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Received — 10 September 2026 ⏭

Omics in Hepatocellular
Elucidating mechanism of Biejia-Ruangan Compound Tablets against alcoholic liver disease through gut-liver axis using integrated multi-omics Xiang-Ying Yan · Wen-Jia Chen · Ya-Wen Chen · Yuan Zeng · Bing-Bing Cai · Na Lin · Yan-Qiong Zhang
Zhongguo Zhong Yao Za Zhi. 2026 Aug;51(15):4401-4409. doi: 10.19540/j.cnki.cjcmm.20260421.801.ABSTRACTBased on the gut-liver axis, this study integrated multi-omics and network pharmacology strategies to explore the mechanism of Biejia-Ruangan Compound Tablets(BRC), a preferred Chinese patent medicine for anti-hepatic fibrosis, in alleviating alcoholic liver disease(ALD). The Lieber-DeCarli ethanol liquid diet was used to establish the ALD model, and the pharmacodynamic effects of BRC were evalu
3 September 2026 at 18:00

Elucidating mechanism of Biejia-Ruangan Compound Tablets against alcoholic liver disease through gut-liver axis using integrated multi-omics

Omics in Hepatocellular

By: Xiang-Ying Yan · Wen-Jia Chen · Ya-Wen Chen · Yuan Zeng · Bing-Bing Cai · Na Lin · Yan-Qiong Zhang

3 September 2026 at 18:00

Zhongguo Zhong Yao Za Zhi. 2026 Aug;51(15):4401-4409. doi: 10.19540/j.cnki.cjcmm.20260421.801.

ABSTRACT

Based on the gut-liver axis, this study integrated multi-omics and network pharmacology strategies to explore the mechanism of Biejia-Ruangan Compound Tablets(BRC), a preferred Chinese patent medicine for anti-hepatic fibrosis, in alleviating alcoholic liver disease(ALD). The Lieber-DeCarli ethanol liquid diet was used to establish the ALD model, and the pharmacodynamic effects of BRC were evaluated. Non-targeted metabolomics and network pharmacology were employed to screen key metabolites and pathways, while multiple technical methods such as immunohistochemistry were used to verify key molecules in the gut-liver axis. The results showed that BRC significantly improved liver morphology and pathological damage in mice, reduced organ indices, and decreased serum levels of aspartate aminotransferase(AST) and alanine aminotransferase(ALT). BRC also alleviated hepatocellular steatosis, inflammatory infiltration, and fibrosis, and reduced the levels of reactive oxygen species(ROS) and partially restored superoxide dismutase(SOD) activity. Metabolomic analysis indicated that BRC could significantly reverse the disordered metabolic profiles of the intestine and liver, and increase the level of the differential metabolite prostaglandin E_2(PGE_2), which may be closely related to the adenosine 5'-monophosphate(AMP)-activated protein kinase(AMPK) signaling pathway. Compared with the model group, BRC effectively upregulated the expression of prostaglandin G/H synthase-2(COX-2) in the small intestine, inhibited the levels of inflammatory factors such as lipopolysaccharide(LPS), tumor necrosis factor-α(TNF-α), and interleukin-1β(IL-1β) in the liver, and promoted the expression of phosphorylated AMP-activated protein kinase catalytic subunit α2(p-AMPKα2), forkhead box protein O1(FOXO1), and peroxisome proliferator-activated receptor gamma coactivator-1α(PGC-1α) in the liver, as well as the activity of cytoplasmic phosphoenolpyruvate carboxykinase 1(PCK1). In conclusion, BRC may alleviate ALD by alleviating hepatic inflammation, oxidative stress, and metabolic disorders through the gut-liver axis via the COX-2/AMPK/FOXO1/PGC-1α/PCK1 signaling pathway. This study provides a scientific basis and new insights for the clinical application of BRC and the prevention and treatment of ALD with TCM.

PMID:42693054 | DOI:10.19540/j.cnki.cjcmm.20260421.801

Received — 27 May 2026 ⏭

cs.AI, q-bio.NC updates on arXiv.org
Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models Qingyuan Zeng · Pengxiang Cai · Zixin Guan · Ziyang Chen · Anglin Liu · Lang Qin · Xinyao Lai · Jintai Chen
arXiv:2605.25681v1 Announce Type: cross Abstract: Designing a single molecule that modulates two targets is a promising strategy for polypharmacology, but it remains substantially harder than standard single-target generation because one candidate must satisfy two binding requirements while preserving drug-likeness and synthesizability. Existing dual-target generative methods typically introduce dual-target capability by either retraining the generator or intervening in the diffusion process du
26 May 2026 at 12:00

Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models

cs.AI, q-bio.NC updates on arXiv.org

By: Qingyuan Zeng · Pengxiang Cai · Zixin Guan · Ziyang Chen · Anglin Liu · Lang Qin · Xinyao Lai · Jintai Chen

26 May 2026 at 12:00

arXiv:2605.25681v1 Announce Type: cross Abstract: Designing a single molecule that modulates two targets is a promising strategy for polypharmacology, but it remains substantially harder than standard single-target generation because one candidate must satisfy two binding requirements while preserving drug-likeness and synthesizability. Existing dual-target generative methods typically introduce dual-target capability by either retraining the generator or intervening in the diffusion process during sampling. The former can be costly and difficult to stabilize when dual-target supervision is sparse, while the latter may be sensitive to denoising-time target balancing and competing update directions. These limitations motivate a generator-preserving alternative that keeps the pretrained prior intact: can dual-target candidates instead be recovered from the input space of a frozen single-target diffusion model, without modifying its parameters or denoising dynamics? We formulate this task as a constrained multi-objective optimization problem and propose REUSE, a hierarchical evolutionary input-space search framework that combines pair-conditioned exploration with structured multi-stage selection to enforce dual-target affinity, chemical quality, and diversity. Experiments show that, compared with methods that modify the diffusion process, REUSE consistently improves dual-target affinity and balance, achieving a 20.9-percentage-point gain in Dual High Affinity over the strongest prior baseline while maintaining competitive molecular quality.