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Terminalia chebula Retz. aqueous extract exerts anti-adhesive and anti-inflammatory effects against Helicobacter pylori: Insights from lysine metabolism remodeling and fecal metabolomics

By: Ling Ou · Bingyun Lu · Zhong Feng · Haobo Chen · Yuanjing Zou · Chuqiu Zhang · Qingchang Chen · Chang Peng · Meicun Yao · Ye Chen

28 August 2026 at 18:00

J Ethnopharmacol. 2026 Aug 29;373:122318. doi: 10.1016/j.jep.2026.122318. Online ahead of print.

ABSTRACT

ETHNOPHARMACOLOGICAL RELEVANCE: Helicobacter pylori (H. pylori) infection is a leading risk factor for chronic gastritis, peptic ulcers, and gastric cancer. The escalating antibiotic resistance of H. pylori and adverse effects arising from standard antibiotic regimens have underscored an urgent need for natural, food-complementary therapeutic alternatives. Terminalia chebula Retz., commonly named "Hezi" in traditional Chinese medicine and "Haritaki" in Ayurveda, is a well-recognized edible fruit with a long history of use in alleviating gastrointestinal disorders.

AIM OF THE STUDY: While it has been traditionally recognized for its anti-inflammatory and antimicrobial properties, its anti-adhesive efficacy against H. pylori and the metabolic mechanisms underlying its in vivo effects remain largely unexplored.

MATERIALS AND METHODS: This study adopted multiple analytical and experimental approaches: ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), RNA-seq, cell viability and adhesion assays, western blotting, hematoxylin and eosin (H&E) staining, enzyme-linked immunosorbent assay (ELISA), metabolomics, and proteomics.

RESULTS: In this study, 15 primary compounds in T. chebula aqueous extract were identified, predominantly tannins. Multi-omics analyses (transcriptomics, metabolomics, and proteomics) revealed that T. chebula aqueous extract significantly inhibited H. pylori adhesion and enriched the lysine degradation pathway. Notably, N-alpha-acetyl-L-lysine was characterized as a key metabolite in fecal metabolomic profiling, which was associated with glycosphingolipid biosynthesis, ferroptosis, HIF-1 signaling, lysosomal function, and arginine metabolism. In vitro assays confirmed that N-alpha-acetyl-L-lysine reduced H. pylori adhesion to GES-1 cells, reversed H. pylori-induced cellular damage, and suppressed the secretion of pro-inflammatory cytokines (IL-6 and TNF-α). In vivo, T. chebula aqueous extract administration markedly alleviated H. pylori-induced gastric inflammation by downregulating IL-6, IL-1β, TNF-α, TGF-β, and IFN-γ. Collectively, these findings demonstrate that T. chebula aqueous extract exerts anti-H. pylori effects by regulating lysine metabolism, with N-alpha-acetyl-L-lysine serving as a key metabolite via fecal metabolomics.

CONCLUSION: These findings highlight T. chebula's promising potential as a functional food ingredient or adjunctive therapy for H. pylori-related diseases, providing a natural, mechanism-based option for clinical intervention.

PMID:42665167 | DOI:10.1016/j.jep.2026.122318

Xpertbench: Expert Level Tasks with Rubrics-Based Evaluation

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

By: Xue Liu · Xin Ma · Yuxin Ma · Yongchang Peng · Duo Wang · Zhoufutu Wen · Ge Zhang · Kaiyuan Zhang · Xinyu Chen · Tianci He · Jiani Hou · Liang Hu · Ziyun Huang · Yongzhe Hui · Jianpeng Jiao · Chennan Ju · Yingru Kong · Yiran Li · Mengyun Liu · Luyao Ma · Fei Ni · Yiqing Ni · Yueyan Qiu · Yanle Ren · Zilin Shi · Zaiyuan Wang · Wenjie Yue · Shiyu Zhang · Xinyi Zhang · Kaiwen Zhao · Zhenwei Zhu · Shanshan Wu · Qi Zhao · Wenhao Huang

7 April 2026 at 12:00

arXiv:2604.02368v3 Announce Type: replace Abstract: As Large Language Models (LLMs) exhibit plateauing performance on conventional benchmarks, a pivotal challenge persists: evaluating their proficiency in complex, open-ended tasks characterizing genuine expert-level cognition. Existing frameworks suffer from narrow domain coverage, reliance on generalist tasks, or self-evaluation biases. To bridge this gap, we present XpertBench, a high-fidelity benchmark engineered to assess LLMs across authentic professional domains. XpertBench consists of 1,346 meticulously curated tasks across 80 categories, spanning finance, healthcare, legal services, education, and dual-track research (STEM and Humanities). These tasks are derived from over 1,000 submissions by domain experts--including researchers from elite institutions and practitioners with extensive clinical or industrial experience--ensuring superior ecological validity. Each task uses detailed rubrics with mostly 15-40 weighted checkpoints to assess professional rigor. To facilitate scalable yet human-aligned assessment, we introduce ShotJudge, a novel evaluation paradigm that employs LLM judges calibrated with expert few-shot exemplars to mitigate self-rewarding biases. Our empirical evaluation of state-of-the-art LLMs reveals a pronounced performance ceiling: even leading models achieve a peak success rate of only ~66%, with a mean score around 55%. Models also exhibit domain-specific divergence, showing non-overlapping strengths in quantitative reasoning versus linguistic synthesis.. These findings underscore a significant "expert-gap" in current AI systems and establish XpertBench as a critical instrument for navigating the transition from general-purpose assistants to specialized professional collaborators.