Liver fibrosis is an excessive wound-healing response triggered by chronic liver injury. It may eventually progress to cirrhosis, liver failure or liver cancer. Currently, there are no effective therapeutic strategies available. Deacetylasperulosidic acid methyl ester (DAM), a natural iridoid compound derived from Rubiaceae plants, possesses potential anti-inflammatory activity. However, its role in liver fibrosis and the underlying mechanisms remain unclear. Given the critical involvement of inflammation and gut microbiota dysbiosis in the development of liver fibrosis, this study aimed to investigate whether DAM could ameliorate liver fibrosis by modulating hepatic inflammation and intestinal dysbiosis. Using a carbon tetrachloride (CCl₄)-induced liver fibrosis model in mice, we evaluated DAM’s effects via histopathology, serum biochemical assays, liver fibrosis marker detection, intestinal barrier analysis and 16S rRNA gene sequencing. DAM treatment significantly alleviated hepatic histopathological damage, reduced serum levels of ALT, AST and γ-GT, inhibited hepatic collagen deposition (HA, LN, IV-C and PC Ⅲ) and reduced the expression of the fibrotic markers α-SMA and Col1a1. Furthermore, DAM markedly inhibited the hepatic expression of the pro-inflammatory cytokines TNF-α, IL-1β and IL-6, demonstrating its anti-inflammatory properties. DAM also attenuated intestinal structural damage, enhanced the expression of tight junction proteins Claudin-1, ZO-1 and Occludin, and improved intestinal barrier integrity, thereby reducing endotoxin translocation. 16S rRNA gene sequencing further revealed that DAM improved CCl₄-induced gut microbiota dysbiosis by reducing the abundance of pro-inflammatory genera such as Faecalibaculum and Dubosiella, thereby contributing to the restoration of microbial homeostasis. Collectively, DAM effectively ameliorates CCl₄-induced liver fibrosis by modulating hepatic inflammation and gut microbiota dysbiosis and may serve as a promising candidate for the prevention and treatment of liver fibrosis.

Background: Recently, considerable progress has been made in the quality of clinical trials conducted in China. However, the number of clinical trials conducted in China still falls below the global average standard. This study aims to identify research hotspots, collaborative networks, and evolutionary trends in the field of clinical trial quality management (CTQM) in China through bibliometrics and visual analyses to provide theoretical support and practical references for the optimization of domestipolicies.Methods: A systematic literature search was performed across the CNKI, Wanfang, and VIP databases to clinical trial quality management CTQM-related publications. Bibliometric analysis was conducted using CiteSpace 6.1.R6 and Co-Occurrence 20.5 (COOC 20.5), with key metrics including: annual output, active institutions, core journals, main authors, keywords, and thematic evolution. To capture internationally published works, supplementary searches were executed in Scopus, Web of Science, and PubMed for CTQM publications authored by Chinese scholars. Owing to the limited number of results (6 records), these documents were only included only in the discussion analysis.Results: A total of 528 articles were retrieved from the field of CTQM. The research process was divided into three periods: the basic standardization period (2003–2012), technology convergence period (2013–2019), and the intelligent transformation period (2020–2024). The theme shifted from the localization of the system to risk management, data management, and ethical governance driven by emerging technologies. The issuing organizations are primarily national-level administrative bodies, showing strong political-academic collaboration but limited cross-system partnerships. Artificial intelligence (AI)-based clinical trial quality management enhances quality control (QC) efficiency; however, it raises concerns about data privacy and ethical disparities.Conclusion: China’s research in the field of CTQM has led to the innovative integration of traditional quality control methods with new technologies. However, insufficient interdisciplinary cooperation and the absence of a data governance system pose ongoing challenges. In the future, it is necessary to build a three-dimensional ecosystem of “policy guidance, technological breakthroughs, and ethical synergy” to promote the rapid development of drug research in China.