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Journal Abstract Search

428 related items for PubMed ID: 38690269

  • 1.
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  • 2. Identification and validation of potential diagnostic signature and immune cell infiltration for NAFLD based on cuproptosis-related genes by bioinformatics analysis and machine learning.
    Ouyang G, Wu Z, Liu Z, Pan G, Wang Y, Liu J, Guo J, Liu T, Huang G, Zeng Y, Wei Z, He S, Yuan G.
    Front Immunol; 2023; 14():1251750. PubMed ID: 37822923
    [Abstract] [Full Text] [Related]

  • 3. Exosome-related gene identification and diagnostic model construction in hepatic ischemia-reperfusion injury.
    You Y, Chen S, Tang B, Xing X, Deng H, Wu Y.
    Sci Rep; 2024 Sep 28; 14(1):22450. PubMed ID: 39341981
    [Abstract] [Full Text] [Related]

  • 4. Comprehensive analysis of cuproptosis-related genes involved in immune infiltration and their use in the diagnosis of hepatic ischemia‒reperfusion injury: an experimental Study.
    Cai X, Deng J, Zhou X, Wang K, Cai H, Yan Y, Jiang J, Yang J, Gu J, Zhang Y, Ding Y, Sun Q, Wang W.
    Int J Surg; 2024 Jun 27. PubMed ID: 38935114
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  • 6. A comprehensive analysis of m6A/m7G/m5C/m1A-related gene expression and immune infiltration in liver ischemia-reperfusion injury by integrating bioinformatics and machine learning algorithms.
    Meng Z, Li X, Lu S, Hua Y, Yin B, Qian B, Li Z, Zhou Y, Sergeeva I, Fu Y, Ma Y.
    Eur J Med Res; 2024 Jun 13; 29(1):326. PubMed ID: 38867322
    [Abstract] [Full Text] [Related]

  • 7. Identification of hub glycolysis-related genes in acute myocardial infarction and their correlation with immune infiltration using bioinformatics analysis.
    Zhang X, Zhang L, Gao Y, Liu Z, Gong K.
    BMC Cardiovasc Disord; 2024 Jul 10; 24(1):349. PubMed ID: 38987688
    [Abstract] [Full Text] [Related]

  • 8. Identification of hub cuproptosis related genes and immune cell infiltration characteristics in periodontitis.
    Liu S, Ge J, Chu Y, Cai S, Wu J, Gong A, Zhang J.
    Front Immunol; 2023 Jul 10; 14():1164667. PubMed ID: 37215133
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  • 10. Identification of cuproptosis-related biomarkers and analysis of immune infiltration in allograft lung ischemia-reperfusion injury.
    Qin J, Xiao X, Li S, Wen N, Qin K, Li H, Wu J, Lu B, Li M, Sun X.
    Front Mol Biosci; 2023 Jul 10; 10():1269478. PubMed ID: 38074089
    [Abstract] [Full Text] [Related]

  • 11. Predicting mitophagy-related genes and unveiling liver endothelial cell heterogeneity in hepatic ischemia-reperfusion injury.
    Pan B, Ma X, Zhou S, Cheng X, Fang J, Yi Q, Li Y, Li S, Yang J.
    Front Immunol; 2024 Jul 10; 15():1370647. PubMed ID: 38694511
    [Abstract] [Full Text] [Related]

  • 12. Integrated bioinformatics combined with machine learning to analyze shared biomarkers and pathways in psoriasis and cervical squamous cell carcinoma.
    Liu L, Yin P, Yang R, Zhang G, Wu C, Zheng Y, Wu S, Liu M.
    Front Immunol; 2024 Jul 10; 15():1351908. PubMed ID: 38863714
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  • 14. Identifying hub circadian rhythm biomarkers and immune cell infiltration in rheumatoid arthritis.
    Wen P, Ma T, Zhang B, Hao L, Wang Y, Guo J, Song W, Wang J, Zhang Y.
    Front Immunol; 2022 Jul 10; 13():1004883. PubMed ID: 36238290
    [Abstract] [Full Text] [Related]

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  • 16. Identification of diagnostic signature and immune infiltration for ischemic cardiomyopathy based on cuproptosis-related genes through bioinformatics analysis and experimental validation.
    Tan X, Xu S, Zeng Y, Qin Z, Yu F, Jiang H, Xu H, Li X, Wang X, Zhang G, Ma B, Zhang T, Fan J, Bo X, Kang P, Tang J, Fan H, Zhou Y.
    Int Immunopharmacol; 2024 Sep 10; 138():112574. PubMed ID: 38971104
    [Abstract] [Full Text] [Related]

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  • 18. Identification and verification of a novel signature that combines cuproptosis-related genes with ferroptosis-related genes in osteoarthritis using bioinformatics analysis and experimental validation.
    He B, Liao Y, Tian M, Tang C, Tang Q, Ma F, Zhou W, Leng Y, Zhong D.
    Arthritis Res Ther; 2024 May 13; 26(1):100. PubMed ID: 38741149
    [Abstract] [Full Text] [Related]

  • 19. Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learning.
    Chen Y, Liao L, Wang B, Wu Z.
    Front Immunol; 2024 May 13; 15():1332279. PubMed ID: 38390317
    [Abstract] [Full Text] [Related]

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