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Disclosures: Jing He: Nothing to Disclose, Boqiang Liu: Nothing to Disclose, Liang Shi: Nothing to Disclose, Xiujun Cai: Nothing to Disclose 707 AI-BASED DIGITAL PATHOLOGY SHOWS THAT DENIFANSTAT IMPROVES MULTIPLE PARAMETERS OF FIBROSIS AND REDUCES PROGRESSION TO CIRRHOSIS IN MASH PATIENTS WITH F2/F3 FIBROSIS RESULTS: OF THE FASCINATE-2 STUDY Mary Rinella 1 Wen-Wei Tsai 2 Katharine Grimmer 2 Eduardo Martins 2 Pierre Bedossa 3 Kutbuddin Akbary 4 Dean Tai 4 Marie O'Farrell 2 George Kemble 2 Rohit Loomba 5 , 1 The University of Chicago, 2 Sagimet Biosciences, 3 Liverpat, 4 HistoIndex, 5 University of California, San Diego Background: AI-based digital pathology is an advanced tool that complements conventional histopathology by allowing precise and quantitative analysis of histological changes

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Zmiz1 mutations impair neuronal differentiation and synaptic gene expression and are linked to reduced mTOR activity in other contexts, such as melanogenesis [122]