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Resveratrol in animal models of pancreatitis and pancreatic cancer: A systematic review with machine learning

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机构: [1]West China Centre of Excellence for Pancreatitis, Institute of Integrated Traditional Chinese and Western Medicine, West China-Liverpool Biomedical Research Centre, West China Hospital, Sichuan University, Chengdu 610041, China [2]Chinese Evidence-based Medicine and Cochrane China Centre, West China Hospital, Sichuan University, Chengdu 610041, China [3]Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 3GE, UK
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关键词: Resveratrol Acute pancreatitis Pancreatic cancer Meta-analysis Machine learning Mechanism

摘要:
Resveratrol (RES), a common type of plant polyphenols, has demonstrated promising therapeutic efficacy and safety in animal models of pancreatitis and pancreatic cancer. However, a comprehensive analysis of these data is currently unavailable. This study aimed to systematically review the preclinical evidence regarding RES's effects on animal models of pancreatitis and pancreatic cancer via meta-analyses and optimised machine learning techniques.Animal studies published from inception until June 30th 2024, were systematically retrieved and manually filtrated across databases including PubMed, EMBASE, Web of Science, Ovid MEDLINE, Scopus, and Cochrane Library. Methodological quality of the included studies was evaluated following the SYRCLE's RoB tool. Predefined outcomes included histopathology and relevant biochemical parameters for acute pancreatitis, and tumour weight/tumour volume for pancreatic cancer, comparing treatment and model groups. Pooled effect sizes of the outcomes were calculated using STATA 17.0 software. Machine learning techniques were employed to predict the optimal usage and dosage of RES in pancreatitis models.A total of 50 studies comprising 33 for acute pancreatitis, 1 chronic pancreatitis, and 16 for pancreatic cancer were included for data synthesis after screening 996 records. RES demonstrated significant improvements on pancreatic histopathology score, pancreatic function parameters (serum amylase and lipase), inflammatory markers (TNF-α, IL-1β, IL-6, and pancreatic myeloperoxidase), oxidative biomarkers (malondialdehyde and superoxide dismutase), and lung injury (lung histopathology and myeloperoxidase) in acute pancreatitis models. In pancreatic cancer models, RES notably reduced tumour weight and volume. Machine learning highlighted tree-structured Parzen estimator-optimised gradient boosted decision tree model as achieving the best performance, identifying course after disease induction, total dosage, single dosage, and total number of doses as critical factors for improving pancreatic histology. Optimal single dosage was 20-105 mg/kg with 3 to 9 doses.This study comprehensively demonstrates the therapeutic effects of RES in mitigating pancreatitis and pancreatic cancer in animal models. Anti-inflammatory, anti-oxidative, and anti-tumour growth properties are potential mechanisms of action for RES.Copyright © 2025 Elsevier GmbH. All rights reserved.

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出版当年[2025]版:
大类 | 1 区 医学
小类 | 1 区 药物化学 1 区 全科医学与补充医学 1 区 药学 1 区 植物科学
最新[2025]版:
大类 | 1 区 医学
小类 | 1 区 药物化学 1 区 全科医学与补充医学 1 区 药学 1 区 植物科学
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第一作者机构: [1]West China Centre of Excellence for Pancreatitis, Institute of Integrated Traditional Chinese and Western Medicine, West China-Liverpool Biomedical Research Centre, West China Hospital, Sichuan University, Chengdu 610041, China
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