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quantikine mouse scd14 elisa kit  (R&D Systems)


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    R&D Systems quantikine mouse scd14 elisa kit
    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 Mouse Scd14 Elisa Kit, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 27 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/quantikine+mouse+scd14+elisa+kit/Mouse+CD14+Quantikine+ELISA+Kit/pmc13018909-469-8-16
    Average 94 stars, based on 27 article reviews
    quantikine mouse scd14 elisa kit - by Bioz Stars, 2026-09
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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

    Related Articles

    Enzyme-linked Immunosorbent Assay:

    Article Title: Dietary fiber reduces mortality from secondary sepsis in a murine model of Clostridioides difficile infection
    Article Snippet: .. Soluble CD14 (sCD14) levels were quantified using the Quantikine Mouse sCD14 ELISA Kit (Catalog No. MC140, R&D Systems, Minneapolis, MN, USA) following the manufacturer’s instructions. .. Blood urea nitrogen (BUN) concentrations were measured using the QuantiChrom Urea Assay Kit (Catalog No. DIUR-100, BioAssay Systems, Hayward, CA, USA) according to the manufacturer’s protocol.



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    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).
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    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).
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    Figure 3. Probiotics treatment reduces inflammation in peritoneal macrophages and intestine of older obese mice. (A–C) LPS-induced inflammatory response in terms of mRNA expression of IL-6 (A), TNF-α (B), and IL-1β (C) was reduced in primary macrophages isolated from peritoneal cavity of older HFD-fed mice treated with probiotics (n = 8) compared with their controls (n = 6). (D–H) In addition, the expression of proinflammatory markers such as IL-6 (D), TNF-α (E), and IL-1β (F) were decreased, while antiinflammatory genes like IL-10 (G) and TGF-β (H) mRNA expressions were increased in the colon of probiotic-fed older obese mice (n = 8) compared with their controls (n = 6). (I and J) In addition, systemic leaky gut markers such as LPS binding protein (LBP) (I) and <t>soluble</t> <t>CD14</t> (J) were reduced in the serum of probiotic-fed older obese mice (n = 7) compared with their controls (n = 6). Values are mean of n = 6–8 in each group, and data are shown as mean ± SEM. *P < 0.05; **P < 0.01, ***P < 0.001 by Student t-test (A–J).
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    Figure 3. Probiotics treatment reduces inflammation in peritoneal macrophages and intestine of older obese mice. (A–C) LPS-induced inflammatory response in terms of mRNA expression of IL-6 (A), TNF-α (B), and IL-1β (C) was reduced in primary macrophages isolated from peritoneal cavity of older HFD-fed mice treated with probiotics (n = 8) compared with their controls (n = 6). (D–H) In addition, the expression of proinflammatory markers such as IL-6 (D), TNF-α (E), and IL-1β (F) were decreased, while antiinflammatory genes like IL-10 (G) and TGF-β (H) mRNA expressions were increased in the colon of probiotic-fed older obese mice (n = 8) compared with their controls (n = 6). (I and J) In addition, systemic leaky gut markers such as LPS binding protein (LBP) (I) and <t>soluble</t> <t>CD14</t> (J) were reduced in the serum of probiotic-fed older obese mice (n = 7) compared with their controls (n = 6). Values are mean of n = 6–8 in each group, and data are shown as mean ± SEM. *P < 0.05; **P < 0.01, ***P < 0.001 by Student t-test (A–J).
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    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: Soluble CD14 (sCD14) levels were quantified using the Quantikine Mouse sCD14 ELISA Kit (Catalog No. MC140, R&D Systems, Minneapolis, MN, USA) following the manufacturer’s instructions.

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

    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

    Figure 3. Probiotics treatment reduces inflammation in peritoneal macrophages and intestine of older obese mice. (A–C) LPS-induced inflammatory response in terms of mRNA expression of IL-6 (A), TNF-α (B), and IL-1β (C) was reduced in primary macrophages isolated from peritoneal cavity of older HFD-fed mice treated with probiotics (n = 8) compared with their controls (n = 6). (D–H) In addition, the expression of proinflammatory markers such as IL-6 (D), TNF-α (E), and IL-1β (F) were decreased, while antiinflammatory genes like IL-10 (G) and TGF-β (H) mRNA expressions were increased in the colon of probiotic-fed older obese mice (n = 8) compared with their controls (n = 6). (I and J) In addition, systemic leaky gut markers such as LPS binding protein (LBP) (I) and soluble CD14 (J) were reduced in the serum of probiotic-fed older obese mice (n = 7) compared with their controls (n = 6). Values are mean of n = 6–8 in each group, and data are shown as mean ± SEM. *P < 0.05; **P < 0.01, ***P < 0.001 by Student t-test (A–J).

    Journal: JCI insight

    Article Title: A human-origin probiotic cocktail ameliorates aging-related leaky gut and inflammation via modulating the microbiota/taurine/tight junction axis.

    doi: 10.1172/jci.insight.132055

    Figure Lengend Snippet: Figure 3. Probiotics treatment reduces inflammation in peritoneal macrophages and intestine of older obese mice. (A–C) LPS-induced inflammatory response in terms of mRNA expression of IL-6 (A), TNF-α (B), and IL-1β (C) was reduced in primary macrophages isolated from peritoneal cavity of older HFD-fed mice treated with probiotics (n = 8) compared with their controls (n = 6). (D–H) In addition, the expression of proinflammatory markers such as IL-6 (D), TNF-α (E), and IL-1β (F) were decreased, while antiinflammatory genes like IL-10 (G) and TGF-β (H) mRNA expressions were increased in the colon of probiotic-fed older obese mice (n = 8) compared with their controls (n = 6). (I and J) In addition, systemic leaky gut markers such as LPS binding protein (LBP) (I) and soluble CD14 (J) were reduced in the serum of probiotic-fed older obese mice (n = 7) compared with their controls (n = 6). Values are mean of n = 6–8 in each group, and data are shown as mean ± SEM. *P < 0.05; **P < 0.01, ***P < 0.001 by Student t-test (A–J).

    Article Snippet: To determine the impact of probiotics feeding on systemic leaky gut, markers such as LBP (catalog HK205-01, Hycult Biotech) and sCD14 (catalog MC140, R&D Systems) were measured in serum using ELISA kits and following manufacturer instructions.

    Techniques: Probiotics, Expressing, Isolation, Binding Assay