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soluble vcam 1 svcam 1  (R&D Systems)


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    Structured Review

    R&D Systems soluble vcam 1 svcam 1
    Blood biomarker dynamics during the annual 12‐week dosing gap. (A) NfL serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). <t>(B)</t> <t>SVCAM‐1</t> serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (C) SVCAM‐1 levels correlated to NTZ serum levels measured at baseline (green, time point A) and at the end of the 12‐week dosing gap (orange, time point B). Spearman (non‐parametric) analysis revealed a significant correlation ( p value < 0.0001).
    Soluble Vcam 1 Svcam 1, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 53 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/soluble+vcam+1+svcam+1/pmc12790166-62-2-5?v=R%26D+Systems
    Average 94 stars, based on 53 article reviews
    soluble vcam 1 svcam 1 - by Bioz Stars, 2026-08
    94/100 stars

    Images

    1) Product Images from "Annual 12‐Week Dosing Gap of Natalizumab: Clinical Efficacy, Blood Biomarkers, and CSF Cell Composition"

    Article Title: Annual 12‐Week Dosing Gap of Natalizumab: Clinical Efficacy, Blood Biomarkers, and CSF Cell Composition

    Journal: Annals of Clinical and Translational Neurology

    doi: 10.1002/acn3.70207

    Blood biomarker dynamics during the annual 12‐week dosing gap. (A) NfL serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (B) SVCAM‐1 serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (C) SVCAM‐1 levels correlated to NTZ serum levels measured at baseline (green, time point A) and at the end of the 12‐week dosing gap (orange, time point B). Spearman (non‐parametric) analysis revealed a significant correlation ( p value < 0.0001).
    Figure Legend Snippet: Blood biomarker dynamics during the annual 12‐week dosing gap. (A) NfL serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (B) SVCAM‐1 serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (C) SVCAM‐1 levels correlated to NTZ serum levels measured at baseline (green, time point A) and at the end of the 12‐week dosing gap (orange, time point B). Spearman (non‐parametric) analysis revealed a significant correlation ( p value < 0.0001).

    Techniques Used: Biomarker Discovery

    The annual 12‐week dosing gap modulates the composition of CSF immune cells. (A) Quantification of CD45+ CSF immune cell counts per ml by flow cytometry at time points A and B from six patients. (B) UMAP plots of CSF scRNAseq data immune cell subsets from nine patients at time points A (left) and B (right), annotated by aCSF. (C–I) Quantification of immune cell subset clusters as a percentage of cells within each sample from CSF of healthy donors (HD), treatment‐naïve MS (MS), and NTZ‐treated MS patients on SID (baseline, time point A) as well as after the A12WG (time point B). Only subsets with a significant increase from time points A and B are shown. (J–L) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of sVCAM‐1. Only significant positive correlations are shown. (M–N) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of NfL. Only significant correlations are shown. Statistical difference is indicated * p < 0.05. The circled dots indicate patients with MRI features after the treatment gap (patient #6, black; patient #8, blue).
    Figure Legend Snippet: The annual 12‐week dosing gap modulates the composition of CSF immune cells. (A) Quantification of CD45+ CSF immune cell counts per ml by flow cytometry at time points A and B from six patients. (B) UMAP plots of CSF scRNAseq data immune cell subsets from nine patients at time points A (left) and B (right), annotated by aCSF. (C–I) Quantification of immune cell subset clusters as a percentage of cells within each sample from CSF of healthy donors (HD), treatment‐naïve MS (MS), and NTZ‐treated MS patients on SID (baseline, time point A) as well as after the A12WG (time point B). Only subsets with a significant increase from time points A and B are shown. (J–L) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of sVCAM‐1. Only significant positive correlations are shown. (M–N) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of NfL. Only significant correlations are shown. Statistical difference is indicated * p < 0.05. The circled dots indicate patients with MRI features after the treatment gap (patient #6, black; patient #8, blue).

    Techniques Used: Flow Cytometry, Tandem Mass Spectroscopy

    Mechanism of action of natalizumab. (A) with a scenario where all VLA‐4‐expressing immune cells are blocked from trafficking into the CNS. Theoretical scenario (B) where some cells are blocked from trafficking into the CNS, while others are not. When VLA‐4 binds to VCAM‐1, sVCAM‐1 can be produced.
    Figure Legend Snippet: Mechanism of action of natalizumab. (A) with a scenario where all VLA‐4‐expressing immune cells are blocked from trafficking into the CNS. Theoretical scenario (B) where some cells are blocked from trafficking into the CNS, while others are not. When VLA‐4 binds to VCAM‐1, sVCAM‐1 can be produced.

    Techniques Used: Expressing, Produced



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    Blood biomarker dynamics during the annual 12‐week dosing gap. (A) NfL serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). <t>(B)</t> <t>SVCAM‐1</t> serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (C) SVCAM‐1 levels correlated to NTZ serum levels measured at baseline (green, time point A) and at the end of the 12‐week dosing gap (orange, time point B). Spearman (non‐parametric) analysis revealed a significant correlation ( p value < 0.0001).
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    Figure Lengend Snippet: Effects of YQHX on serum inflammatory cytokines and macrophage infiltration within atherosclerotic plaques in ApoE –/– mice. ( A–D ) Concentrations of TNF-α, IL-6, IL-1β, and sVCAM-1 in serum (n = 6). ( E ) Immunohistochemistry staining of F4/80 in plaques (n = 3). Data are expressed as means ± SD. ### P < 0.001 versus control, * P < 0.05 versus model, ** P < 0.01 versus model, *** P < 0.001 versus model.

    Article Snippet: According to the manufacturer’s protocols for TNF-α (Cat. #EK282, Lianke), IL-6 (Cat. #EK206, Lianke), interleukin-1 beta (IL-1β; Cat. #EK201B, Lianke), and soluble VCAM-1 (sVCAM-1) (Cat. #EK290, Lianke) ELISA kits, mouse serum samples were introduced into microplate wells and incubated with a diluted primary antibody solution.

    Techniques: Immunohistochemistry, Staining, Control

    Blood biomarker dynamics during the annual 12‐week dosing gap. (A) NfL serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (B) SVCAM‐1 serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (C) SVCAM‐1 levels correlated to NTZ serum levels measured at baseline (green, time point A) and at the end of the 12‐week dosing gap (orange, time point B). Spearman (non‐parametric) analysis revealed a significant correlation ( p value < 0.0001).

    Journal: Annals of Clinical and Translational Neurology

    Article Title: Annual 12‐Week Dosing Gap of Natalizumab: Clinical Efficacy, Blood Biomarkers, and CSF Cell Composition

    doi: 10.1002/acn3.70207

    Figure Lengend Snippet: Blood biomarker dynamics during the annual 12‐week dosing gap. (A) NfL serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (B) SVCAM‐1 serum levels measured during SID (baseline, time point A), at the end of the 12‐week dosing gap (time point B), as well as 3 months post gap (time point C). (C) SVCAM‐1 levels correlated to NTZ serum levels measured at baseline (green, time point A) and at the end of the 12‐week dosing gap (orange, time point B). Spearman (non‐parametric) analysis revealed a significant correlation ( p value < 0.0001).

    Article Snippet: NTZ and soluble VCAM‐1 (sVCAM‐1) (R&D Systems DY809) were measured by ELISA.

    Techniques: Biomarker Discovery

    The annual 12‐week dosing gap modulates the composition of CSF immune cells. (A) Quantification of CD45+ CSF immune cell counts per ml by flow cytometry at time points A and B from six patients. (B) UMAP plots of CSF scRNAseq data immune cell subsets from nine patients at time points A (left) and B (right), annotated by aCSF. (C–I) Quantification of immune cell subset clusters as a percentage of cells within each sample from CSF of healthy donors (HD), treatment‐naïve MS (MS), and NTZ‐treated MS patients on SID (baseline, time point A) as well as after the A12WG (time point B). Only subsets with a significant increase from time points A and B are shown. (J–L) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of sVCAM‐1. Only significant positive correlations are shown. (M–N) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of NfL. Only significant correlations are shown. Statistical difference is indicated * p < 0.05. The circled dots indicate patients with MRI features after the treatment gap (patient #6, black; patient #8, blue).

    Journal: Annals of Clinical and Translational Neurology

    Article Title: Annual 12‐Week Dosing Gap of Natalizumab: Clinical Efficacy, Blood Biomarkers, and CSF Cell Composition

    doi: 10.1002/acn3.70207

    Figure Lengend Snippet: The annual 12‐week dosing gap modulates the composition of CSF immune cells. (A) Quantification of CD45+ CSF immune cell counts per ml by flow cytometry at time points A and B from six patients. (B) UMAP plots of CSF scRNAseq data immune cell subsets from nine patients at time points A (left) and B (right), annotated by aCSF. (C–I) Quantification of immune cell subset clusters as a percentage of cells within each sample from CSF of healthy donors (HD), treatment‐naïve MS (MS), and NTZ‐treated MS patients on SID (baseline, time point A) as well as after the A12WG (time point B). Only subsets with a significant increase from time points A and B are shown. (J–L) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of sVCAM‐1. Only significant positive correlations are shown. (M–N) The scatterplots depict correlations between absolute changes from time points A and B of immune cell subset proportions in the CSF and serum concentrations of NfL. Only significant correlations are shown. Statistical difference is indicated * p < 0.05. The circled dots indicate patients with MRI features after the treatment gap (patient #6, black; patient #8, blue).

    Article Snippet: NTZ and soluble VCAM‐1 (sVCAM‐1) (R&D Systems DY809) were measured by ELISA.

    Techniques: Flow Cytometry, Tandem Mass Spectroscopy

    Mechanism of action of natalizumab. (A) with a scenario where all VLA‐4‐expressing immune cells are blocked from trafficking into the CNS. Theoretical scenario (B) where some cells are blocked from trafficking into the CNS, while others are not. When VLA‐4 binds to VCAM‐1, sVCAM‐1 can be produced.

    Journal: Annals of Clinical and Translational Neurology

    Article Title: Annual 12‐Week Dosing Gap of Natalizumab: Clinical Efficacy, Blood Biomarkers, and CSF Cell Composition

    doi: 10.1002/acn3.70207

    Figure Lengend Snippet: Mechanism of action of natalizumab. (A) with a scenario where all VLA‐4‐expressing immune cells are blocked from trafficking into the CNS. Theoretical scenario (B) where some cells are blocked from trafficking into the CNS, while others are not. When VLA‐4 binds to VCAM‐1, sVCAM‐1 can be produced.

    Article Snippet: NTZ and soluble VCAM‐1 (sVCAM‐1) (R&D Systems DY809) were measured by ELISA.

    Techniques: Expressing, Produced