells (JAR). Representative data from three independent experiments. J) Immunocytochemistry staining of RNase1 in activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Nuclei were counterstained with DAPI. Representative images of n = 2 independent replicates. Scale bar: 10 µm. Data represent mean ± S.D. ** p , 0.001–0.01, and *** p < 0.001 by two‐sided unpaired Student's t ‐test.

    Journal: Advanced Science

    Article Title: Ribonuclease 1 Induces T‐Cell Dysfunction and Impairs CD8 + T‐Cell Cytotoxicity to Benefit Tumor Growth through Hijacking STAT1

    doi: 10.1002/advs.202404961

    Figure Lengend Snippet: RNase1‐induced T‐cell dysregulation may require the internalization of RNase1 into T cells. A) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in EphA4‐knockdown (sh‐EphA4#1), ALK‐knockdown (sh‐ALK#1), or control (sh‐Ctrl) activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). B) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with different concentrations of recombinant EphrinA5 as indicated for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). C) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), Cpd1 (10 µ m ), or RNase1 combined to Cpd1 for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). D) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), crizotinib (0.5 µ m ), or RNase1 combined to crizotinib for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). E) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. Right: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for different time‐points as indicated. β‐actin served as a loading control. Representative data from three independent experiments. F) Left: Western blot analysis of RNase1 in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. Right: Quantitative results of Western blot of RNase1 in the left panel of (F). Quantitative data were analyzed from three independent experiments. G) Left: Western blot analysis of RNase1 in unactivated PBMC‐derived T cells and activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) or RNase1 combined with dynasore (10 µ m for 1 h treatment) for 48 h. β‐actin served as a loading control. Right: Quantitative results of Western blot of RNase1 in the left panel of (G). Quantitative data were analyzed from three independent experiments. H) Quantitative RT‐PCR analysis of IL‐2 mRNA expression in unactivated Jurkat T cells and activated Jurkat T cells treated without or with RNase1 (1 µg mL −1 ), dynasore (10 µ m for 1 h treatment), or RNase1 combined with dynasore (20 µ m for 1 h treatment) for 48 h. Representative data from three independent experiments (each experiment contains three technical replicates). I) Western blot analysis of the whole cell lysate (WCL), cytoplasmic, and nuclear fractions in activated Jurkat T cells (JA) and 1 µg mL −1 RNase1‐treated activated Jurkat T cells (JAR). Representative data from three independent experiments. J) Immunocytochemistry staining of RNase1 in activated PBMC‐derived T cells treated without or with RNase1 (1 µg mL −1 ) for 48 h. Nuclei were counterstained with DAPI. Representative images of n = 2 independent replicates. Scale bar: 10 µm. Data represent mean ± S.D. ** p , 0.001–0.01, and *** p < 0.001 by two‐sided unpaired Student's t ‐test.

    Article Snippet: Recombinant EphrinA5 (#374‐EA‐200, R&D Systems) was added to medium at the indicated concentrations for 48 h. The used concentrations of inhibitors were 10 μ m Cpd1 (#sc‐314230; Santa Cruz Biotechnology), 0.5 μ m crizotinib (#TM‐T1661‐1; TargetMol), and 10 μ m dynasore (#SI‐D7693; Sigma‐Aldrich).

    Techniques: Quantitative RT-PCR, Expressing, Knockdown, Control, Recombinant, Western Blot, Derivative Assay, Immunocytochemistry, Staining