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tgfb2 1 2 antibody  (R&D Systems)


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    R&D Systems tgfb2 1 2 antibody
    Tgfb2 1 2 Antibody, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 7 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/tgfb2+1+2+antibody/TGF-beta+2%2F1%2E2+Antibody/10__1080_slash_2162402x__2020__1747677-45-2-7
    Average 94 stars, based on 7 article reviews
    tgfb2 1 2 antibody - by Bioz Stars, 2026-09
    94/100 stars

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    Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, <t>TGFB2,</t> IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.
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    Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, <t>TGFB2,</t> IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.
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    Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, <t>TGFB2,</t> IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.
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    R&D Systems tgfb2 1 2 antibody
    Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, <t>TGFB2,</t> IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.
    Tgfb2 1 2 Antibody, supplied by R&D Systems, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/tgfb2+1+2+antibody/TGF-beta+2%2F1%2E2+Antibody/10__1080_slash_2162402x__2020__1747677-45-2-7
    Average 94 stars, based on 1 article reviews
    tgfb2 1 2 antibody - by Bioz Stars, 2026-09
    94/100 stars
      Buy from Supplier

    94
    R&D Systems tgfb2 antibody
    Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, <t>TGFB2,</t> IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.
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    https://www.bioz.com/product/tgfb2+1+2+antibody/TGF-beta+2%2F1%2E2+Antibody/pm27259327-47-7-10
    Average 94 stars, based on 1 article reviews
    tgfb2 antibody - by Bioz Stars, 2026-09
    94/100 stars
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    Image Search Results


    Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, TGFB2, IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.

    Journal: Heliyon

    Article Title: Identification and experimental verification of immune-related hub genes in intervertebral disc degeneration

    doi: 10.1016/j.heliyon.2024.e34530

    Figure Lengend Snippet: Candidate hub gene identification and diagnosis model construction. (A) Coefficient profiles of variables in the LASSO regression model (Candidate genes: SORT1, PTGDS, TGFB2, IRF1, DEFB1, FABP3, AGT, NR1H3, HLA-DRA, and NFKBIZ). (B) Ten-fold cross-validation for turning parameter (λ) selection in the LASSO regression model. (C) The random forest algorithm of key genes. (D) Violin map of key genes. (E) Venn diagram of the intersection of the LASSO algorithm and core genes in the PPI network. (F) The ROC curve of the diagnostic model. (G) The ROC curve of the individual genes. (H) The ROC curve of the validation dataset.

    Article Snippet: The following antibodies were added and incubated at 4 °C overnight: NR1H3 antibody (14351-1-AP, proteintech, 1:2000), SORT1 antibody (12369-1-AP, proteintech, 1:2000), PTGDS antibody (10754-2-AP, proteintech, 1:1000), AGT antibody (11992-1-AP, proteintech, 1:1000), IRF1 antibody (11335-1-AP, proteintech, 1:500), TGFB2 antibody (28426-1-AP, proteintech, 1:500), and GAPDH antibody (10494-1-AP, proteintech, 1:5000).

    Techniques: Biomarker Discovery, Selection, Diagnostic Assay

    In vitro validation experiment. (A) Identification of M1 macrophages. (B) Cell coculture of nucleus pulposus cells and macrophages. (C) IL-1β and TNF-α levels in the supernatant after 24 h of coculture. (D) Levels of NR1H3, SORT1, PTGDS, AGT, IRF1, and TGFB2 mRNA in nucleus pulposus cells after 24 h of coculture. (E) Levels of NR1H3, SORT1, PTGDS, AGT, IRF1, and TGFB2 protein in nucleus pulposus cells after 24 h of coculture. The unedited images are referenced in . *: P < 0.05, **: P < 0.01, ***: P < 0.010, ****: P < 0.0001, ns: P > 0.05.

    Journal: Heliyon

    Article Title: Identification and experimental verification of immune-related hub genes in intervertebral disc degeneration

    doi: 10.1016/j.heliyon.2024.e34530

    Figure Lengend Snippet: In vitro validation experiment. (A) Identification of M1 macrophages. (B) Cell coculture of nucleus pulposus cells and macrophages. (C) IL-1β and TNF-α levels in the supernatant after 24 h of coculture. (D) Levels of NR1H3, SORT1, PTGDS, AGT, IRF1, and TGFB2 mRNA in nucleus pulposus cells after 24 h of coculture. (E) Levels of NR1H3, SORT1, PTGDS, AGT, IRF1, and TGFB2 protein in nucleus pulposus cells after 24 h of coculture. The unedited images are referenced in . *: P < 0.05, **: P < 0.01, ***: P < 0.010, ****: P < 0.0001, ns: P > 0.05.

    Article Snippet: The following antibodies were added and incubated at 4 °C overnight: NR1H3 antibody (14351-1-AP, proteintech, 1:2000), SORT1 antibody (12369-1-AP, proteintech, 1:2000), PTGDS antibody (10754-2-AP, proteintech, 1:1000), AGT antibody (11992-1-AP, proteintech, 1:1000), IRF1 antibody (11335-1-AP, proteintech, 1:500), TGFB2 antibody (28426-1-AP, proteintech, 1:500), and GAPDH antibody (10494-1-AP, proteintech, 1:5000).

    Techniques: In Vitro, Biomarker Discovery