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  1. Zhou XD, Targher G, Byrne CD, Somers V, Kim SU, Chahal CAA, et al.
    Hepatol Int, 2023 Aug;17(4):773-791.
    PMID: 37204656 DOI: 10.1007/s12072-023-10543-8
    BACKGROUND: Fatty liver disease in the absence of excessive alcohol consumption is an increasingly common condition with a global prevalence of ~ 25-30% and is also associated with cardiovascular disease (CVD). Since systemic metabolic dysfunction underlies its pathogenesis, the term metabolic (dysfunction)-associated fatty liver disease (MAFLD) has been proposed for this condition. MAFLD is closely intertwined with obesity, type 2 diabetes mellitus and atherogenic dyslipidemia, which are established cardiovascular risk factors. Unlike CVD, which has received attention in the literature on fatty liver disease, the CVD risk associated with MAFLD is often underestimated, especially among Cardiologists.

    METHODS AND RESULTS: A multidisciplinary panel of fifty-two international experts comprising Hepatologists, Endocrinologists, Diabetologists, Cardiologists and Family Physicians from six continents (Asia, Europe, North America, South America, Africa and Oceania) participated in a formal Delphi survey and developed consensus statements on the association between MAFLD and the risk of CVD. Statements were developed on different aspects of CVD risk, ranging from epidemiology to mechanisms, screening, and management.

    CONCULSIONS: The expert panel identified important clinical associations between MAFLD and the risk of CVD that could serve to increase awareness of the adverse metabolic and cardiovascular outcomes of MAFLD. Finally, the expert panel also suggests potential areas for future research.

  2. He F, Aebersold R, Baker MS, Bian X, Bo X, Chan DW, et al.
    Nature, 2024 Dec;636(8042):322-331.
    PMID: 39663494 DOI: 10.1038/s41586-024-08280-5
    The human body contains trillions of cells, classified into specific cell types, with diverse morphologies and functions. In addition, cells of the same type can assume different states within an individual's body during their lifetime. Understanding the complexities of the proteome in the context of a human organism and its many potential states is a necessary requirement to understanding human biology, but these complexities can neither be predicted from the genome, nor have they been systematically measurable with available technologies. Recent advances in proteomic technology and computational sciences now provide opportunities to investigate the intricate biology of the human body at unprecedented resolution and scale. Here we introduce a big-science endeavour called π-HuB (proteomic navigator of the human body). The aim of the π-HuB project is to (1) generate and harness multimodality proteomic datasets to enhance our understanding of human biology; (2) facilitate disease risk assessment and diagnosis; (3) uncover new drug targets; (4) optimize appropriate therapeutic strategies; and (5) enable intelligent healthcare, thereby ushering in a new era of proteomics-driven phronesis medicine. This ambitious mission will be implemented by an international collaborative force of multidisciplinary research teams worldwide across academic, industrial and government sectors.
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