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Accurately predicting the unconfined compressive strength (UCS) of microsilica-lime stabilized sulfate sand (MSLSS) is critical for the safe and efficient design of infrastructure in arid regions, yet it remains challenging due to the highly nonlinear relationships among influencing factors. This study pioneers the development of hybrid machine learning (ML) models, integrating the Sparrow Search Algorithm (SSA) with XGBoost (XGB), Random Forest, and Decision Tree, for predicting UCS of MSLSS. These models were trained and tested on experimental datasets incorporating input variables: lime content, microsilica content, curing days, curing condition, optimum moisture content (OMC), and maximum dry density. Comprehensive performance evaluation using metrics such as R 2 , MAE , MSE , and MRE demonstrated that SSA optimization markedly enhanced the predictive accuracy and generalization capability of all base models, with the RF model exhibiting the most substantial improvement. The hybrid XGB-SSA model achieved the highest overall predictive accuracy, yielding excellent performance on the testing set ( R 2  = 0.982, MAE  = 1.358). The standard XGB model also displayed competitive results, presenting a practical alternative when model complexity is a concern. SHAP-based interpretability analysis revealed OMC and microsilica content as the most influential input variables. This study provides valuable support for geotechnical design and engineering applications in relevant contexts.

Heart failure (HF) poses a significant global disease burden. The current evidence on the impact of air pollution on HF remains inconsistent. We aimed to conduct a systematic review of the literature and meta-analysis to provide a more comprehensive and multiperspective assessment of the associations between short- and long-term air pollution exposure and HF from epidemiological evidences. Three databases were searched up to 31 August 2022 for studies investigating the association between air pollutants ( , , , , CO, ) and HF hospitalization, incidence, or mortality. A random effects model was used to derive the risk estimations. Subgroup analysis was conducted by geographical location, age of participants, outcome, study design, covered area, the methods of exposure assessment, and the length of exposure window. Sensitivity analysis and adjustment for publication bias were performed to test the robustness of the results. Of 100 studies covering 20 countries worldwide, 81 were for short-term and 19 were for long-term exposure. Almost all air pollutants were adversely associated with the risk of HF in both short- and long-term exposure studies. For short-term exposures, we found the risk of HF increased by 1.8% [relative risk , 95% confidence interval (CI): 1.011, 1.025] and 1.6% ( , 95% CI: 1.011, 1.020) per increment of and , respectively. HF was also significantly associated with , , and CO, but not . Positive associations were stronger when exposure was considered over the previous 2 d (lag 0-1) rather than on the day of exposure only (lag 0). For long-term exposures, there were significant associations between several air pollutants and HF with RR (95% CI) of 1.748 (1.112, 2.747) per increment in , 1.212 (1.010, 1.454) per increment in , and 1.204 (1.069, 1.356) per increment in , respectively. The adverse associations of most pollutants with HF were greater in low- and middle-income countries than in high-income countries. Sensitivity analysis demonstrated the robustness of our results. Available evidence highlighted adverse associations between air pollution and HF regardless of short- and long-term exposure. Air pollution is still a prevalent public health issue globally and sustained policies and actions are called for to reduce the burden of HF. https://doi.org/10.1289/EHP11506.

Aquatic ecosystems worldwide are increasingly affected by human activities, with urbanization representing a major source of environmental stress. Channelization and flow depletion are key stressors in urban aquatic ecosystems. However, the combined effects of these factors on benthic macroinvertebrate and fish communities in urban rivers remain poorly understood. We examined the ecological impacts of channelization and flow depletion on benthic macroinvertebrates and fish in four urban rivers in Beijing, China: the natural high-flow Yongding River, the natural low-flow Gaojinggou River, the artificial high-flow Yongding River Diversion Channel, and the artificial low-flow Renmin Channel. By analyzing community composition, diversity, biomass, and water quality parameters, we assessed how river type (natural vs. artificial) and flow conditions (high vs. low) shape macroinvertebrate and fish communities across these urban rivers. Results showed that artificial channels had higher water temperatures, lower pH and DO, and higher concentrations of COD, NH 4 + , TP, fluorides, and sulfides compared to natural rivers, with flow depletion intensifying these effects. Both macroinvertebrate and fish community compositions varied significantly between river types and flow conditions. Channelization and flow depletion significantly reduced species richness, Shannon-Wiener diversity, and biomass in both macroinvertebrates and fish. Furthermore, we found a significant interaction between river type and flow depletion, as revealed by two-way ANOVA, with macroinvertebrate and fish communities in natural rivers being more sensitive to flow reductions than artificial channels. Redundancy analyses (RDAs) revealed that total phosphorus (TP) was the primary driver of macroinvertebrate community variation (contributing 23.6%), while DO played a crucial role in fish assemblages (contributing 20.6%). These findings underscore the significant impacts of channelization and flow depletion on urban river ecosystems, highlighting the vulnerability of natural rivers to flow depletion. Our study calls for urgent implementation of integrated management strategies to mitigate hydrological alterations, restore natural flow regimes, and reduce nutrient inputs, thereby enhancing the ecological resilience of urban aquatic ecosystems.

Construction in northwest China is generally packed with issues linked to loess soil with poor engineering properties and day-night and seasonal freeze-thaw (FT) actions. This study explored the potential benefits of nano-MgO (NM) as an innovative solution for improving mechanical properties of loess. To this end, a series of unconfined compression test (UCT) and nuclear magnetic resonance tests (NMRT) were conducted. Results showed that the unconfined compressive strength (UCS) exhibited an a “rise-fall” trend with the addition of NM. An optimum dosage of 2% NM is expected to bring about 71.9% and 143.5% strength gain for non-FT and FT samples, respectively. Meanwhile, the FT-induced strength reduction ratio decreased from 56.3% to 38.1% with NM content from 0 to 2%. These illustrated that NM can be very effective in improving mechanical performance and alleviating freeze-thaw damage. On the other hand, deformation modulus presented similar trends with UCS, while failure strain behaved in a reverse way. Accordingly, empirical models for UCS, as well as its relationships with modulus and failure strain, were established and validated by literature data. Furthermore, nuclear magnetic resonance tests revealed that adding NM could increase the proportion of bound water with intensive interaction, yielding improved performance and durability. This investigation shows that NM represents an alternative to cement for soil stabilization, and provides scientific support for the construction design in cold regions.

The unique features of the sulfenamides’ S(II)-N bond lead to interesting stereochemical properties and significant industrial functions. Here we present a chemoselective Chan–Lam coupling of sulfenamides to prepare N -arylated sulfenamides. A tridentate pybox ligand governs the chemoselectivity favoring C–N bond formation, and overrides the competitive C-S bond formation by preventing the S,N-bis-chelation of sulfenamides to copper center. The Cu(II)-derived resting state of catalyst is captured by UV-Vis spectra and EPR technique, and the key intermediate is confirmed by the EPR isotope response using 15 N-labeled sulfenamide. A computational mechanistic study reveals that N -arylation is both kinetically and thermodynamically favorable, with deprotonation of the sulfenamide nitrogen atom occurring prior to reductive elimination. The origin of ligand-controlled chemoselectivity is explored, with the interaction between the pybox ligand and the sulfenamide substrate controlling the energy of the S -arylation and the corresponding product distribution, in agreement with the EPR studies and kinetic results. Sulfenamides are a class of divalent sulfur-derived scaffolds featuring an S-N bond with many industrial applications, however, they are also challenging substrates for synthetic transformations. Here, the authors present a highly chemoselective ligand-controlled Chan–Lam coupling of sulfenamides as a straightforward route to N-arylated sulfenamides.

Esophageal squamous cell carcinoma is a major histological type of esophageal cancer, with distinct incidence and survival patterns among races. Although previous studies have characterized somatic mutations in this disease, a rigorous comparison between different patient populations has not been conducted. Here we sequence the samples of 316 Chinese patients, combine them with those from The Cancer Genome Atlas, and perform a comparative analysis between Asian and Caucasian patients. We find that mutated CSMD3 is associated with better prognosis in Asian patients. Applying a robust computational strategy that adjusts for both technical and biological confounding factors, we find that TP53 , EP300 , and NFE2L2 show higher mutational frequencies in Asian patients. Moreover, NFE2L2 mutations correlate with the allele status of a nearby high- F st SNP, suggesting their potential interaction. Our study provides insights into the molecular basis underlying the striking racial disparities of this disease, and represents a general computational framework for such a cross-population comparison. Esophageal squamous cell carcinoma (ESCC) exhibits differences in incidence and survival patterns among races. Here, analysis of Chinese and TCGA ESCC patients reveals that Asian patients exhibit higher TP53, EP300 and NFE2L2 mutational frequencies, and mutated CSMD3 associates with better prognosis.

To effectively identify the source of water in coal mines and prevent water-related accidents, this paper utilises the hydrochemical characteristics of the aquifers Shanxi Hanzui Coal Mine. The fuzzy C-means (FCM) clustering method is employed to classify water sample data, followed by principal component analysis (PCA) for dimensionality reduction to extract key features. The SMOTE algorithm is then applied to address the issue of class imbalance. Based on this, a decision tree model (FPS-DT) is constructed using the CART algorithm. To validate the model’s performance, five-fold cross-validation was used for evaluation. The results showed that the average classification accuracy of the FPS-DT model was 93%. In contrast, the accuracy of the comparison model, which only used PCA and decision trees, was 78%, indicating that the method proposed in this paper has significant advantages in terms of identification accuracy and generalisation capability. Additionally, the FPS-DT model features a clear structure and explicit classification rules, offering good interpretability and robustness. It can adapt to the real-time water source identification requirements of complex underground environments, providing theoretical support and technical assurance for coal mine safety production and water hazard prevention and control.

Migratory functionalization of C–H bonds through metal migration from carbon to carbon under transition metal catalysis is a process of significant academic and industrial interest. Herein, a palladium-catalyzed migratory cyclization of α -bromoalkene derivatives ArXCBr=CH 2 , in which X denotes a phosphorus (P(O)R), silicon (SiR 2 ), sulfur (SO 2 ), carbon (C(O)), nitrogen (NTs), or oxygen-based moiety, affording various benzoheterocyclic compounds has been developed. Mechanistic investigations have demonstrated that the cyclization reaction proceeds through an unexpected cascade, with trans -1,2-palladium migration between sp 2 carbons being a key step of catalytic cycle. To the best of our knowledge, this type of metal migration has not been reported previously. Migratory functionalization of C–H bonds through metal migration from carbon to carbon under transition metal catalysis is a process of significant academic and industrial interest. Here, the authors report a palladium-catalyzed migratory cyclization of α-bromoalkene derivatives to yield benzoheterocycles.

Periodic freezing–thawing is recognized as a real threat to the mechanical properties of reinforced loess, which has been used in the recent construction of high-speed railways in northwest China; however, the performance of these materials under periodic freezing–thawing and dynamic loading has rarely been investigated. In this work, dynamic triaxial tests were conducted on fly ash- and polypropylene fiber-reinforced loess with different blend ratios and freeze–thaw cycles. The dynamic shear modulus and damping ratio were investigated. The results revealed that cyclic freezing–thawing had a remarkable effect on the dynamic shear modulus and damping ratio, which demonstrated considerable reductions and increases, respectively, after cyclic freezing–thawing. Additionally, the dynamic shear modulus increased notably with the fly ash content and confining pressure and decreased with the water content. Meanwhile, the damping ratio increased with the fiber content and water content and decreased with the fly ash content and confining pressure. Comparatively, the effects of polypropylene fiber on dynamic behavior were found to be not significant. Furthermore, novel models were established to predict the dynamic shear modulus and damping ratio for reinforced loess. The results provide more information towards infrastructure design in seasonal frozen regions.

This study aims to investigate the roles of gut microbiota and plasma metabolites in salt sensitivity (SS) of blood pressure (SSBP) and hypertension. A 23-day, multicenter, dietary salt intervention trial (the MetaSalt study) recruited 528 participants who underwent a baseline observation, low-salt, and high-salt interventions. SSBP was assessed and used as the primary outcome, and fecal shotgun metagenome and plasma targeted metabolome were measured. We found that high salt significantly altered 85 gut-microbial species ( p  < 9.42 × 10 −5 ) and 70 metabolites ( p  < 2.26 × 10 −4 ). Among them, the changes in 22 species and 8 metabolites were associated with SSBP ( p  < 0.05), and a gut microbiota-acylcarnitine network implicated in SSBP was identified, with a gut microbiota-derived metabolite, isovalerylcarnitine, as the core metabolite. Isovalerylcarnitine was also inversely associated with SSBP in the GenSalt study ( p  = 0.0102). Importantly, increased isovalerylcarnitine attenuated SS hypertension and improved endothelial function in rats, and was associated with reduced risk (ranging from 13% to 19%) of BP progression and incident hypertension in a prospective cohort (n = 3907, median follow-up = 5.5 years). This study demonstrated that the gut-acylcarnitine axis may play roles in the development of SS hypertension. Trial number: ChiCTR1900025171. Here, combining data from a clinical trial and animal models, the authors show a role for a gut-acylcarnitine axis in the development of salt-sensitive hypertension, and identify isovalerylcarnitine as a key microbiota-derived modulator and potential target for the precision prevention of hypertension.