Objective: Investigate the impact and mechanism of semaglutide (Sema) combined with high‐intensity interval training (HIIT) on hepatic glucose/lipid metabolism in db/db mice using untargeted metabolomics. Methods: Db/db mice were divided into model control, Sema alone, and Sema + HIIT groups, with db/m mice as controls. Sema (0.1 mg/kg/week) was administered subcutaneously, and the control group was subcutaneously injected with the same volume of distilled water. Engaging in HIIT swimming occurred for five consecutive days weekly. Weekly fasting plasma glucose (FPG), body mass, and food intake were assessed. After 8 weeks, blood/liver tissues were analyzed; liver metabolomics used LC–MS. Results: Following an 8‐week intervention, it was determined that the weight loss efficacy of Sema alone was suboptimal. The lowering of FPG did not differ significantly between the Sema alone and the combined intervention groups. The combined treatment demonstrated superior efficacy compared with Sema alone in enhancing liver weight, liver index, food intake, TG, TC, hepatic TG, and liver injury biomarkers (AST, ALT; P < 0.05). Histological findings indicated that the combination intervention markedly decreased fat vacuoles and inflammatory infiltration in hepatocytes ( P < 0.001). A total of 721 differential metabolites were identified after the combined intervention, with primary alterations in amino acids and their derivatives, lipids, energy metabolism, and bile acids, encompassing key pathways such as the TCA cycle, amino acid metabolism, and bile acid metabolism. Conclusions: Semaglutide combined with HIIT synergistically improves hepatic glucose and lipid metabolism in diabetic mice, providing a new treatment strategy for liver lipid disorders.

Objective: Task-oriented training (TOT) is the predominant rehabilitative training approach grounded in motor control theory. The effectiveness of treating hand dysfunction in children with cerebral palsy has not been established. This research conducts a systematic analysis of the rehabilitation treatment effects of TOT on hand dysfunction in children with cerebral palsy. Methods: Comprehensive searches were performed in databases including China National Knowledge Infrastructure, Wan Fang Database, Chinese Science and Technology Periodical Databases, SinoMed, PubMed, Web of Science, Embase, and Cochrane Library for randomized controlled trials of TOT utilized in the rehabilitation of hand dysfunction in pediatric patients with cerebral palsy. The control group underwent standard rehabilitation treatment, but the experimental group received TOT alongside the control group treatment. The search time concluded in August 2025, coinciding with the establishment of each database. Two researchers independently performed literature screening and data extraction, while the quality of the literature was assessed using the Cochrane risk of bias assessment tool. A meta-analysis was conducted with Revman 5.4 software. Results: Sixteen publications were included, encompassing 1,037 children with cerebral palsy. The meta-analysis indicated that the enhancement of hand function in the experimental group surpassed that of the control group [SMD = 1.44, 95% CI (1.12, 1.76), p < 0.01]. Additionally, the recovery of grip strength and cognitive ability was superior in the experimental group [SMD = 0.52, 95% CI (0.17, 0.87), p < 0.05; MD = 0.93, 95% CI (0.60, 1.27), p < 0.01]. Furthermore, the WeeFIM Scale score for the experimental group exceeded that of the control group [MD = 6.47, 95% CI (5.22, 7.72), p < 0.01]. Conclusion: TOT can boost the manual dexterity of children with cerebral palsy, and improve their grip strength and cognitive abilities. It is also more efficacious in enhancing the functional autonomy of youngsters. It is important to highlight that certain markers of the overall sample size, such as grip strength and IQ, were featured in only three publications, resulting in inadequate statistical power. Future research necessitates further large-sample, high-quality randomized controlled trials to validate the aforementioned conclusions.

Background: Metabolic prediction equations provide a low-cost means of estimating submaximal cycling oxygen uptake (VO₂), yet equations derived from maximal exercise are often applied to steady-state fixed-load protocols without validation. Portable analysers including the COSMED K5 and CORTEX MetaMax 3B permit field-based VO₂ measurement, but neither is error-free. We assessed agreement between four prediction equations and both devices in untrained young women, partitioning total error into bias-related and residual components. Methods: Nineteen untrained young women completed four constant-power cycling stages (30, 40, 50, 60 W). VO₂ was estimated from four equations (one submaximal cycling formula, three maximal-test equations) and measured concurrently with two portable indirect calorimeters. Linear mixed-effects models accounted for repeated within-participant observations. Agreement was evaluated using Lin’s concordance correlation coefficient (CCC), mean absolute percentage error (MAPE) and Bland–Altman analysis with proportional bias testing; 95% confidence intervals came from participant-level cluster bootstrap, with false discovery rate correction. Results: Every equation–device combination showed significant negative bias (all P < 0.01), and underprediction worsened at higher intensities. The ACSM submaximal equation with CORTEX MetaMax 3B showed the closest agreement (CCC = 0.69, MAPE = 12.9%, bias = − 1.71 mL·kg⁻¹·min⁻¹), with residual error accounting for 68.5% of total disagreement. The three maximal-test equations paired with COSMED K5 yielded the largest errors, 83–91% of which was bias-related. Even the best combination showed growing underprediction as power increased. Conclusions: The ACSM submaximal cycling equation showed the closest relative agreement among the eight tested pairings. Maximal-test equations agreed poorly with device-measured values during low-to-moderate fixed-load cycling. Without a laboratory gold standard, these findings reflect relative cross-device agreement rather than absolute accuracy, and disagreement cannot be attributed solely to equation error. The intensity-dependent bias suggests that a universal correction factor would be inadequate under the tested conditions. Any correction approach would require population- and device-specific external validation before clinical use.