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Many studies have found that the dysfunction in gut microbiota and the metabolic dysfunction can promote nonalcoholic fatty liver disease (NAFLD) development. Er-Chen decoction (EC) can be used in the treatment of NAFLD. However, the mechanism of this hepatoprotection is still unknown. In this study, we constructed a rat model with NAFLD fed with high-fat chow and administered EC treatment. The therapeutic effects of EC on NAFLD were evaluated by measuring transaminases, blood lipid levels, and pathological changes in the liver. In addition, we measured the effects of EC on liver inflammatory response and oxidative stress. The changes in gut microbiota after EC treatment were studied using 16S rRNA sequencing. Serum untargeted metabolomics analysis was also used to study the metabolic regulatory mechanisms of EC on NAFLD. The results showed that EC decreased the serum transaminases and lipid levels and improved the pathological changes in NAFLD rats. Furthermore, EC enhanced the activities of SOD and GSH-Px and decreased MDA level in the liver. EC treatment also decreased the gene and protein levels of IL-6, IL-1β, and TNF-α in the liver and serum. The 16S rRNA sequencing and untargeted metabolomics indicated that EC treatment affected the gut microbiota and regulated serum metabolism. Correlation analysis showed that the effects of EC on taurine and hypotaurine metabolism, cysteine and methionine metabolism, and vitamin B6 metabolism pathways were associated with affecting in the abundance of Lactobacillus, Dubosiella, Lachnospiraceae, Desulfovibri, Romboutsia, Akkermansia, Intestinimonas, and Candidatus_saccharimonas in the gut. In conclusion, our study confirmed the protective effect of EC on NAFLD. EC could treat NAFLD by inhibiting oxidative stress, reducing inflammatory responses, and improving the dysbiosis of gut microbiota and the modulation of the taurine and hypotaurine metabolism, cysteine and methionine metabolism, and vitamin B6 metabolism pathways in serum.

While air pollution is known as a risk factor for acute myocardial infarction (AMI) incidence, its impact on AMI subtypes—ST-elevation (STEMI) and non-ST-elevation myocardial infarction (NSTEMI)—remains incompletely understood. This study analyzed 149,632 AMI hospital admissions (70,730 STEMI and 69,594 NSTEM) in Beijing, China, from 2013 to 2019 using a time-stratified case-crossover design to evaluate the association between daily concentrations of six air pollutants (PM2.5, PM10, SO2, NO2, CO, and O3) and daily hospital admissions for total AMI, STEMI, and NSTEMI. Elevated levels of PM2.5, PM10, SO2, NO2, and CO were significantly associated with increased admission risk for total AMI, STEMI, and NSTEMI, with the strongest lag effects observed at lag0 for STEMI and at lag1 for NSTEMI. Subgroup analyses showed enhanced effects of PM2.5, SO2, and NO2 for total AMI and SO2 for NSTEMI among individuals with asthma. Additionally, a stronger effect of PM10 on STEMI was observed among individuals with stroke. These findings demonstrate that air pollutants differentially impact AMI subtypes through distinct temporal patterns and population vulnerabilities, underscoring the necessity of incorporating AMI subtype classification and individual susceptibility factors in environmental health risk assessments and related public health policies.

Background Social Determinants of Health (SDoHs) exert their influence primarily through social structures and environmental conditions. However, limited evidence exists regarding which specific SDoHs are associated with all-cause and cardiovascular mortality, and whether incorporating SDoHs into the Life’s Essential 8 (LE8) framework improves mortality prediction. Methods Data were analyzed from the 2005–2018 National Health and Nutrition Examination Survey (NHANES). Weighted Cox proportional hazards models were used to estimate associations between SDoHs and mortality. Additive interaction effects were quantified using the relative excess risk due to interaction (RERI). Predictive performance was assessed using continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI) for all-cause and cardiovascular mortality. Results Among 22,938 participants, 2,344 all-cause deaths (7.29%) and 720 cardiovascular deaths (2.12%) were observed over a median follow-up of 7.83 years. Multivariable analyses revealed that unemployment (HR = 1.44, 95% CI: 1.25–1.66), low-income status (poverty-to-income ratio (PIR) < 1; HR = 1.75, 95% CI: 1.32–2.31), severe food insecurity (HR = 1.45, 95% CI: 1.19–1.78), and being unmarried or living alone (HR = 1.43, 95% CI: 1.28–1.59) were independent predictors of all-cause mortality (all P  < 0.001). Low PIR (HR = 1.90, 95% CI: 1.21–2.97) and being unmarried or living alone (HR = 1.52, 95% CI: 1.26–1.85) were also significantly associated with cardiovascular mortality. Significant additive interactions were found between unemployment and low PIR (RERI = 0.90), food insecurity (RERI = 0.59), and unmarried or living alone (RERI = 0.37) for all-cause mortality. An additive interaction between low PIR and unmarried or living alone (RERI = 0.46) was observed for cardiovascular mortality. Including these SDoHs significantly improved 1-, 3-, 5-, and 10-year prediction of all-cause and cardiovascular mortality (NRI and IDI, all P  < 0.05). Conclusion Unemployment, low PIR, severe food insecurity, and being unmarried or living alone were identified as independent predictors of increased all-cause mortality. Low PIR and being unmarried or living alone were also associated with cardiovascular mortality. Incorporating these SDoHs into the LE8 framework improved predictive performance for both mortality outcomes. Graphical Abstract

Purpose Surface-guided radiotherapy (SGRT) has been demonstrated to be a promising supplement to cone-beam computed tomography (CBCT) in adjuvant breast cancer radiotherapy, but a rational combination mode is lacking in clinical practice. The aim of this study was to explore this mode and investigate its impact on the setup and dose accuracy. Methods and materials Daily SGRT and weekly CBCT images were acquired for 23 patients with breast cancer who received conventional fractionated radiotherapy after lumpectomy. Sixteen modes were acquired by randomly selecting one (CBCT 1 ), two (CBCT ij ), three (CBCT ijk ), four (CBCT ijkl ), and five (CBCT 12345 ) images from the CBCT images for fusion with the SGRT. The CTV-PTV margins, OAR doses, and dose coverage (V95%) of PTV and CTV was calculated based on SGRT setup errors with different regions of interest (ROIs). Dose correlations between these modalities were investigated using Pearson and Spearman’s methods. Patient-specific parameters were recorded to assess their impact on dose. Results The CTV-PTV margins decreased with increasing CBCT frequencies and were close to 5 mm for CBCT ijkl and CBCT 12345 . For the ipsilateral breast ROI, SGRT errors were larger in the AP direction, and target doses were higher in all modes than in the whole breast ROI (P < 0.05). In the ipsilateral ROI, the target dose correlations between all modes increased with increasing CBCT time intervals, decreased, and then increased with increasing CBCT frequencies, with the inflection point being CBCT participation at week 5. The dose deviations in CBCT 123 , CBCT 124 , CBCT 125 , CBCT ijkl , and CBCT 12345 were minimal and did not differ significantly (P > 0.05). There was excellent agreement between CBCT 124 and CBCT 1234 , and between (CBCT ijkl , CBCT 12345 ) and CBCT 125 in determining the classification for the percentage of PTV deviation (Kappa = 0.704–0.901). In addition, there were weak correlations between the patient’s D ips_b (ipsilateral breast diameter with bolus) and CTV doses in modes with CBCT participation at week 4 (R = 0.270 to 0.480). Conclusions Based on weekly CBCT, these modes with ipsilateral ROI and a combination of daily SGRT and a CBCT frequency of ≥ 3 were recommended, and CBCT was required at weeks 1 and 2 for CBCT ijk .

Background Prediabetes (pre-DM) is recognized as an intermediate state of glucose metabolism with a high potential to progress to diabetes mellitus (DM). However, its prognostic value in patients with premature acute myocardial infarction (PAMI) under the age of 35 remains unclear. This study aimed to investigate the relationship between pre-DM and long-term cardiovascular outcomes in this unique population. Methods This retrospective cohort study included 796 PAMI patients under 35 years of age who were categorized into three groups based to glycated hemoglobin levels or previous history: normal glucose regulation (NGR), pre-DM, and DM. The primary endpoint was the occurrence of major adverse cardiovascular and cerebrovascular events (MACCE) including all-cause death, non-fatal myocardial infarction, non-fatal stroke, or revascularization. Multivariable Cox regression, Kaplan–Meier and Subgroup analyses were performed. Results Pre-DM was observed in 22.1% of the PAMI cohort. During the median follow-up of 81 months, the incidence of MACCE was 23.5%, with significantly higher rates in the pre-DM and DM group compared to the NGR group (18.4%, 27.3%, 34.2%; p  < 0.001). After adjusting for confounding variables, pre-DM remained independently associated with an increased risk of MACCE (HR 1.51, 95%CI 1.05–2.18, p  = 0.027). Subgroup analysis demonstrated that pre-DM status was a robust risk factor compared to NGR. Moreover, pre-DM had a similar impact on MACCE events as DM in patients with PAMI. Conclusions Pre-DM is associated with a poor prognosis in young AMI patients under 35 years old, suggesting that it may be an independent predictor of adverse events in this population.

Non‐alcoholic steatohepatitis (NASH) is a severe form of fatty liver disease. If not treated, it can lead to liver damage, cirrhosis and even liver cancer. However, advances in treatment have remained relatively slow, and there is thus an urgent need to develop appropriate treatments. Hedan tablet (HDP) is used to treat metabolic syndrome. However, scientific understanding of the therapeutic effect of HDP on NASH remains limited. We used HDP to treat a methionine/choline‐deficient diet‐induced model of NASH in rats to elucidate the therapeutic effects of HDP on liver injury. In addition, we used untargeted metabolomics to investigate the effects of HDP on metabolites in liver of NASH rats, and further validated its effects on inflammation and lipid metabolism following screening for potential target pathways. HDP had considerable therapeutic, anti‐oxidant, and anti‐inflammatory effects on NASH. HDP could also alter the hepatic metabolites changed by NASH. Moreover, HDP considerable moderated NF‐κB and lipid metabolism‐related pathways. The present study found that HDP had remarkable therapeutic effects in NASH rats. The therapeutic efficacy of HDP in NASH mainly associated with regulation of NF‐κB and lipid metabolism‐related pathways via arachidonic acid metabolism, glycine‐serine‐threonine metabolism, as well as steroid hormone biosynthesis.

French is one of the best cultural tourism destinations in the world. Its development experiences in terms of cultural tourism are valuable for Hebei, whose competitiveness of cultural tourism is weak comparatively in spite of rich cultural resources. Specifically, France achieves great successes of cultural tourism through scientific planning, producing tourism products injected by cultures, and developing tourism festivals. On this basis, four suggestions are recommended to improve cultural tourism in Hebei Province based on its actual situation, namely building cultural brand of tourism, strengthening government management, and developing tourism derivatives, and reinforcing talent training.

Metal sulfides for hydrogen evolution catalysis typically suffer from unfavorable hydrogen desorption properties due to the strong interaction between the adsorbed H and the intensely electronegative sulfur. Here, we demonstrate a general strategy to improve the hydrogen evolution catalysis of metal sulfides by modulating the surface electron densities. The N modulated NiCo 2 S 4 nanowire arrays exhibit an overpotential of 41 mV at 10 mA cm −2 and a Tafel slope of 37 mV dec −1 , which are very close to the performance of the benchmark Pt/C in alkaline condition. X-ray photoelectron spectroscopy, synchrotron-based X-ray absorption spectroscopy, and density functional theory studies consistently confirm the surface electron densities of NiCo 2 S 4 have been effectively manipulated by N doping. The capability to modulate the electron densities of the catalytic sites could provide valuable insights for the rational design of highly efficient catalysts for hydrogen evolution and beyond. The hydrogen evolution reaction is a promising route to produce clean hydrogen fuel; however, its efficient electrolytic generation relies on expensive platinum. Here, the authors show how modulating electron density in a metal sulfide, NiCo 2 S 4 , boosts hydrogen desorption to achieve high catalytic activity.

In this study, a multi-objective particle swarm optimization (MOIPSO) algorithm is proposed to address complex optimization problems, including real-world engineering challenges. The algorithm retains the basic convergence mechanism of particle swarm optimization (PSO) as its core, while innovatively combining the fast non-dominated sorting technique to effectively evaluate and approximate the Pareto optimal solution set. To enhance the diversity and generalization of the solution set, the crowding distance mechanism is introduced, ensuring a good balance between multiple optimization objectives and a wider coverage of the solution space. Additionally, an acceleration factor based on trigonometric functions and an adaptive Gaussian mutation strategy are incorporated, improving the exploration ability of the particles in the search space and facilitating their movement towards the global optimal solution more effectively. The performance of the algorithm is verified using the multi-modal multi-objective benchmark function set provided by CEC2020, and comparisons are made with five advanced multi-objective metaheuristics. The MOIPSO algorithm is also applied to solve the design problem of rail transit upper cover foundation pit, further demonstrating the practical effectiveness of the proposed algorithm. The results show that MOIPSO not only performs well in multi-objective function testing but also proves highly competitive in solving real-world engineering problems. Note that the source codes of MOGWO are publicly available at https://au.mathworks.com/matlabcentral/fileexchange/177404-moipso-optimization-engineering-problem .

This study examines the preparation of controlled low strength material (CLSM) utilizing dredged river sludge as the primary raw material. Laboratory experiments were conducted to analyze the influence of various mix ratios—particularly the water-to-solid ratio (W/S), lime-to-soil ratio (L/S), and supplementary materials including fly ash and slag—on the flowability and unconfined compressive strength (UCS) of the solidified material. The findings indicate that flowability increases with both W/S and L/S ratios. The UCS displays an inverse relationship with the W/S ratio and a positive correlation with the L/S ratio. The addition of slag and fly ash enhances performance, with slag demonstrating superior strengthening properties. Drawing from the experimental results, the study concludes that the optimal mix proportion is highly dependent on specific engineering requirements. For higher-strength road subgrade backfill (requiring 400–800 kPa UCS), an L/S ratio of 0.20 and a W/S ratio of 0.72 was identified as optimal. Conversely, for high-flowability pipeline trench backfill (requiring 200–400 kPa UCS), an L/S ratio of 0.15 and a W/S ratio of 0.80 was found to be ideal.