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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 <t>NRG1</t> (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.
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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 <t>NRG1</t> (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.
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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 <t>NRG1</t> (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.
Nrg1, supplied by MedChemExpress, used in various techniques. Bioz Stars score: 94/100, 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 <t>NRG1</t> (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.
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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 <t>NRG1</t> (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.
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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 <t>NRG1</t> (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.
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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 <t>NRG1</t> (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.
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Image Search Results


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 NRG1 , Sino Biological , Cat#10658-H08H.

Techniques: In Vitro, Biomarker Discovery, Isolation, Staining

Journal: iScience

Article Title: Development of apical out trophoblast stem cell derived organoids to model early human pregnancy

doi: 10.1016/j.isci.2025.112099

Figure Lengend Snippet:

Article Snippet: Human Neuregulin-1 (hNRG-1) , Cell Signaling , Cat# 26941S.

Techniques: Recombinant, Membrane, Cell Recovery, Knock-Out, Immunofluorescence, Plasmid Preparation, Electron Microscopy, Enzyme-linked Immunosorbent Assay, cDNA Synthesis, SYBR Green Assay, DNA Purification, Software

Journal: iScience

Article Title: Development of apical out trophoblast stem cell derived organoids to model early human pregnancy

doi: 10.1016/j.isci.2025.112099

Figure Lengend Snippet:

Article Snippet: Human Neuregulin-1 (hNRG-1) , Cell Signaling , Cat# 26941S.

Techniques: Recombinant, Membrane, Cell Recovery, Knock-Out, Immunofluorescence, Plasmid Preparation, Electron Microscopy, Enzyme-linked Immunosorbent Assay, cDNA Synthesis, SYBR Green Assay, DNA Purification, Software