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Abstract Chronic kidney disease (CKD) is a global health challenge associated with lifestyle factors such as diet, alcohol, BMI, smoking, sleep, and physical activity. Metabolomics, especially nuclear magnetic resonance(NMR), offers insights into metabolic profiles’ role in diseases, but more research is needed on its connection to CKD and lifestyle factors. Therefore, we utilized the latest metabolomics data from the UK Biobank to explore the relationship between plasma metabolites and lifestyle factors, as well as to investigate the associations between various factors, including lifestyle-related metabolites, and the latent phase of CKD onset. The study enrolled approximately 500,000 participants from the UK Biobank (UKB) between 2006 and 2010, excluding 447,163 individuals with missing data for any metabolite in the NMR metabolomics, any biomarker in the blood chemistry (including eGFR, albumin, or cystatin C), any factor required for constructing the lifestyle score, or a baseline diagnosis of CKD. Lifestyle scores (LS) were calculated based on several factors, including diet, alcohol consumption, smoking, BMI, physical activity, and sleep. Each healthy lifestyle component contributed to the overall score, which ranged from 0 to 6. A total of 249 biological metabolites covering multiple categories were determined by the NMR Metabolomics Platform. Random forest algorithms and LASSO regression were employed to identify lifestyle-related metabolites. Subsequently, accelerated failure time models(AFT) were used to assess the relationship between multiple factors, including traditional CKD-related biomarkers (such as eGFR, cystatin C, and albumin) and lifestyle-related metabolites, with the latent phase of incident CKD. Finally, we performed Kaplan–Meier survival curve analysis on the significant variables identified in the AFT model. Over a mean follow-up period of 13.86 years, 2,279 incident chronic kidney disease (CKD) cases were diagnosed. Among the 249 metabolites analyzed, 15 were identified as lifestyle-related, primarily lipid metabolites. Notably, among these metabolites, each 1 mmol/L increase in triglycerides in large LDL particles accelerated the onset of CKD by 24%. Diabetes, hypertension, and smoking were associated with a 56.6%, 31.5% and 22.3% faster onset of CKD, respectively. Additionally, each unit increase in age, BMI, TDI, and cystatin C was linked to a 3.2%, 1.4%, 1.6% and 32.3% faster onset of CKD. In contrast, higher levels of albumin and eGFR slowed the onset of CKD, reducing the speed of progression by 3.0% and 3.9% per unit increase, respectively. Nuclear magnetic resonance metabolomics offers new insights into renal health, though further validation studies are needed in the future.

The functioning of ecosystem services in water-limited grassland ecosystems is significantly influenced by precipitation characteristics. This study aims to quantitatively assess the impact of different precipitation scenarios on grassland productivity using the APSIM model. Historical weather data from 1968 to 2017 and observational data from three types of steppes (meadow, typical, and desert steppe) in Inner Mongolia Autonomous Region from 2004 to 2010 were collected to determine key crop variety parameters for the APSIM model. The effects of annual precipitation, seasonal precipitation, and inter-growing season precipitation variability on aboveground net primary production (ANPP) and precipitation utilization efficiency (PUE) in different types of steppes were investigated by scenario simulation by validated model. The simulated ANPP shows distinctive responses to the changed rainfall characteristics, where the influence of precipitation decreasing is more evident than precipitation increasing by the same precipitation change. Regarding steppe types, the typical steppe responded more strongly to increased precipitation, while decreased precipitation led to higher decline in ANPP for desert steppe. Precipitation during growing seasons caused more significant change than dormancy seasons regarding ANPP, however, PUE show the opposite trend, indicating the contribution of unit level precipitation changes to productivity is significant during dormancy seasons. The effect of changing precipitation during middle growing season outweighed that of late growing season and early growing season, and the positive effect of increasing precipitation were more pronounced in typical steppe and desert steppe if facing early growing season precipitation increase in the future. The research results provide a theoretical basis and technical support for optimizing grassland production management.

The Han River, a key water source for China’s South-to-North Water Diversion Project, faces ecological challenges due to urbanization-driven heavy metal pollution and eutrophication. This study analyzed microbial communities in sediment samples from 15 sites using 16S rDNA sequencing. Our findings revealed a significant decrease in α-diversity with increasing copper (Cu) concentration, with the downstream region (group L) exhibiting higher diversity compared to the upstream region (group U). Group U was dominated by Alphaproteobacteria, while Clostridia prevailed in groups M and L. Analysis of β-nearest taxon index (βNTI) indicated that stochastic processes primarily shaped community assembly. Redundancy analysis (RDA) identified Cu, Fe, and Cr as key environmental factors influencing bacterial community composition in group U, while COD, Chl_a, pH, TN, and TP affected groups M and L. The study emphasizes the importance of addressing heavy metal pollution in eutrophic waters to protect microbial community diversity.

BackgroundType 2 diabetes mellitus (T2DM) is a metabolic disorder characterized by chronic hyperglycemia, mostly resulting from impaired insulin production and diminished glucose metabolism regulation. Qiwei Baizhu San (QWBZS) is a classic formula used in traditional Chinese medicine for the treatment of T2DM. A comprehensive analysis of the efficacy and safety of QWBZS in the treatment of T2DM is essential.MethodsThis study’s protocol was registered with PROSPERO (CRD42024576129). As of August 2024, we searched eight databases to screen and include randomized controlled trials of QWBZS for T2DM. Heterogeneity sources were examined via subgroup analyses, the robustness of the results was determined by sensitivity analyses, publication bias was evaluated using funnel plots and Egger’s test, evidence quality was appraised with GRADEpro, and possible mechanisms of QWBZS for T2DM were categorized and summarized.ResultsThis analysis encompassed 14 qualifying trials with a total of 1,169 subjects. The analytical results suggested that QWBZS, when combined with conventional treatment, was more effective than conventional treatment alone in improving FBG, 2hPG, HbA1c, HOMA-IR, TC, TG, LDL-C, and HDL-C. When QWBZS was used alone, it was more effective than conventional therapy in FBG, 2hPG, and HbA1c. And QWBZS could improve the overall effectiveness of clinical treatment in T2DM patients. The impact of QWBZS therapy alone on HOMA-IR and lipid metabolism remained unclear due to the limited number of trials included. Analysis of adverse events suggested that QWBZS was relatively safe.ConclusionThis study suggested that QWBZS, when combined with conventional treatment, was more effective in improving glucose metabolism, insulin resistance, and lipid metabolism compared to conventional treatment alone in individuals with T2DM. QWBZS alone also contributed to the regulation of blood glucose levels. Meanwhile, QWBZS could improve the overall effective rate of clinical treatment with a relatively high safety profile. Nevertheless, owing to the inferior quality and significant heterogeneity of the existing evidence, additional high-quality studies are requisite to furnish more dependable evidence for the future clinical application of QWBZS.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=576129, identifier [CRD42024576129].