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MedChemExpress anti mouse rat il 17a antibody
Bioinformatics analysis prioritized PTGS2 and MMP9 as candidate inflammatory genes associated with <t>the</t> <t>IL-17</t> signaling pathway in ischemic stroke. (A) Venn diagram showing the overlap between differentially expressed genes (DEGs) identified from GEO datasets and genes retrieved from the CellAge database. Five overlapping genes were identified: PTGS2, MMP9, SERPINB2, CTNNAL1, and HTRA1. CS, genes from CellAge database; DEG, significantly differentially expressed genes in ischemic stroke. (B) Gene Ontology (GO) enrichment analysis of the overlapping genes, including biological process, cellular component, and molecular function categories. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showing that the overlapping genes were enriched in inflammation-related pathways, including the IL-17 signaling pathway and TNF signaling pathway. (D) GSEA comparing ischemic stroke (IS) and control samples, demonstrating enrichment of immune- and inflammation-related pathways in IS. (E) Predicted transcription factor–target gene regulatory network for PTGS2 and MMP9, showing candidate shared upstream transcription factors. Yellow nodes represent TFs, red nodes represent target genes.
Anti Mouse Rat Il 17a Antibody, 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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Multi Sciences (Lianke) Biotech Co Ltd anti rat il 17
Bioinformatics analysis prioritized PTGS2 and MMP9 as candidate inflammatory genes associated with <t>the</t> <t>IL-17</t> signaling pathway in ischemic stroke. (A) Venn diagram showing the overlap between differentially expressed genes (DEGs) identified from GEO datasets and genes retrieved from the CellAge database. Five overlapping genes were identified: PTGS2, MMP9, SERPINB2, CTNNAL1, and HTRA1. CS, genes from CellAge database; DEG, significantly differentially expressed genes in ischemic stroke. (B) Gene Ontology (GO) enrichment analysis of the overlapping genes, including biological process, cellular component, and molecular function categories. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showing that the overlapping genes were enriched in inflammation-related pathways, including the IL-17 signaling pathway and TNF signaling pathway. (D) GSEA comparing ischemic stroke (IS) and control samples, demonstrating enrichment of immune- and inflammation-related pathways in IS. (E) Predicted transcription factor–target gene regulatory network for PTGS2 and MMP9, showing candidate shared upstream transcription factors. Yellow nodes represent TFs, red nodes represent target genes.
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Bioinformatics analysis prioritized PTGS2 and MMP9 as candidate inflammatory genes associated with <t>the</t> <t>IL-17</t> signaling pathway in ischemic stroke. (A) Venn diagram showing the overlap between differentially expressed genes (DEGs) identified from GEO datasets and genes retrieved from the CellAge database. Five overlapping genes were identified: PTGS2, MMP9, SERPINB2, CTNNAL1, and HTRA1. CS, genes from CellAge database; DEG, significantly differentially expressed genes in ischemic stroke. (B) Gene Ontology (GO) enrichment analysis of the overlapping genes, including biological process, cellular component, and molecular function categories. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showing that the overlapping genes were enriched in inflammation-related pathways, including the IL-17 signaling pathway and TNF signaling pathway. (D) GSEA comparing ischemic stroke (IS) and control samples, demonstrating enrichment of immune- and inflammation-related pathways in IS. (E) Predicted transcription factor–target gene regulatory network for PTGS2 and MMP9, showing candidate shared upstream transcription factors. Yellow nodes represent TFs, red nodes represent target genes.
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Thermo Fisher fluorescein isothiocyanate fitc conjugated rat anti mouse il 17a
Bioinformatics analysis prioritized PTGS2 and MMP9 as candidate inflammatory genes associated with <t>the</t> <t>IL-17</t> signaling pathway in ischemic stroke. (A) Venn diagram showing the overlap between differentially expressed genes (DEGs) identified from GEO datasets and genes retrieved from the CellAge database. Five overlapping genes were identified: PTGS2, MMP9, SERPINB2, CTNNAL1, and HTRA1. CS, genes from CellAge database; DEG, significantly differentially expressed genes in ischemic stroke. (B) Gene Ontology (GO) enrichment analysis of the overlapping genes, including biological process, cellular component, and molecular function categories. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showing that the overlapping genes were enriched in inflammation-related pathways, including the IL-17 signaling pathway and TNF signaling pathway. (D) GSEA comparing ischemic stroke (IS) and control samples, demonstrating enrichment of immune- and inflammation-related pathways in IS. (E) Predicted transcription factor–target gene regulatory network for PTGS2 and MMP9, showing candidate shared upstream transcription factors. Yellow nodes represent TFs, red nodes represent target genes.
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OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess <t>IL-17A</t> expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.
Anti Il 17a Antibody, supplied by Multi Sciences (Lianke) Biotech Co Ltd, 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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OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess <t>IL-17A</t> expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.
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OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess <t>IL-17A</t> expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.
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OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess <t>IL-17A</t> expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.
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OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess <t>IL-17A</t> expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.
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Image Search Results


Bioinformatics analysis prioritized PTGS2 and MMP9 as candidate inflammatory genes associated with the IL-17 signaling pathway in ischemic stroke. (A) Venn diagram showing the overlap between differentially expressed genes (DEGs) identified from GEO datasets and genes retrieved from the CellAge database. Five overlapping genes were identified: PTGS2, MMP9, SERPINB2, CTNNAL1, and HTRA1. CS, genes from CellAge database; DEG, significantly differentially expressed genes in ischemic stroke. (B) Gene Ontology (GO) enrichment analysis of the overlapping genes, including biological process, cellular component, and molecular function categories. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showing that the overlapping genes were enriched in inflammation-related pathways, including the IL-17 signaling pathway and TNF signaling pathway. (D) GSEA comparing ischemic stroke (IS) and control samples, demonstrating enrichment of immune- and inflammation-related pathways in IS. (E) Predicted transcription factor–target gene regulatory network for PTGS2 and MMP9, showing candidate shared upstream transcription factors. Yellow nodes represent TFs, red nodes represent target genes.

Journal: Frontiers in Immunology

Article Title: IL-17A-associated PTGS2 and MMP9 inflammatory signaling in ischemic stroke: clinical correlation and experimental evidence

doi: 10.3389/fimmu.2026.1812571

Figure Lengend Snippet: Bioinformatics analysis prioritized PTGS2 and MMP9 as candidate inflammatory genes associated with the IL-17 signaling pathway in ischemic stroke. (A) Venn diagram showing the overlap between differentially expressed genes (DEGs) identified from GEO datasets and genes retrieved from the CellAge database. Five overlapping genes were identified: PTGS2, MMP9, SERPINB2, CTNNAL1, and HTRA1. CS, genes from CellAge database; DEG, significantly differentially expressed genes in ischemic stroke. (B) Gene Ontology (GO) enrichment analysis of the overlapping genes, including biological process, cellular component, and molecular function categories. (C) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showing that the overlapping genes were enriched in inflammation-related pathways, including the IL-17 signaling pathway and TNF signaling pathway. (D) GSEA comparing ischemic stroke (IS) and control samples, demonstrating enrichment of immune- and inflammation-related pathways in IS. (E) Predicted transcription factor–target gene regulatory network for PTGS2 and MMP9, showing candidate shared upstream transcription factors. Yellow nodes represent TFs, red nodes represent target genes.

Article Snippet: Rats in the IL-17A neutralizing antibody-treated group were treated with Anti-Mouse/Rat IL-17A Antibody (17F3; MedChemExpress, Cat. No. HY-P990222), a mouse IgG1κ monoclonal neutralizing antibody against mouse/rat IL-17A, via intravenous injection at 100 μg/rat immediately after reperfusion and again at 12 h post-reperfusion.

Techniques: Control

Serum IL-17A, PTGS2, and MMP9 levels in the clinical cohort and their correlations with each other and with stroke severity. (A–C) Serum IL-17A, PTGS2, and MMP9 levels were significantly higher in patients with ischemic stroke than in healthy controls. IS, ischemic stroke (n = 104); Normal, control group (n = 58). (D) Correlations among serum IL-17A, PTGS2, and MMP9 levels in the stroke group. (E) Positive correlations between serum IL-17A, PTGS2, and MMP9 levels and admission NIHSS scores in patients with ischemic stroke. Correlations were analyzed using Spearman’s rank correlation test. *P < 0.05, **P < 0.01, ***P < 0.001.

Journal: Frontiers in Immunology

Article Title: IL-17A-associated PTGS2 and MMP9 inflammatory signaling in ischemic stroke: clinical correlation and experimental evidence

doi: 10.3389/fimmu.2026.1812571

Figure Lengend Snippet: Serum IL-17A, PTGS2, and MMP9 levels in the clinical cohort and their correlations with each other and with stroke severity. (A–C) Serum IL-17A, PTGS2, and MMP9 levels were significantly higher in patients with ischemic stroke than in healthy controls. IS, ischemic stroke (n = 104); Normal, control group (n = 58). (D) Correlations among serum IL-17A, PTGS2, and MMP9 levels in the stroke group. (E) Positive correlations between serum IL-17A, PTGS2, and MMP9 levels and admission NIHSS scores in patients with ischemic stroke. Correlations were analyzed using Spearman’s rank correlation test. *P < 0.05, **P < 0.01, ***P < 0.001.

Article Snippet: Rats in the IL-17A neutralizing antibody-treated group were treated with Anti-Mouse/Rat IL-17A Antibody (17F3; MedChemExpress, Cat. No. HY-P990222), a mouse IgG1κ monoclonal neutralizing antibody against mouse/rat IL-17A, via intravenous injection at 100 μg/rat immediately after reperfusion and again at 12 h post-reperfusion.

Techniques: Control

MCAO-induced activation of IL-17A/PTGS2/MMP9-related inflammatory markers and changes after anti-IL-17A antibody treatment in rat brain tissue. (A–C) Relative mRNA levels of PTGS2, MMP9, and IL-17A in the sham, MCAO, and anti-IL-17A Ab groups. (D–F) Protein concentrations of PTGS2, MMP9, and IL-17A. (G, H) Concentrations of PGE2 and IL-6. (I) Neurological deficit scores assessed using the Longa scoring system. In panel I, the sham group median was 0; therefore, a minimal bar height was displayed for visualization only. (J) Representative TTC-stained brain sections from the MCAO and anti-IL-17A Ab groups. White areas indicate infarct regions, whereas red areas indicate viable brain tissue. (K) Quantitative analysis of infarct volume percentage based on TTC staining. Sham, sham-operated group; Model, MCAO group; anti-IL-17A Ab, IL-17A neutralizing antibody-treated MCAO group. Data in panels A-H are presented as mean ± SEM (n = 6 per group). Neurological deficit scores in panel I are presented as median (interquartile range) (n = 6 per group). TTC analysis in panels (J, K) was performed in an independent cohort of rats, with final sample sizes of n = 4 for the MCAO group and n = 5 for the anti-IL-17A Ab group; one rat in the MCAO group died before tissue collection. *P < 0.05, **P < 0.01, ***P < 0.001.

Journal: Frontiers in Immunology

Article Title: IL-17A-associated PTGS2 and MMP9 inflammatory signaling in ischemic stroke: clinical correlation and experimental evidence

doi: 10.3389/fimmu.2026.1812571

Figure Lengend Snippet: MCAO-induced activation of IL-17A/PTGS2/MMP9-related inflammatory markers and changes after anti-IL-17A antibody treatment in rat brain tissue. (A–C) Relative mRNA levels of PTGS2, MMP9, and IL-17A in the sham, MCAO, and anti-IL-17A Ab groups. (D–F) Protein concentrations of PTGS2, MMP9, and IL-17A. (G, H) Concentrations of PGE2 and IL-6. (I) Neurological deficit scores assessed using the Longa scoring system. In panel I, the sham group median was 0; therefore, a minimal bar height was displayed for visualization only. (J) Representative TTC-stained brain sections from the MCAO and anti-IL-17A Ab groups. White areas indicate infarct regions, whereas red areas indicate viable brain tissue. (K) Quantitative analysis of infarct volume percentage based on TTC staining. Sham, sham-operated group; Model, MCAO group; anti-IL-17A Ab, IL-17A neutralizing antibody-treated MCAO group. Data in panels A-H are presented as mean ± SEM (n = 6 per group). Neurological deficit scores in panel I are presented as median (interquartile range) (n = 6 per group). TTC analysis in panels (J, K) was performed in an independent cohort of rats, with final sample sizes of n = 4 for the MCAO group and n = 5 for the anti-IL-17A Ab group; one rat in the MCAO group died before tissue collection. *P < 0.05, **P < 0.01, ***P < 0.001.

Article Snippet: Rats in the IL-17A neutralizing antibody-treated group were treated with Anti-Mouse/Rat IL-17A Antibody (17F3; MedChemExpress, Cat. No. HY-P990222), a mouse IgG1κ monoclonal neutralizing antibody against mouse/rat IL-17A, via intravenous injection at 100 μg/rat immediately after reperfusion and again at 12 h post-reperfusion.

Techniques: Activation Assay, Staining

Spearman correlation analyses among IL-17A, PTGS2, MMP9, PGE2, and IL-6 in rat brain tissue. Correlation analyses were performed using pooled data from all animals (n = 18). (A) Correlation between IL-17A and PTGS2 mRNA expression. (B) Correlation between IL-17A and MMP9 mRNA expression. (C) Correlation between IL-17A and PTGS2 protein expression. (D) Correlation between IL-17A and MMP9 protein expression. (E) Correlation between IL-17A and PGE2 levels. (F) Correlation between IL-17A and IL-6 levels. Sham, sham-operated group; Model, MCAO group; anti-IL-17A Ab, IL-17A neutralizing antibody-treated MCAO group. Given the limited sample size, these correlations should be interpreted with caution.

Journal: Frontiers in Immunology

Article Title: IL-17A-associated PTGS2 and MMP9 inflammatory signaling in ischemic stroke: clinical correlation and experimental evidence

doi: 10.3389/fimmu.2026.1812571

Figure Lengend Snippet: Spearman correlation analyses among IL-17A, PTGS2, MMP9, PGE2, and IL-6 in rat brain tissue. Correlation analyses were performed using pooled data from all animals (n = 18). (A) Correlation between IL-17A and PTGS2 mRNA expression. (B) Correlation between IL-17A and MMP9 mRNA expression. (C) Correlation between IL-17A and PTGS2 protein expression. (D) Correlation between IL-17A and MMP9 protein expression. (E) Correlation between IL-17A and PGE2 levels. (F) Correlation between IL-17A and IL-6 levels. Sham, sham-operated group; Model, MCAO group; anti-IL-17A Ab, IL-17A neutralizing antibody-treated MCAO group. Given the limited sample size, these correlations should be interpreted with caution.

Article Snippet: Rats in the IL-17A neutralizing antibody-treated group were treated with Anti-Mouse/Rat IL-17A Antibody (17F3; MedChemExpress, Cat. No. HY-P990222), a mouse IgG1κ monoclonal neutralizing antibody against mouse/rat IL-17A, via intravenous injection at 100 μg/rat immediately after reperfusion and again at 12 h post-reperfusion.

Techniques: Expressing

OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess IL-17A expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.

Journal: Scientific Reports

Article Title: Osthol ameliorates obesity-associated lipid metabolic disorders by inhibiting ADRA1D-dependent Th17 cell differentiation

doi: 10.1038/s41598-025-20719-x

Figure Lengend Snippet: OST Attenuates Systemic Inflammation and Downregulates Th17-Related Factor Expression. ( A ) KEGG pathway enrichment analysis of downstream targets of OST. This figure is based on data from KEGG (Kyoto Encyclopedia of Genes and Genomes) at https://www.kegg.jp/ ; © Kanehisa Laboratories. ( B ) Flow cytometry was used to evaluate the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( C ) Immunohistochemical staining of liver tissues was performed to assess IL-17A expression. ( D ) Immunofluorescence staining was conducted to detect CD4⁺RORγt⁺ double-positive cells in liver sections. ( E ) Serum levels of IL-6, IL-1β, TNF-α, and IL-17A were measured using ELISA. n = 6. **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.

Article Snippet: Cells were then fixed and permeabilized, followed by intracellular staining with a phycoerythrin (PE)-conjugated anti-IL-17A antibody (F21IL1702, Lianke Biotech, Hangzhou, China).

Techniques: Expressing, Flow Cytometry, Immunohistochemical staining, Staining, Immunofluorescence, Enzyme-linked Immunosorbent Assay

OST Inhibits Th17 Cell Differentiation in Vitro. ( A ) Flow cytometry was used to assess the proportion of CD4⁺IL-17A⁺ cells in a Th17-polarized cell model treated with different doses of OST. ( B ) RT-qPCR was performed to evaluate mRNA expression levels of RORγt and IL-17A. ( C ) Western blot was performed to evaluate protein expression levels of RORγt, IL-17A, IL-17RA, TRAF6, and Act1. ( D ) ELISA was used to quantify the secretion of IL-6, IL-1β, TNF-α, IL-10, and TGF-β in the culture supernatants. n = 3. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.

Journal: Scientific Reports

Article Title: Osthol ameliorates obesity-associated lipid metabolic disorders by inhibiting ADRA1D-dependent Th17 cell differentiation

doi: 10.1038/s41598-025-20719-x

Figure Lengend Snippet: OST Inhibits Th17 Cell Differentiation in Vitro. ( A ) Flow cytometry was used to assess the proportion of CD4⁺IL-17A⁺ cells in a Th17-polarized cell model treated with different doses of OST. ( B ) RT-qPCR was performed to evaluate mRNA expression levels of RORγt and IL-17A. ( C ) Western blot was performed to evaluate protein expression levels of RORγt, IL-17A, IL-17RA, TRAF6, and Act1. ( D ) ELISA was used to quantify the secretion of IL-6, IL-1β, TNF-α, IL-10, and TGF-β in the culture supernatants. n = 3. * P < 0.05, ** P < 0.01, *** P < 0.001, **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.

Article Snippet: Cells were then fixed and permeabilized, followed by intracellular staining with a phycoerythrin (PE)-conjugated anti-IL-17A antibody (F21IL1702, Lianke Biotech, Hangzhou, China).

Techniques: Cell Differentiation, In Vitro, Flow Cytometry, Quantitative RT-PCR, Expressing, Western Blot, Enzyme-linked Immunosorbent Assay

OST Suppresses Th17 Differentiation via an ADRA1D-Dependent Mechanism. ( A ) Volcano plot of differentially expressed genes (DEGs) in the GSE110729 obesity dataset. ( B ) Venn diagram showing the intersection between OST’s potential targets and DEGs from the GSE110729 dataset. ( C ) RT-qPCR was performed to assess the expression of ADRA1D, IL-17A, and RORγt in Th17-polarized CD4⁺ T cells with or without ADRA1D overexpression. ( D ) Western blot was conducted to evaluate the protein expression of ADRA1D, IL-17A, RORγt, IL-17RA, TRAF6, and Act1. ( E ) ELISA was used to measure the levels of IL-6, IL-1β, TNF-α, IL-10, and TGF-β in the culture supernatants. n = 3. *** P < 0.001, **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.

Journal: Scientific Reports

Article Title: Osthol ameliorates obesity-associated lipid metabolic disorders by inhibiting ADRA1D-dependent Th17 cell differentiation

doi: 10.1038/s41598-025-20719-x

Figure Lengend Snippet: OST Suppresses Th17 Differentiation via an ADRA1D-Dependent Mechanism. ( A ) Volcano plot of differentially expressed genes (DEGs) in the GSE110729 obesity dataset. ( B ) Venn diagram showing the intersection between OST’s potential targets and DEGs from the GSE110729 dataset. ( C ) RT-qPCR was performed to assess the expression of ADRA1D, IL-17A, and RORγt in Th17-polarized CD4⁺ T cells with or without ADRA1D overexpression. ( D ) Western blot was conducted to evaluate the protein expression of ADRA1D, IL-17A, RORγt, IL-17RA, TRAF6, and Act1. ( E ) ELISA was used to measure the levels of IL-6, IL-1β, TNF-α, IL-10, and TGF-β in the culture supernatants. n = 3. *** P < 0.001, **** P < 0.0001. One-way ANOVA followed by Tukey’s post hoc test was used for multiple group comparisons.

Article Snippet: Cells were then fixed and permeabilized, followed by intracellular staining with a phycoerythrin (PE)-conjugated anti-IL-17A antibody (F21IL1702, Lianke Biotech, Hangzhou, China).

Techniques: Quantitative RT-PCR, Expressing, Over Expression, Western Blot, Enzyme-linked Immunosorbent Assay

ADRA1D Overexpression Attenuates the Metabolic and Immunomodulatory Effects of OST in Vivo. ( A ) Body weight changes were monitored in HFD-fed mice treated with OST. (B) Weights of adipose tissue and liver were measured to assess the effect on organ hypertrophy. ( C ) Serum levels of TG, TC, FFA, ALT, and AST were evaluated by biochemical assays. ( D ) Flow cytometry was performed to assess the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( E ) Immunofluorescence staining of liver tissue was used to detect CD4⁺RORγt⁺ double-positive cell infiltration. ( F ) Immunohistochemistry was performed to evaluate hepatic IL-17A protein expression. ( G ) Western blotting was conducted to assess ADRA1D protein expression in liver tissue. ( H ) Western blot was used to detect the phosphorylation levels of ERK1/2 and PI3K in liver tissue. ( I ) H&E staining of adipose tissue was used to assess adipocyte morphology. (J) Oil red O staining of liver sections was performed to evaluate hepatic lipid deposition. n = 6. ** P < 0.01, **** P < 0.0001. For three or more groups, one-way or two-way analysis of variance (ANOVA) was applied, followed by Tukey’s post hoc test. P < 0.05 was considered statistically significant.

Journal: Scientific Reports

Article Title: Osthol ameliorates obesity-associated lipid metabolic disorders by inhibiting ADRA1D-dependent Th17 cell differentiation

doi: 10.1038/s41598-025-20719-x

Figure Lengend Snippet: ADRA1D Overexpression Attenuates the Metabolic and Immunomodulatory Effects of OST in Vivo. ( A ) Body weight changes were monitored in HFD-fed mice treated with OST. (B) Weights of adipose tissue and liver were measured to assess the effect on organ hypertrophy. ( C ) Serum levels of TG, TC, FFA, ALT, and AST were evaluated by biochemical assays. ( D ) Flow cytometry was performed to assess the proportion of CD4⁺IL-17A⁺ cells in the spleen. ( E ) Immunofluorescence staining of liver tissue was used to detect CD4⁺RORγt⁺ double-positive cell infiltration. ( F ) Immunohistochemistry was performed to evaluate hepatic IL-17A protein expression. ( G ) Western blotting was conducted to assess ADRA1D protein expression in liver tissue. ( H ) Western blot was used to detect the phosphorylation levels of ERK1/2 and PI3K in liver tissue. ( I ) H&E staining of adipose tissue was used to assess adipocyte morphology. (J) Oil red O staining of liver sections was performed to evaluate hepatic lipid deposition. n = 6. ** P < 0.01, **** P < 0.0001. For three or more groups, one-way or two-way analysis of variance (ANOVA) was applied, followed by Tukey’s post hoc test. P < 0.05 was considered statistically significant.

Article Snippet: Cells were then fixed and permeabilized, followed by intracellular staining with a phycoerythrin (PE)-conjugated anti-IL-17A antibody (F21IL1702, Lianke Biotech, Hangzhou, China).

Techniques: Over Expression, In Vivo, Flow Cytometry, Immunofluorescence, Staining, Immunohistochemistry, Expressing, Western Blot, Phospho-proteomics