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  1. Article ; Online: The Prevalence of Advanced Liver Fibrosis Among Patients With Type 2 Diabetes Mellitus: A Single-Centre Experience in Penang, Malaysia.

    Lee, Xe Hui / Nor, Lisa Mohamed / Ang, Choon Seong / Yeow, Toh Peng / Lim, Shueh Lin

    Journal of the ASEAN Federation of Endocrine Societies

    2023  Volume 38, Issue 1, Page(s) 52–61

    Abstract: Objectives: Type 2 diabetes mellitus (T2DM) is an important risk factor for Non-alcoholic fatty liver disease (NAFLD). It worsens the course of NAFLD. We investigated the prevalence of advanced liver fibrosis among patients with T2DM. Our secondary ... ...

    Abstract Objectives: Type 2 diabetes mellitus (T2DM) is an important risk factor for Non-alcoholic fatty liver disease (NAFLD). It worsens the course of NAFLD. We investigated the prevalence of advanced liver fibrosis among patients with T2DM. Our secondary objectives were to describe patient demographics, to explore associated clinical factors, and to compare FIB-4 Index and liver stiffness measurement (LSM).
    Methodology: This was a cross-sectional study on 258 patients with T2DM duration of at least 10 years. Transient elastography (FibroScan
    Results: The prevalence of advanced liver fibrosis was 22.1%. Associated factors were body mass index (BMI), alanine transaminase (ALT), aspartate transaminase (AST), gamma-glutamyl transferase (GGT), triglyceride (TG) and high-density lipoprotein (HDL) cholesterol. Independent factors were BMI and GGT (
    Conclusion: Our study confirmed the high prevalence of advanced liver fibrosis among patients with long-standing T2DM. This study suggests the benefit of advanced liver fibrosis screening in patients with a minimum of 10 years of T2DM, especially those with high BMI and GGT.
    MeSH term(s) Humans ; Non-alcoholic Fatty Liver Disease/complications ; Diabetes Mellitus, Type 2/complications ; Prevalence ; Malaysia/epidemiology ; Cross-Sectional Studies ; Liver Cirrhosis/diagnosis ; gamma-Glutamyltransferase
    Chemical Substances gamma-Glutamyltransferase (EC 2.3.2.2)
    Language English
    Publishing date 2023-02-25
    Publishing country Philippines
    Document type Journal Article
    ZDB-ID 2893162-2
    ISSN 2308-118X ; 0857-1074
    ISSN (online) 2308-118X
    ISSN 0857-1074
    DOI 10.15605/jafes.038.01.08
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Urine supernatant reveals a signature that predicts survival in clear-cell renal cell carcinoma.

    Daza, Jorge / Salomé, Bérengère / Okhawere, Kennedy / Bane, Octavia / Meilika, Kirolos N / Korn, Talia G / Qi, Jingjing / Xe, Hui / Patel, Manishkumar / Brody, Rachel / Kim-Schulze, Seunghee / Sfakianos, John P / Lewis, Sara / Rich, Jordan M / Zuluaga, Laura / Badani, Ketan K / Horowitz, Amir

    BJU international

    2023  Volume 132, Issue 1, Page(s) 75–83

    Abstract: Objective: To profile the cell-free urine supernatant and plasma of a small cohort of clear-cell renal cell carcinoma (ccRCC) patients by measuring the relative concentrations of 92 proteins related to inflammation. Using The Cancer Genome Atlas (TCGA), ...

    Abstract Objective: To profile the cell-free urine supernatant and plasma of a small cohort of clear-cell renal cell carcinoma (ccRCC) patients by measuring the relative concentrations of 92 proteins related to inflammation. Using The Cancer Genome Atlas (TCGA), we then performed a targeted mRNA analysis of genes encoding the above proteins and defined their effects on overall survival (OS).
    Subjects/patients and methods: Samples were collected prospectively from ccRCC patients. A multiplex proximity extension assay was used to measure the concentrations of 92 inflammation-related proteins in cell-free urine supernatants and plasma. Transcriptomic and clinical information from ccRCC patients was obtained from TCGA. Unsupervised clustering and differential protein expression analyses were performed on protein concentration data. Targeted mRNA analysis on genes encoding significant differentially expressed proteins was performed using TCGA. Backward stepwise regression analyses were used to build a nomogram. The performance of the nomogram and clinical benefit was assessed by discrimination and calibration, and a decision curve analysis, respectively.
    Results: Unsupervised clustering analysis revealed inflammatory signatures in the cell-free urine supernatant of ccRCC patients. Backward stepwise regressions using TCGA data identified transcriptomic risk factors and risk groups associated with OS. A nomogram to predict 2-year and 5-year OS was developed using these risk factors. The decision curve analysis showed that our model was associated with a net benefit improvement compared to the treat-all/none strategies.
    Conclusion: We defined four novel biomarkers using proteomic and transcriptomic data that distinguish severity of prognosis in ccRCC. We showed that these biomarkers can be used in a model to predict 2-year and 5-year OS in ccRCC across different tumour stages. This type of analysis, if validated in the future, provides non-invasive prognostic information that could inform either management or surveillance strategies for patients.
    MeSH term(s) Humans ; Carcinoma, Renal Cell/genetics ; Proteomics ; Carcinoma ; Inflammation ; Kidney Neoplasms/genetics ; Prognosis
    Language English
    Publishing date 2023-03-07
    Publishing country England
    Document type Journal Article
    ZDB-ID 1462191-5
    ISSN 1464-410X ; 1464-4096 ; 1358-8672
    ISSN (online) 1464-410X
    ISSN 1464-4096 ; 1358-8672
    DOI 10.1111/bju.15989
    Database MEDical Literature Analysis and Retrieval System OnLINE

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