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Panel a demonstrates the use of non-invasive biomarkers derived from stool (microbiome DNA), blood (metabolites), and urine, integrated via multi-omics and machine learning to predict fibrosis stages, assess HCC risk, forecast complications like HE, and predict treatment responses

Congcong Zhang, [email protected] These authors have contributed equally to this work Disclaimer All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers

All three of these polymerases contain a [4Fe-4S] within their C-terminal catalytic subunits (POLA, POLD1, and POLE1, respectively) (Shi et al., 2021)

Saxena et al., 2018

Scatozza, F