Fig 2: Acsl4 deficiency in hepatocytes alters cell death, inflammation, and proliferation in STZ-HFD model.TUNEL staining (A), cleaved caspase-3 staining (B), and 4-hydroxynonenal (4HNE) staining (C) of liver sections from Acsl4f/f and Acsl4?hepa mice after 12 and 20 weeks of STZ-HFD treatment (n = 7). Scale bars: 200 µm (A, B) or 100 µm (C). Quantification of TUNEL-positive cells (A), cleaved caspase-3-positive cells (B), and 4HNE-positive area (C) per view field. D Gene expression of inflammation markers (Il6, Tnf, Il1b, and Ccl2) was determined by qRT-PCR in livers and presented as relative expression compared to Acsl4f/f mice. E Infiltrating leukocytes were isolated from livers. Cells were stained for CD45 to identify leukocytes and with Hoechst 33258 to exclude dead cells. Cells were stained for suitable markers and gated as neutrophil granulocytes (CD11b+ Ly6G+) or macrophages (CD11b+ F4/80+). Gene expression of fibrosis markers (Acta2, Col1a1, Mmp2, Timp1, and Col5a2) (F) and proliferation markers (Ccnd1, Ccne1, and Ccna2) (G) was determined by qRT-PCR in livers and presented as relative expression compared to Acsl4f/f mice. H Immunoblot analysis of liver extracts for proliferation-related proteins (cyclin A2 and PCNA), using GAPDH as loading control. Quantification of protein levels, normalized to GAPDH. I Ki67 staining of liver sections (n = 7). Scale bars: 100 µm. Quantification of Ki67-positive area was performed using ImageJ. J Ki67 staining of tumor areas in livers from Acsl4f/f and Acsl4?hepa mice after 20 weeks of treatment (n = 5). Quantification of Ki67-positive area within tumor areas was performed using ImageJ. Data are expressed as mean ± SEM from 10 to 12 mice per group (unless stated otherwise). *p < 0.05; **p < 0.01; ***p < 0.001; unpaired t-test comparing Acsl4?hepa to Acsl4f/f mice for each time point.

Fig 3: Acsl4 deficiency in hepatocytes decreases liver fibrogenesis in DEN-CCl4 model.A TUNEL staining of liver sections from Acsl4f/f and Acsl4?hepa mice after 12 and 24 weeks of DEN-CCl4 treatment (n = 9). Scale bars: 200 µm. Quantification of TUNEL-positive cells per view field. B, C Gene expression of inflammation markers (Il6, Tnf, Il1b, Ccl2) (B) and proliferation markers (Ccnd1, Ccne1, and Ccna2) (C) was determined by qRT-PCR in livers and presented as relative expression compared to Acsl4f/f mice. D Ki67 staining of liver sections (n = 8). Scale bars: 100 µm. Quantification of Ki67-positive area was performed using ImageJ. E Gene expression of fibrosis markers (Acta2, Col1a1, Mmp2, Timp1, and Col5a2) was determined by qRT-PCR in livers and presented as relative expression compared to Acsl4f/f mice. F Sirius Red, Collagen I, and Masson Trichrome staining of liver sections (n = 9). Scale bars: 100 µm. G Quantification of Sirius Red-, Collagen I-, and Masson Trichrome-positive area was performed using ImageJ. Data are expressed as mean ± SEM from 13 to 16 mice per group (unless stated otherwise). *p < 0.05; **p < 0.01; ***p < 0.001; unpaired t test comparing Acsl4?hepa to Acsl4f/f mice for each time point.

Fig 4: Transcriptomic roadmap of HSC activation. (A) UMAP visualization of the qHSCs and aHSCs from pooled HSCs of control, CCL4‐treated, and bile duct‐ligated mice. (B) The expression of the qHSC marker genes Lrat and Ecm1 and aHSC marker genes Col1a1 and Acta2 overlaid on the UMAP of (A). (C) Heatmap depicting the top 50 representative genes (ordered by adjusted P‐values) of qHSC and aHSC. (D) Pseudotime trajectory indicating the activation of HSC during liver fibrosis. (E) Heatmap representing four gene clusters based on the dynamic gene expression pattern over pseudotime from the qHSC state to the aHSC state. Cluster 1: 202 genes; cluster 2: 82 genes; cluster 3: 288 genes, and cluster 4: 401 genes. Plot showing average expression of the four gene clusters along pseudotime. GO biological pathway analysis of the four gene clusters. Expression kinetics of representative genes of four gene clusters.