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Abstract Proanthocyanidin‐rich grape seed extract (GSE) has been shown to have the potential to protect bones, although the underlying mechanism remains unknown. The current study aims to explore GSE's preventive and therapeutic impact on bone loss induced by oestrogen deficiency and the underlying mechanism through the gut microbiota (GM) and metabolomic responses. In oestrogen‐deficient ovariectomized (OVX) mice, GSE ameliorated bone loss by inhibiting the expansion of bone marrow adipose tissue (BMAT), restoring BMAT lipolysis and promoting bone formation. GSE regulated OVX‐induced GM dysbiosis by reducing the abundance of opportunistic pathogenic bacteria, such as Alistipes, Turicibacter and Romboutsia, while elevating the abundance of beneficial bacteria, such as Bifidobacterium. The modified GM primarily impacted lipid and amino acid metabolism. Furthermore, the serum metabolites of GSE exhibited a significant enrichment in lipid metabolism. In summary, GSE shows potential as a functional food for preventing oestrogen deficiency‐induced bone loss by modulating GM and metabolite‐mediated lipid metabolism.

Abstract Severe acute pancreatitis (SAP) onset and development are closely associated with intestinal barrier injury. Evidence from clinical practice and research has shown that electroacupuncture (EA) at the Zusanli (ST36) acupoint can improve intestinal barrier function and abdominal symptoms in patients with SAP; however, the specific mechanisms of action remain unclear. This study aimed to observe the changes in the intestinal microbiota and metabolites in SAP rats and to explore the effect of EA at ST36 on intestinal barrier injury in SAP rats. 16S rRNA gene sequencing combined with microbial diversity analysis, short‐chain fatty acids (SCFAs)‐targeted metabolomics, immunohistochemistry, immunofluorescence, western blotting, and other techniques were used to explore the mechanism of EA at bilateral ST36 acupoints on SAP‐related intestinal barrier injury. Our results showed that EA at ST36 could repair intestinal barrier injury by modulating intestinal microecology, thereby reducing intestinal inflammation, restoring intestinal function, and ultimately alleviating the prognosis of SAP. Our study provides new insights into the mechanisms and treatment of intestinal barrier injury in patients with SAP from the perspectives of microbiota and SCFAs regulation.

Ship dynamic models serve as the foundation for designing ship controllers, trajectory planning, and obstacle avoidance. Support vector regression (SVR) is a commonly used nonparametric modelling method for ship dynamics. Achieving high accuracy SVR models requires a substantial amount of training samples. Additionally, as the number of training samples increases, the computational efficiency for solving the quadratic programming problem (QPP) of SVR decreases. Ship controllers demand dynamic models with both high accuracy and computational efficiency. Therefore, to enhance the prediction accuracy and computational efficiency of SVR, this paper proposes a nonparametric modelling method based on twin SVR (TSVR). TSVR replaces a large QPP with a set of smaller QPPs, significantly enhancing generalizability and computational efficiency. To further improve the predictive accuracy of TSVR, the puma optimizer algorithm is employed to determine the optimal hyperparameters. The performance of the proposed method is validated using a Mariner class vessel. Gaussian white noise is introduced into the modelling data to simulate measurement error. The TSVR model accurately predicts various zigzag and turning circle manoeuvring motions under disturbance conditions, demonstrating its robustness and generalizability. Compared to the SVR model, the TSVR model achieves lower root mean square error and computational time, confirming its superior predictive accuracy and computational efficiency.