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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 24 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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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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    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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    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: 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

    (A) Schematic depicting the timeline of SIV infection and ART initiation in AL (n=11) and CR animals (n=6). (B) Plasma viral load (log10 SIV copies/mL) in AL and CR animals at longitudinal timepoints of 7-, 14-, 21-, and 28-days post-infection (dpi) along with area under the curve analysis of viremia across the first 28 days of SIV. VL AUC was calculated using the trapezoidal method. (C) Dot plots depicting SIV growth (0-14 dpi) and decay (14-28 dpi) rates per day calculated from plasma viral load. (D & E) Percentage of CCR5 + CD4 + and CD8 + total memory T cells in AL and CR animals across blood, pLN and colon at uninfected (D) and 14 dpi (E) time points. (F) Two-sided spearman correlation between %CCR5 + CD4 + memory T cells in the colon and plasma viral load (SIV copies/mL) at 14 dpi. (G) Quantification of plasma IFN-α (pg/mL) in AL and CR animals at 14 dpi through ELISA. (H) Mean fluorescence intensity (MFI) of CD169 expression in CD14+ CD16- classical monocytes in the blood of AL and CR animals at 14 dpi (right) with a representative histogram from one animal in each cohort (left). (I) Frequencies of Ki-67 + CD4 + and CD8 + total memory T cells in AL and CR animals across blood, pLN and colon at 14 dpi. (J) Frequencies of Ki-67 + CD16 + and CD16 - NK cells in the pLN of AL and CR animals at 14 dpi through flow cytometry. (K) Plots depicting two-sided Spearman correlation between plasma IFN-α and frequencies of Ki-67 + CD4 + memory T cells in the pLN of AL and CR animals at 14 dpi. Statistical analysis: (B-E, G-J) Mann-Whitney U test and (F & K) Spearman non-parametric correlation with confidence bands generated through linear regression. α=0.05.

    Journal: bioRxiv

    Article Title: Metabolic reprogramming by caloric restriction enhances acute phase virological control and reduces chronic inflammation in SIV-infected rhesus macaques

    doi: 10.64898/2026.03.11.711076

    Figure Lengend Snippet: (A) Schematic depicting the timeline of SIV infection and ART initiation in AL (n=11) and CR animals (n=6). (B) Plasma viral load (log10 SIV copies/mL) in AL and CR animals at longitudinal timepoints of 7-, 14-, 21-, and 28-days post-infection (dpi) along with area under the curve analysis of viremia across the first 28 days of SIV. VL AUC was calculated using the trapezoidal method. (C) Dot plots depicting SIV growth (0-14 dpi) and decay (14-28 dpi) rates per day calculated from plasma viral load. (D & E) Percentage of CCR5 + CD4 + and CD8 + total memory T cells in AL and CR animals across blood, pLN and colon at uninfected (D) and 14 dpi (E) time points. (F) Two-sided spearman correlation between %CCR5 + CD4 + memory T cells in the colon and plasma viral load (SIV copies/mL) at 14 dpi. (G) Quantification of plasma IFN-α (pg/mL) in AL and CR animals at 14 dpi through ELISA. (H) Mean fluorescence intensity (MFI) of CD169 expression in CD14+ CD16- classical monocytes in the blood of AL and CR animals at 14 dpi (right) with a representative histogram from one animal in each cohort (left). (I) Frequencies of Ki-67 + CD4 + and CD8 + total memory T cells in AL and CR animals across blood, pLN and colon at 14 dpi. (J) Frequencies of Ki-67 + CD16 + and CD16 - NK cells in the pLN of AL and CR animals at 14 dpi through flow cytometry. (K) Plots depicting two-sided Spearman correlation between plasma IFN-α and frequencies of Ki-67 + CD4 + memory T cells in the pLN of AL and CR animals at 14 dpi. Statistical analysis: (B-E, G-J) Mann-Whitney U test and (F & K) Spearman non-parametric correlation with confidence bands generated through linear regression. α=0.05.

    Article Snippet: Detection of sCD14 in monkey plasma was carried out using a CD14 Quantikine ELISA kit specific to rhesus macaques (R&D Systems, Minneapolis, MN) according to the manufacturer’s instructions.

    Techniques: Infection, Clinical Proteomics, Enzyme-linked Immunosorbent Assay, Fluorescence, Expressing, Flow Cytometry, MANN-WHITNEY, Generated

    (A & B) Combined weight (in kg.) (A) and body condition scores (B) of AL and CR animals comprising all measurements throughout the entire duration of ART. (C & D) Combined plasma glucose (C) and triglyceride (D) (mg/dL) of AL and CR animals comprising all measurements throughout the entire duration of ART. (E) Absolute counts (cells/µL) of total CD4 + and CD8 + T cells in blood from AL and CR animals after 11 months of ART. Counts were calculated using total lymphocyte counts from complete blood chemistries and multiplied by frequencies of viable CD3 + CD4 + or CD8 + lymphocytes assessed via flow cytometry (F & G) Absolute counts (cells/µL) of CD4 + (F) and CD8 + T cell (G) maturation subsets in the blood of AL and CR animals at 11M ART. (H) Principal component analysis (PCA) of 15 immune phenotypic markers in distinct immune cell lineages (CD4 + /CD8 + Tn, Tcm, Ttm, Tem, Treg (only CD4 + ), Tfh (only CD4 + ), NK cells (CD16 + & CD16 - ), and monocytes (classical, intermediate, & non-classical) in blood, lymph nodes, and colon at 11M ART, obtained via flow cytometry. Gating definitions were performed in accordance with Figure S2. (I) Representative H&E staining image of colon sections from one AL and CR animal (left). The graph on the right represents the quantification of immune cell infiltrates (immune cells/mm 2 ) (right) at 11M ART. (J) Flow cytometric proportions of major immune cell subsets in the colon at 11M ART between AL and CR animals. (K & L) Percentage of total CD4 + T cells expressing HLA-DR (K) and CD69 (L) in the colon at 11M ART obtained via flow cytometry. (M) Quantification of soluble CD14 (sCD14) in the plasma at 11M ART through ELISA. Values were interpolated using a standard curve and expressed in pg/mL. (N) Correlation between plasma sCD14 (ELISA) and colon immune cells/mm 2 (H&E) at 11M ART. (O) Volcano plot representing the mean log2 fold change of plasma cytokine and chemokine concentrations at 11M ART. red = over-expressed in CR, blue = under-expressed in CR, gray = nonsignificant. (P) Quantification of total SIV DNA in purified blood CD4 + T cells at ART initiation through 9 months of continuous ART. Data is represented as SIV DNA cell equivalents per million cells. (Q) Quantification of total SIV DNA in the LNs and colon at 11M ART. Data is represented as cell equivalents per million cells. Statistical Analyses: (A-G, I-M, P-Q) Mann-Whitney U-test, (H) PERMANOVA and (N) Spearman non-parametric correlation with confidence bands generated through linear regression. α=0.05.

    Journal: bioRxiv

    Article Title: Metabolic reprogramming by caloric restriction enhances acute phase virological control and reduces chronic inflammation in SIV-infected rhesus macaques

    doi: 10.64898/2026.03.11.711076

    Figure Lengend Snippet: (A & B) Combined weight (in kg.) (A) and body condition scores (B) of AL and CR animals comprising all measurements throughout the entire duration of ART. (C & D) Combined plasma glucose (C) and triglyceride (D) (mg/dL) of AL and CR animals comprising all measurements throughout the entire duration of ART. (E) Absolute counts (cells/µL) of total CD4 + and CD8 + T cells in blood from AL and CR animals after 11 months of ART. Counts were calculated using total lymphocyte counts from complete blood chemistries and multiplied by frequencies of viable CD3 + CD4 + or CD8 + lymphocytes assessed via flow cytometry (F & G) Absolute counts (cells/µL) of CD4 + (F) and CD8 + T cell (G) maturation subsets in the blood of AL and CR animals at 11M ART. (H) Principal component analysis (PCA) of 15 immune phenotypic markers in distinct immune cell lineages (CD4 + /CD8 + Tn, Tcm, Ttm, Tem, Treg (only CD4 + ), Tfh (only CD4 + ), NK cells (CD16 + & CD16 - ), and monocytes (classical, intermediate, & non-classical) in blood, lymph nodes, and colon at 11M ART, obtained via flow cytometry. Gating definitions were performed in accordance with Figure S2. (I) Representative H&E staining image of colon sections from one AL and CR animal (left). The graph on the right represents the quantification of immune cell infiltrates (immune cells/mm 2 ) (right) at 11M ART. (J) Flow cytometric proportions of major immune cell subsets in the colon at 11M ART between AL and CR animals. (K & L) Percentage of total CD4 + T cells expressing HLA-DR (K) and CD69 (L) in the colon at 11M ART obtained via flow cytometry. (M) Quantification of soluble CD14 (sCD14) in the plasma at 11M ART through ELISA. Values were interpolated using a standard curve and expressed in pg/mL. (N) Correlation between plasma sCD14 (ELISA) and colon immune cells/mm 2 (H&E) at 11M ART. (O) Volcano plot representing the mean log2 fold change of plasma cytokine and chemokine concentrations at 11M ART. red = over-expressed in CR, blue = under-expressed in CR, gray = nonsignificant. (P) Quantification of total SIV DNA in purified blood CD4 + T cells at ART initiation through 9 months of continuous ART. Data is represented as SIV DNA cell equivalents per million cells. (Q) Quantification of total SIV DNA in the LNs and colon at 11M ART. Data is represented as cell equivalents per million cells. Statistical Analyses: (A-G, I-M, P-Q) Mann-Whitney U-test, (H) PERMANOVA and (N) Spearman non-parametric correlation with confidence bands generated through linear regression. α=0.05.

    Article Snippet: Detection of sCD14 in monkey plasma was carried out using a CD14 Quantikine ELISA kit specific to rhesus macaques (R&D Systems, Minneapolis, MN) according to the manufacturer’s instructions.

    Techniques: Clinical Proteomics, Flow Cytometry, Staining, Expressing, Enzyme-linked Immunosorbent Assay, Purification, MANN-WHITNEY, Generated