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quantikine elisa mouse immunoassay scd14  (R&D Systems)


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    Structured Review

    R&D Systems quantikine elisa mouse immunoassay scd14
    Plasma markers of systemic inflammation and kidney injury in CDI mice across diets (A) PCoA of Canberra distances of mean-normalized sepsis/immune marker concentrations. Points are colored by diet, and shapes indicate whether mice were humanely euthanized due to clinical sickness or survived until the experimental endpoint. Vectors show the correlation of each measured factor with PC1 and PC2, with the vector length indicating the relative strength of the correlation. Only statistically significant vectors are shown (multiple regression with Benjamini-Hochberg multiple test correction, p.adj. < 0.05). (B) Plasma concentration of each marker that significantly differed between diets (blood urea nitrogen (BUN), and immune factors <t>sCD14,</t> CXCL1, IL-10, IL-1B, IL-6, and TNF-a) at sacrifice. Pairwise comparisons of concentrations between diets were calculated using Kruskal-Wallis and Dunn’s post hoc tests, with p -value corrections conducted via Benjamini and Hochberg. Boxplot lines (from top to bottom) depict the 75 th , 50 th (median), and 25 th percentiles, with lines extending from the top/bottom of the boxplot indicating the largest/smallest observation within ±1.5∗IQR (inter-quartile range). P-value significance (∗∗∗∗: p < 0.0001, ∗∗∗: p < 0.001, ∗∗: p < 0.01, and ∗: p < 0.05).
    Quantikine Elisa Mouse Immunoassay Scd14, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 24 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/quantikine+immunoassay/pmc13018909-15-0-7?v=R%26D+Systems
    Average 94 stars, based on 24 article reviews
    quantikine elisa mouse immunoassay scd14 - by Bioz Stars, 2026-07
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    Images

    1) Product Images from "Dietary fiber reduces mortality from secondary sepsis in a murine model of Clostridioides difficile infection"

    Article Title: Dietary fiber reduces mortality from secondary sepsis in a murine model of Clostridioides difficile infection

    Journal: iScience

    doi: 10.1016/j.isci.2026.115258

    Plasma markers of systemic inflammation and kidney injury in CDI mice across diets (A) PCoA of Canberra distances of mean-normalized sepsis/immune marker concentrations. Points are colored by diet, and shapes indicate whether mice were humanely euthanized due to clinical sickness or survived until the experimental endpoint. Vectors show the correlation of each measured factor with PC1 and PC2, with the vector length indicating the relative strength of the correlation. Only statistically significant vectors are shown (multiple regression with Benjamini-Hochberg multiple test correction, p.adj. < 0.05). (B) Plasma concentration of each marker that significantly differed between diets (blood urea nitrogen (BUN), and immune factors sCD14, CXCL1, IL-10, IL-1B, IL-6, and TNF-a) at sacrifice. Pairwise comparisons of concentrations between diets were calculated using Kruskal-Wallis and Dunn’s post hoc tests, with p -value corrections conducted via Benjamini and Hochberg. Boxplot lines (from top to bottom) depict the 75 th , 50 th (median), and 25 th percentiles, with lines extending from the top/bottom of the boxplot indicating the largest/smallest observation within ±1.5∗IQR (inter-quartile range). P-value significance (∗∗∗∗: p < 0.0001, ∗∗∗: p < 0.001, ∗∗: p < 0.01, and ∗: p < 0.05).
    Figure Legend Snippet: Plasma markers of systemic inflammation and kidney injury in CDI mice across diets (A) PCoA of Canberra distances of mean-normalized sepsis/immune marker concentrations. Points are colored by diet, and shapes indicate whether mice were humanely euthanized due to clinical sickness or survived until the experimental endpoint. Vectors show the correlation of each measured factor with PC1 and PC2, with the vector length indicating the relative strength of the correlation. Only statistically significant vectors are shown (multiple regression with Benjamini-Hochberg multiple test correction, p.adj. < 0.05). (B) Plasma concentration of each marker that significantly differed between diets (blood urea nitrogen (BUN), and immune factors sCD14, CXCL1, IL-10, IL-1B, IL-6, and TNF-a) at sacrifice. Pairwise comparisons of concentrations between diets were calculated using Kruskal-Wallis and Dunn’s post hoc tests, with p -value corrections conducted via Benjamini and Hochberg. Boxplot lines (from top to bottom) depict the 75 th , 50 th (median), and 25 th percentiles, with lines extending from the top/bottom of the boxplot indicating the largest/smallest observation within ±1.5∗IQR (inter-quartile range). P-value significance (∗∗∗∗: p < 0.0001, ∗∗∗: p < 0.001, ∗∗: p < 0.01, and ∗: p < 0.05).

    Techniques Used: Clinical Proteomics, Marker, Plasmid Preparation, Concentration Assay



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    a, Young mice were pretreated with ABx for 2 weeks, and then colonized with Clos for 4 weeks ( n □=□6). b, qPCR shows transcriptional alterations of CDK inhibitors Cdkn2a , Cdkn2d , and Cdkn1a in tPVAT from Clos -mice ( n = 6) and vehicle-mice ( n = 6). c, Representative confocal immunofluorescence images of p16 INK4A in tPVAT from these mice ( n = 5). d, Relative protein expression analysis of SASP components in tPVAT from Clos -mice ( n = 5) and vehicle-mice ( n = 5). e, Young mice were administered to PAA (50 mg/kg, i.p. ) daily for 4 weeks ( n □=□6). f, Representative immunoblots and quantification of intensities for CDK inhibitors p16 INK4A , p19 INK4D , and p21 WAF1/Cip1 and DNA damage marker γ-H2A.X in tPVAT from these mice ( n = 6). g, Representative confocal images of p16 INK4A in tPVAT from these mice ( n = 6). h, Immunoblotting represents the expression of the SASP components IL-1β, <t>IL-6,</t> and CCL2 in tPVAT from PAA-or vehicle-treated mice ( n = 6). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments ( c,g ). Scale bars, 20 and 200 μm ( c,g ). Error bars represent SD ( b,d,f,h ). P values were calculated using a two-tailed unpaired Student’s t -test ( b,d,f,h ). Images created with https://BioRender.com ( a,e ). (* P <0.05, ** P <0.01, *** P <0.001, **** P <0.0001).
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    Image Search Results


    Plasma markers of systemic inflammation and kidney injury in CDI mice across diets (A) PCoA of Canberra distances of mean-normalized sepsis/immune marker concentrations. Points are colored by diet, and shapes indicate whether mice were humanely euthanized due to clinical sickness or survived until the experimental endpoint. Vectors show the correlation of each measured factor with PC1 and PC2, with the vector length indicating the relative strength of the correlation. Only statistically significant vectors are shown (multiple regression with Benjamini-Hochberg multiple test correction, p.adj. < 0.05). (B) Plasma concentration of each marker that significantly differed between diets (blood urea nitrogen (BUN), and immune factors sCD14, CXCL1, IL-10, IL-1B, IL-6, and TNF-a) at sacrifice. Pairwise comparisons of concentrations between diets were calculated using Kruskal-Wallis and Dunn’s post hoc tests, with p -value corrections conducted via Benjamini and Hochberg. Boxplot lines (from top to bottom) depict the 75 th , 50 th (median), and 25 th percentiles, with lines extending from the top/bottom of the boxplot indicating the largest/smallest observation within ±1.5∗IQR (inter-quartile range). P-value significance (∗∗∗∗: p < 0.0001, ∗∗∗: p < 0.001, ∗∗: p < 0.01, and ∗: p < 0.05).

    Journal: iScience

    Article Title: Dietary fiber reduces mortality from secondary sepsis in a murine model of Clostridioides difficile infection

    doi: 10.1016/j.isci.2026.115258

    Figure Lengend Snippet: Plasma markers of systemic inflammation and kidney injury in CDI mice across diets (A) PCoA of Canberra distances of mean-normalized sepsis/immune marker concentrations. Points are colored by diet, and shapes indicate whether mice were humanely euthanized due to clinical sickness or survived until the experimental endpoint. Vectors show the correlation of each measured factor with PC1 and PC2, with the vector length indicating the relative strength of the correlation. Only statistically significant vectors are shown (multiple regression with Benjamini-Hochberg multiple test correction, p.adj. < 0.05). (B) Plasma concentration of each marker that significantly differed between diets (blood urea nitrogen (BUN), and immune factors sCD14, CXCL1, IL-10, IL-1B, IL-6, and TNF-a) at sacrifice. Pairwise comparisons of concentrations between diets were calculated using Kruskal-Wallis and Dunn’s post hoc tests, with p -value corrections conducted via Benjamini and Hochberg. Boxplot lines (from top to bottom) depict the 75 th , 50 th (median), and 25 th percentiles, with lines extending from the top/bottom of the boxplot indicating the largest/smallest observation within ±1.5∗IQR (inter-quartile range). P-value significance (∗∗∗∗: p < 0.0001, ∗∗∗: p < 0.001, ∗∗: p < 0.01, and ∗: p < 0.05).

    Article Snippet: Quantikine ELISA Mouse Immunoassay – sCD14 , RnD Systems , MC140.

    Techniques: Clinical Proteomics, Marker, Plasmid Preparation, Concentration Assay

    Salivary PTX3, calprotectin, and IL-8 are elevated in early-onset neonatal pneumonia (EONP) and show strong case—control discrimination. (A – C) Distributions of salivary PTX3, calprotectin, and IL-8 in EONP vs. healthy controls (medians with IQRs; Mann–Whitney tests, all P < 0.001). (D – F) ROC curves for each single biomarker with optimal cutoffs (PTX3 ≥ 1.38 ng/mL; calprotectin ≥5.49 ng/mL; IL-8 ≥ 8.69 pg/mL). The solid line denotes the ROC curve and the dashed lines indicate the 95% confidence interval (lower and upper limits). (G) ROC curves for the three-marker combined model (logistic regression using PTX3, calprotectin, and IL-8). The combined model achieved an apparent AUC of 0.978, and internally validated performance is overlaid (LOOCV and 5-fold cross-validation), demonstrating minimal performance degradation.

    Journal: Frontiers in Pediatrics

    Article Title: Noninvasive salivary biomarkers (PTX3, calprotectin, and IL-8) for early-onset neonatal pneumonia: case-control differences and exploratory discrimination

    doi: 10.3389/fped.2026.1747967

    Figure Lengend Snippet: Salivary PTX3, calprotectin, and IL-8 are elevated in early-onset neonatal pneumonia (EONP) and show strong case—control discrimination. (A – C) Distributions of salivary PTX3, calprotectin, and IL-8 in EONP vs. healthy controls (medians with IQRs; Mann–Whitney tests, all P < 0.001). (D – F) ROC curves for each single biomarker with optimal cutoffs (PTX3 ≥ 1.38 ng/mL; calprotectin ≥5.49 ng/mL; IL-8 ≥ 8.69 pg/mL). The solid line denotes the ROC curve and the dashed lines indicate the 95% confidence interval (lower and upper limits). (G) ROC curves for the three-marker combined model (logistic regression using PTX3, calprotectin, and IL-8). The combined model achieved an apparent AUC of 0.978, and internally validated performance is overlaid (LOOCV and 5-fold cross-validation), demonstrating minimal performance degradation.

    Article Snippet: Salivary PTX3, calprotectin, and IL-8 concentrations were measured using commercial ELISA kits according to the manufacturers' instructions: PTX3 with the QuantikineTM Human Pentraxin 3 Immunoassay (R&D Systems, Cat. DPTX30B); calprotectin with the Quantikine® Human Calprotectin Heterodimer Immunoassay (R&D Systems, Cat. DS8900); and IL-8 with the LEGEND MAXTM High Sensitivity Human IL-8 ELISA Kit (BioLegend, Cat. 431517).

    Techniques: Control, MANN-WHITNEY, Biomarker Discovery, Marker

    Salivary biomarkers are inter-correlated and track systemic inflammation in EONP. (A) Pairwise correlations among salivary PTX3, calprotectin, and IL-8 in EONP (Spearman r , all P < 0.001). (B) Corresponding correlations in healthy controls (all P > 0.05). (C) Heatmap of Spearman correlations between salivary biomarkers and systemic indices (hs-CRP, serum PCT, serum IL-6, WBC, ANC, I/T ratio, platelets) in EONP, showing moderate-to-strong positive associations with inflammatory markers and inverse associations with platelets (panel labels show exact r ).

    Journal: Frontiers in Pediatrics

    Article Title: Noninvasive salivary biomarkers (PTX3, calprotectin, and IL-8) for early-onset neonatal pneumonia: case-control differences and exploratory discrimination

    doi: 10.3389/fped.2026.1747967

    Figure Lengend Snippet: Salivary biomarkers are inter-correlated and track systemic inflammation in EONP. (A) Pairwise correlations among salivary PTX3, calprotectin, and IL-8 in EONP (Spearman r , all P < 0.001). (B) Corresponding correlations in healthy controls (all P > 0.05). (C) Heatmap of Spearman correlations between salivary biomarkers and systemic indices (hs-CRP, serum PCT, serum IL-6, WBC, ANC, I/T ratio, platelets) in EONP, showing moderate-to-strong positive associations with inflammatory markers and inverse associations with platelets (panel labels show exact r ).

    Article Snippet: Salivary PTX3, calprotectin, and IL-8 concentrations were measured using commercial ELISA kits according to the manufacturers' instructions: PTX3 with the QuantikineTM Human Pentraxin 3 Immunoassay (R&D Systems, Cat. DPTX30B); calprotectin with the Quantikine® Human Calprotectin Heterodimer Immunoassay (R&D Systems, Cat. DS8900); and IL-8 with the LEGEND MAXTM High Sensitivity Human IL-8 ELISA Kit (BioLegend, Cat. 431517).

    Techniques:

    Salivary biomarkers modestly enrich for blood-culture-positive bacteremia within EONP. (A – C) Salivary PTX3, calprotectin, and IL-8 in culture-positive vs. culture-negative EONP cases (medians with IQRs; Mann–Whitney P < 0.001, =0.003, =0.002, respectively). (D – F) ROC curves for bacteremia detection using single salivary markers with optimal cutoffs (PTX3 ≥ 2.51 ng/mL; calprotectin ≥14.57 ng/mL; IL-8 ≥ 18.97 pg/mL), yielding AUCs 0.725, 0.682, and 0.689, respectively. The solid line denotes the ROC curve and the dashed lines indicate the 95% confidence interval (lower and upper limits). (G) ROC curves for the three-marker combined model (logistic regression using PTX3, calprotectin, and IL-8). The combined model achieved an apparent AUC of 0.702, with internally validated AUCs of 0.706 (5-fold cross-validation) and 0.702 (LOOCV), indicating stable but moderate enrichment performance.

    Journal: Frontiers in Pediatrics

    Article Title: Noninvasive salivary biomarkers (PTX3, calprotectin, and IL-8) for early-onset neonatal pneumonia: case-control differences and exploratory discrimination

    doi: 10.3389/fped.2026.1747967

    Figure Lengend Snippet: Salivary biomarkers modestly enrich for blood-culture-positive bacteremia within EONP. (A – C) Salivary PTX3, calprotectin, and IL-8 in culture-positive vs. culture-negative EONP cases (medians with IQRs; Mann–Whitney P < 0.001, =0.003, =0.002, respectively). (D – F) ROC curves for bacteremia detection using single salivary markers with optimal cutoffs (PTX3 ≥ 2.51 ng/mL; calprotectin ≥14.57 ng/mL; IL-8 ≥ 18.97 pg/mL), yielding AUCs 0.725, 0.682, and 0.689, respectively. The solid line denotes the ROC curve and the dashed lines indicate the 95% confidence interval (lower and upper limits). (G) ROC curves for the three-marker combined model (logistic regression using PTX3, calprotectin, and IL-8). The combined model achieved an apparent AUC of 0.702, with internally validated AUCs of 0.706 (5-fold cross-validation) and 0.702 (LOOCV), indicating stable but moderate enrichment performance.

    Article Snippet: Salivary PTX3, calprotectin, and IL-8 concentrations were measured using commercial ELISA kits according to the manufacturers' instructions: PTX3 with the QuantikineTM Human Pentraxin 3 Immunoassay (R&D Systems, Cat. DPTX30B); calprotectin with the Quantikine® Human Calprotectin Heterodimer Immunoassay (R&D Systems, Cat. DS8900); and IL-8 with the LEGEND MAXTM High Sensitivity Human IL-8 ELISA Kit (BioLegend, Cat. 431517).

    Techniques: MANN-WHITNEY, Marker, Biomarker Discovery

    a, Young mice were pretreated with ABx for 2 weeks, and then colonized with Clos for 4 weeks ( n □=□6). b, qPCR shows transcriptional alterations of CDK inhibitors Cdkn2a , Cdkn2d , and Cdkn1a in tPVAT from Clos -mice ( n = 6) and vehicle-mice ( n = 6). c, Representative confocal immunofluorescence images of p16 INK4A in tPVAT from these mice ( n = 5). d, Relative protein expression analysis of SASP components in tPVAT from Clos -mice ( n = 5) and vehicle-mice ( n = 5). e, Young mice were administered to PAA (50 mg/kg, i.p. ) daily for 4 weeks ( n □=□6). f, Representative immunoblots and quantification of intensities for CDK inhibitors p16 INK4A , p19 INK4D , and p21 WAF1/Cip1 and DNA damage marker γ-H2A.X in tPVAT from these mice ( n = 6). g, Representative confocal images of p16 INK4A in tPVAT from these mice ( n = 6). h, Immunoblotting represents the expression of the SASP components IL-1β, IL-6, and CCL2 in tPVAT from PAA-or vehicle-treated mice ( n = 6). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments ( c,g ). Scale bars, 20 and 200 μm ( c,g ). Error bars represent SD ( b,d,f,h ). P values were calculated using a two-tailed unpaired Student’s t -test ( b,d,f,h ). Images created with https://BioRender.com ( a,e ). (* P <0.05, ** P <0.01, *** P <0.001, **** P <0.0001).

    Journal: bioRxiv

    Article Title: Gut Microbiota Production of Phenylacetate Programs Vascular Niche Senescence and Drives Atherosclerosis

    doi: 10.64898/2026.02.27.708541

    Figure Lengend Snippet: a, Young mice were pretreated with ABx for 2 weeks, and then colonized with Clos for 4 weeks ( n □=□6). b, qPCR shows transcriptional alterations of CDK inhibitors Cdkn2a , Cdkn2d , and Cdkn1a in tPVAT from Clos -mice ( n = 6) and vehicle-mice ( n = 6). c, Representative confocal immunofluorescence images of p16 INK4A in tPVAT from these mice ( n = 5). d, Relative protein expression analysis of SASP components in tPVAT from Clos -mice ( n = 5) and vehicle-mice ( n = 5). e, Young mice were administered to PAA (50 mg/kg, i.p. ) daily for 4 weeks ( n □=□6). f, Representative immunoblots and quantification of intensities for CDK inhibitors p16 INK4A , p19 INK4D , and p21 WAF1/Cip1 and DNA damage marker γ-H2A.X in tPVAT from these mice ( n = 6). g, Representative confocal images of p16 INK4A in tPVAT from these mice ( n = 6). h, Immunoblotting represents the expression of the SASP components IL-1β, IL-6, and CCL2 in tPVAT from PAA-or vehicle-treated mice ( n = 6). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments ( c,g ). Scale bars, 20 and 200 μm ( c,g ). Error bars represent SD ( b,d,f,h ). P values were calculated using a two-tailed unpaired Student’s t -test ( b,d,f,h ). Images created with https://BioRender.com ( a,e ). (* P <0.05, ** P <0.01, *** P <0.001, **** P <0.0001).

    Article Snippet: Cell culture supernatants were assessed for IL-6 using a QuantikineTM ELISA Human IL-6 Immunoassay kit (R&D Systems, D6050), according to the manufacturer’s instructions.

    Techniques: Immunofluorescence, Expressing, Western Blot, Marker, Two Tailed Test

    a, IL-6 concentration in culture medium derived from replicative senescent or proliferating ECs treated with PAA (10 μM) or vehicle for 72 h ( n □=□10 biologically independent samples). b, Representative immunoblots demonstrate the expression of NOTCH1 and downstream targets N1ICD and HES1 in hADSC-adipocytes exposed to CM derived from vehicle- or PAA-treated ECs ( n = 6). c,d, Immunoblotting for NOTCH1 ( c ) and the insulin signaling pathway ( d ) in insulin-stimulated adipocytes treated with PAA-CM in the presence or absence of anti-IL6R neutralizing antibody, Tocilizumab (100 μg/mL) ( n = 6). e,f, Immunoblotting for the insulin signaling pathway ( e ) and thermogenic markers UCP1 and PGC1α ( f ) in adipocytes treated with PAA-CM in the presence or absence of Notch inhibitor, DAPT (10 µM) ( n = 6). g, qPCR represents transcriptional changes of thermogenic markers Ucp1 and Ppargc1a in PAA-CM-exposed adipocytes transfected with siHES1 or siNeg ( n = 6). h, Summary scheme outlining the mechanisms of microbial metabolite PAA for triggering adipocyte dysfunction. PAA indirectly activates NOTCH1 and its downstream HES1 in adipocytes by releasing senescence-messaging secretome containing IL6 from adjacent ECs. This both downregulates thermogenic function and the insulin signaling pathway in adipocytes. Error bars represent SD ( a-g ). P values were calculated using one-way ANOVA followed by Tukey’s post hoc test ( a ) and a two-tailed unpaired Student’s t -test ( b-g ). Image created with https://BioRender.com ( h ).

    Journal: bioRxiv

    Article Title: Gut Microbiota Production of Phenylacetate Programs Vascular Niche Senescence and Drives Atherosclerosis

    doi: 10.64898/2026.02.27.708541

    Figure Lengend Snippet: a, IL-6 concentration in culture medium derived from replicative senescent or proliferating ECs treated with PAA (10 μM) or vehicle for 72 h ( n □=□10 biologically independent samples). b, Representative immunoblots demonstrate the expression of NOTCH1 and downstream targets N1ICD and HES1 in hADSC-adipocytes exposed to CM derived from vehicle- or PAA-treated ECs ( n = 6). c,d, Immunoblotting for NOTCH1 ( c ) and the insulin signaling pathway ( d ) in insulin-stimulated adipocytes treated with PAA-CM in the presence or absence of anti-IL6R neutralizing antibody, Tocilizumab (100 μg/mL) ( n = 6). e,f, Immunoblotting for the insulin signaling pathway ( e ) and thermogenic markers UCP1 and PGC1α ( f ) in adipocytes treated with PAA-CM in the presence or absence of Notch inhibitor, DAPT (10 µM) ( n = 6). g, qPCR represents transcriptional changes of thermogenic markers Ucp1 and Ppargc1a in PAA-CM-exposed adipocytes transfected with siHES1 or siNeg ( n = 6). h, Summary scheme outlining the mechanisms of microbial metabolite PAA for triggering adipocyte dysfunction. PAA indirectly activates NOTCH1 and its downstream HES1 in adipocytes by releasing senescence-messaging secretome containing IL6 from adjacent ECs. This both downregulates thermogenic function and the insulin signaling pathway in adipocytes. Error bars represent SD ( a-g ). P values were calculated using one-way ANOVA followed by Tukey’s post hoc test ( a ) and a two-tailed unpaired Student’s t -test ( b-g ). Image created with https://BioRender.com ( h ).

    Article Snippet: Cell culture supernatants were assessed for IL-6 using a QuantikineTM ELISA Human IL-6 Immunoassay kit (R&D Systems, D6050), according to the manufacturer’s instructions.

    Techniques: Concentration Assay, Derivative Assay, Western Blot, Expressing, Transfection, Two Tailed Test

    a, Clos -colonized young mice received a senolytic cocktail containing Dasatinib + Quercetin (5 + 50 mg/kg/d) for 3 days, followed by a 7-day resting period ( n □=□6). b, Representative immunoblots for CDK inhibitors p16 INK4A , p19 INK4D , and p21 WAF1/Cip1 and DNA damage marker γ-H2A.X in tPVAT from Clos -colonized mice treated with D+Q or vehicle ( n = 6). c,d, Representative confocal immunofluorescence images of IL-6 ( c ) and bright-field SA-β-gal staining images ( d ) in tPVAT from these mice ( n = 6). e, Representative confocal images of NOTCH1 in tPVAT from these mice ( n = 6). f,g, Immunoblotting for the insulin signaling pathway ( f ) and thermogenic markers UCP1 and PGC1α ( g ) in tPVAT from Clos -colonized mice treated with D+Q or vehicle ( n = 6). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments. Scale bar, 50, 100, and 200 μm ( c,d,e ). Error bars represent SD ( b,d,f,g ). P values were calculated using a two-tailed unpaired Student’s t -test ( b,d,f,g ). Images created with https://BioRender.com ( a ).

    Journal: bioRxiv

    Article Title: Gut Microbiota Production of Phenylacetate Programs Vascular Niche Senescence and Drives Atherosclerosis

    doi: 10.64898/2026.02.27.708541

    Figure Lengend Snippet: a, Clos -colonized young mice received a senolytic cocktail containing Dasatinib + Quercetin (5 + 50 mg/kg/d) for 3 days, followed by a 7-day resting period ( n □=□6). b, Representative immunoblots for CDK inhibitors p16 INK4A , p19 INK4D , and p21 WAF1/Cip1 and DNA damage marker γ-H2A.X in tPVAT from Clos -colonized mice treated with D+Q or vehicle ( n = 6). c,d, Representative confocal immunofluorescence images of IL-6 ( c ) and bright-field SA-β-gal staining images ( d ) in tPVAT from these mice ( n = 6). e, Representative confocal images of NOTCH1 in tPVAT from these mice ( n = 6). f,g, Immunoblotting for the insulin signaling pathway ( f ) and thermogenic markers UCP1 and PGC1α ( g ) in tPVAT from Clos -colonized mice treated with D+Q or vehicle ( n = 6). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments. Scale bar, 50, 100, and 200 μm ( c,d,e ). Error bars represent SD ( b,d,f,g ). P values were calculated using a two-tailed unpaired Student’s t -test ( b,d,f,g ). Images created with https://BioRender.com ( a ).

    Article Snippet: Cell culture supernatants were assessed for IL-6 using a QuantikineTM ELISA Human IL-6 Immunoassay kit (R&D Systems, D6050), according to the manufacturer’s instructions.

    Techniques: Western Blot, Marker, Immunofluorescence, Staining, Two Tailed Test

    a,b, Plasma samples from aged ASCVD patients (>80 years old) enrolled in the ASCVD cohort ( n = 110; male and female) and healthy controls ( n = 77; male and female) were subjected to targeted metabolomics for PAA quantification. c, Adjusted regression models for the association of PAA with atherosclerosis in the ASCVD cohort ( n □=□187). Effect estimates were controlled for age, sex, smoking, alcohol, family history of CVD, LDL-C, triglycerides, HDL-C, Hb1Ac, CRP, troponin T, and NT-proBNP. Error bars show 95% confidence intervals. OR, odds ratio. d, Ldlr −/− and WT mice were fed chow (for 8 weeks) or Western diet (for 12 weeks). WC: WT + chow diet; WW: WT + Western diet; LC: Ldlr −/− + chow diet; LW: Ldlr −/− + Western diet. e, Plasma PAA levels in these mice quantified by LC-MS/MS targeted metabolomics ( n □=□5). f, Representative images (left) and quantification (right) of H&E staining of aortic root lesions ( n □=□5). Arrowheads indicate plaque areas. g, Correlation of plasma PAA levels with aortic root lesion area and luminal occlusion (%). h, Representative immunoblots and quantification of intensities for the CDK inhibitor p16 INK4A , the SASP component IL-6, DNA damage marker γ-H2A.X, and the endothelial function marker phosphorylated eNOS S1177 in aortas from Ldlr −/− and WT mice fed a chow or Western diet for 12 weeks ( n = 5). i, Expression of CDKN1A , IL1B , and IL6 genes (upper) and co-expression of the senescence-associated genes in atherosclerotic aortic wall (AOR) of patients with CAD ( n □=□600) and healthy individuals ( n □=□250) in the STARNET database. j,k,l, Representative immunoblots and quantification of intensities for senescence hallmarks ( j ), insulin signaling pathway ( k ), and thermogenic markers ( l ) in tPVAT from Ldlr −/− and WT mice fed a chow or Western diet for 12 weeks ( n = 5). m, Plasma and aortic PVAT samples were collected from the validation study, including aged CAD patients undergoing CABG surgery ( n □=□5) and non-CAD controls ( n □=□5), for LC-MS/MS PAA quantification and senescence studies. n, Plasma PAA concentrations in aged CAD patients ( n □=□5) and non-CAD controls ( n □=□5). o,p,q, Representative immunoblots and quantification of intensities for senescence hallmarks ( o ), NOTCH1 and thermogenic markers ( p ), and insulin signaling pathway ( q ) in aortic PVAT from the individuals in the validation study ( n = 5). r, PAA was administered (PAA) or not (Ctrl) to chow-fed Ldlr −/− mice for 8 weeks. s, Quantification of H&E-stained aortic root lesion area (left) and aortic occlusion (right). Total cholesterol concentrations in plasma ( n = 5). t, Representative immunoblots and quantification of intensities for senescence hallmarks p16 INK4A , IL-6, and γ-H2A.X in aortas (left) and tPVAT (right). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments. Scale bar, 200 μm ( f ). Error bars represent SD ( h,j-l,o-t ). P values were calculated using two-tailed Mann–Whitney U -test ( b ), one-way ANOVA followed by Tukey’s post hoc test ( e,f,h,j-l ), Welch’s t-test ( i ), and a two-tailed unpaired Student’s t -test ( n-t ). Correlation coefficient and P values were calculated by Spearman’s rank-order correlation test ( g ). Data are shown as median with min–max; each violin represents interquartile range (IQR); center lines indicate the median; upper and lower lines are bounded by 25th and 75th percentiles ( b , n ). Images created with https://BioRender.com ( a,d,m,r ).

    Journal: bioRxiv

    Article Title: Gut Microbiota Production of Phenylacetate Programs Vascular Niche Senescence and Drives Atherosclerosis

    doi: 10.64898/2026.02.27.708541

    Figure Lengend Snippet: a,b, Plasma samples from aged ASCVD patients (>80 years old) enrolled in the ASCVD cohort ( n = 110; male and female) and healthy controls ( n = 77; male and female) were subjected to targeted metabolomics for PAA quantification. c, Adjusted regression models for the association of PAA with atherosclerosis in the ASCVD cohort ( n □=□187). Effect estimates were controlled for age, sex, smoking, alcohol, family history of CVD, LDL-C, triglycerides, HDL-C, Hb1Ac, CRP, troponin T, and NT-proBNP. Error bars show 95% confidence intervals. OR, odds ratio. d, Ldlr −/− and WT mice were fed chow (for 8 weeks) or Western diet (for 12 weeks). WC: WT + chow diet; WW: WT + Western diet; LC: Ldlr −/− + chow diet; LW: Ldlr −/− + Western diet. e, Plasma PAA levels in these mice quantified by LC-MS/MS targeted metabolomics ( n □=□5). f, Representative images (left) and quantification (right) of H&E staining of aortic root lesions ( n □=□5). Arrowheads indicate plaque areas. g, Correlation of plasma PAA levels with aortic root lesion area and luminal occlusion (%). h, Representative immunoblots and quantification of intensities for the CDK inhibitor p16 INK4A , the SASP component IL-6, DNA damage marker γ-H2A.X, and the endothelial function marker phosphorylated eNOS S1177 in aortas from Ldlr −/− and WT mice fed a chow or Western diet for 12 weeks ( n = 5). i, Expression of CDKN1A , IL1B , and IL6 genes (upper) and co-expression of the senescence-associated genes in atherosclerotic aortic wall (AOR) of patients with CAD ( n □=□600) and healthy individuals ( n □=□250) in the STARNET database. j,k,l, Representative immunoblots and quantification of intensities for senescence hallmarks ( j ), insulin signaling pathway ( k ), and thermogenic markers ( l ) in tPVAT from Ldlr −/− and WT mice fed a chow or Western diet for 12 weeks ( n = 5). m, Plasma and aortic PVAT samples were collected from the validation study, including aged CAD patients undergoing CABG surgery ( n □=□5) and non-CAD controls ( n □=□5), for LC-MS/MS PAA quantification and senescence studies. n, Plasma PAA concentrations in aged CAD patients ( n □=□5) and non-CAD controls ( n □=□5). o,p,q, Representative immunoblots and quantification of intensities for senescence hallmarks ( o ), NOTCH1 and thermogenic markers ( p ), and insulin signaling pathway ( q ) in aortic PVAT from the individuals in the validation study ( n = 5). r, PAA was administered (PAA) or not (Ctrl) to chow-fed Ldlr −/− mice for 8 weeks. s, Quantification of H&E-stained aortic root lesion area (left) and aortic occlusion (right). Total cholesterol concentrations in plasma ( n = 5). t, Representative immunoblots and quantification of intensities for senescence hallmarks p16 INK4A , IL-6, and γ-H2A.X in aortas (left) and tPVAT (right). Data were determined in 8-10 micrographs and represent triplicated biologically independent experiments. Scale bar, 200 μm ( f ). Error bars represent SD ( h,j-l,o-t ). P values were calculated using two-tailed Mann–Whitney U -test ( b ), one-way ANOVA followed by Tukey’s post hoc test ( e,f,h,j-l ), Welch’s t-test ( i ), and a two-tailed unpaired Student’s t -test ( n-t ). Correlation coefficient and P values were calculated by Spearman’s rank-order correlation test ( g ). Data are shown as median with min–max; each violin represents interquartile range (IQR); center lines indicate the median; upper and lower lines are bounded by 25th and 75th percentiles ( b , n ). Images created with https://BioRender.com ( a,d,m,r ).

    Article Snippet: Cell culture supernatants were assessed for IL-6 using a QuantikineTM ELISA Human IL-6 Immunoassay kit (R&D Systems, D6050), according to the manufacturer’s instructions.

    Techniques: Clinical Proteomics, Western Blot, Liquid Chromatography with Mass Spectroscopy, Staining, Marker, Expressing, Biomarker Discovery, Two Tailed Test, MANN-WHITNEY