2026-10-14T20:03:34Z https://www.scidb.cn/oai

10.57760/sciencedb.29531 2026-03-18T14:07:23Z

2026-03-18 Dataset for "Machine Learning–Guided Design of Mechanoadaptive Bioglues for Multi-Tissue Trauma and First-Aid Applications" doi:10.57760/sciencedb.29531 en This dataset supports the research on machine learning (ML)-guided rational design of mechanoadaptive bioglues (TuneGlues) for multi-tissue trauma repair and emergency first-aid applications. It contains the full raw experimental data generated from the study, including:Chemical synthesis and structural characterization data of 4 polyurethane prepolymers and 2 amino acid-mimetic crosslinkers (the building blocks of TuneGlues);Mechanical property testing data of 72 groups of TuneGlues formulations, which serves as the training dataset for ML model construction;Raw data of ML model training, 5-fold cross-validation, performance evaluation, and the 100,000-group formulation-mechanical property prediction database;In vitro and in vivo experimental data of TuneGlues, including tissue adhesion performance, biocompatibility, degradation kinetics, hemostatic efficacy, and long-term adhesion stability;Preclinical validation data of TuneGlues in porcine and goat models of single-tissue (lung, intestine, skin, bone) and multi-tissue trauma, as well as performance verification data of the integrated portable first-aid delivery device.This dataset can be reused for the development of novel tissue adhesives, ML-driven biomaterial design, wound healing research, and emergency medical device development. The data correspond to the peer-reviewed and accepted manuscript entitled Machine Learning–Guided Design of Mechanoadaptive Bioglues for Multi-Tissue Trauma and First-Aid Applications. Machine learning; Bioglue; Tissue adhesive; Multi-tissue trauma; Wound healing; First-aid device Chengkai Xuan Yanbo Jia Muyuan Chai Huaiming Wang Xuehua Zhao Wei Yang Xuemin Liu Chaoyu Cao Wenxuan Wu Yaqiang Jiang Zhenxing Wang Serge Ostrovidov Ke Zheng Kai Wu Yunhua Chen Shentao Yan Feng Xu Xuetao Shi PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank