ObjectiveTo investigate whether Huanglian Jiedutang can inhibit neutrophil infiltration in the brains of middle cerebral artery occlusion （MCAO） mice by regulating the expression of neutrophil-related chemokines in exosomes， thereby achieving therapeutic effects. MethodsA total of 130 male specific pathogen-free （SPF） C57BL/6J mice were randomly divided into four groups： Sham-operated group， MCAO model group， Huanglian Jiedutang group （6 g·kg^-1）， and Ginaton group （21.6 mg·kg^-1）， with 10 mice in the Ginaton group and 40 mice in each of the remaining three groups. Mice in the Huanglian Jiedutang group and the Ginaton group were administered the corresponding drugs by oral gavage once daily at a volume of 0.15 mL·（10 g）^-1 for 7 consecutive days， while the sham-operated and model groups received an equal volume of saline via the same route. After 7 days， MCAO surgery was performed. The distal and proximal ends of the right common carotid artery （CCA） were ligated， a small incision was made between the two ligatures， and a silicone rubber-coated monofilament with a rounded tip was inserted into the lumen to occlude the CCA. The filament was left in place for 1 h to establish a focal cerebral ischemia model. At 24 h after modeling， mice were evaluated. Neurological function was assessed using the Longa score. Cerebral infarct volume was measured by 2，3，5-triphenyltetrazolium chloride （TTC） staining. Cerebral blood flow was observed by laser speckle imaging. Hematoxylin and eosin （HE） staining and Nissl staining were used to observe pathological changes in brain tissues. Exosomes were isolated from mouse plasma and brain tissues by ultracentrifugation and molecular size exclusion and identified by electron microscopy， particle size analysis， and protein blotting. Long-chain RNA libraries of exosomes were constructed and sequenced. Real-time quantitative reverse transcription polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of inflammatory factors and neutrophil-related chemokines in exosomes from plasma and brain tissues of each group. Enzyme-linked immunosorbent assay （ELISA） was used to detect the protein expression of inflammatory factors and neutrophil-related chemokines in exosomes from brain tissues of each group. Immunohistochemistry was used to detect the expression of the neutrophil-specific protein myeloperoxidase （MPO） in the brains of mice in each group. ResultsCompared with the sham-operated group， the model group showed decreased neurological function scores （P<0.01）， obvious cerebral infarction （P<0.01）， reduced cerebral blood flow （P<0.01）， neuronal necrosis in the brain， and decreased numbers of Nissl bodies （P<0.01）. The mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were significantly increased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were increased （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were elevated （P<0.01）. Compared with the model group， the Huanglian Jiedutang group and the Ginaton group showed increased neurological function scores （P<0.05）， reduced cerebral infarct volume （P<0.01）， restored cerebral blood flow （P<0.01）， reduced necrotic cells in the brain， and increased numbers of Nissl bodies （P<0.01）. In the Huanglian Jiedutang group， the mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were decreased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were reduced （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were decreased （P<0.01）. ConclusionHuanglian Jiedutang can effectively regulate the expression of neutrophil-related chemokines in exosomes from plasma and brain tissues of MCAO mice， thereby reducing neutrophil infiltration in the brain and achieving therapeutic effects.

ObjectiveTo investigate whether Huanglian Jiedutang can inhibit neutrophil infiltration in the brains of middle cerebral artery occlusion （MCAO） mice by regulating the expression of neutrophil-related chemokines in exosomes， thereby achieving therapeutic effects. MethodsA total of 130 male specific pathogen-free （SPF） C57BL/6J mice were randomly divided into four groups： Sham-operated group， MCAO model group， Huanglian Jiedutang group （6 g·kg^-1）， and Ginaton group （21.6 mg·kg^-1）， with 10 mice in the Ginaton group and 40 mice in each of the remaining three groups. Mice in the Huanglian Jiedutang group and the Ginaton group were administered the corresponding drugs by oral gavage once daily at a volume of 0.15 mL·（10 g）^-1 for 7 consecutive days， while the sham-operated and model groups received an equal volume of saline via the same route. After 7 days， MCAO surgery was performed. The distal and proximal ends of the right common carotid artery （CCA） were ligated， a small incision was made between the two ligatures， and a silicone rubber-coated monofilament with a rounded tip was inserted into the lumen to occlude the CCA. The filament was left in place for 1 h to establish a focal cerebral ischemia model. At 24 h after modeling， mice were evaluated. Neurological function was assessed using the Longa score. Cerebral infarct volume was measured by 2，3，5-triphenyltetrazolium chloride （TTC） staining. Cerebral blood flow was observed by laser speckle imaging. Hematoxylin and eosin （HE） staining and Nissl staining were used to observe pathological changes in brain tissues. Exosomes were isolated from mouse plasma and brain tissues by ultracentrifugation and molecular size exclusion and identified by electron microscopy， particle size analysis， and protein blotting. Long-chain RNA libraries of exosomes were constructed and sequenced. Real-time quantitative reverse transcription polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of inflammatory factors and neutrophil-related chemokines in exosomes from plasma and brain tissues of each group. Enzyme-linked immunosorbent assay （ELISA） was used to detect the protein expression of inflammatory factors and neutrophil-related chemokines in exosomes from brain tissues of each group. Immunohistochemistry was used to detect the expression of the neutrophil-specific protein myeloperoxidase （MPO） in the brains of mice in each group. ResultsCompared with the sham-operated group， the model group showed decreased neurological function scores （P<0.01）， obvious cerebral infarction （P<0.01）， reduced cerebral blood flow （P<0.01）， neuronal necrosis in the brain， and decreased numbers of Nissl bodies （P<0.01）. The mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were significantly increased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were increased （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were elevated （P<0.01）. Compared with the model group， the Huanglian Jiedutang group and the Ginaton group showed increased neurological function scores （P<0.05）， reduced cerebral infarct volume （P<0.01）， restored cerebral blood flow （P<0.01）， reduced necrotic cells in the brain， and increased numbers of Nissl bodies （P<0.01）. In the Huanglian Jiedutang group， the mRNA expression levels of IL-1β， MPO， CXCL1， CXCL2， CXCL3， CXCL10， CCL2， and CCL3 in exosomes from plasma and brain tissues were decreased （P<0.05， P<0.01）. The protein expression levels of IL-1β， MPO， CXCL2， and CXCL10 in exosomes from brain tissues were reduced （P<0.05， P<0.01）， and MPO-positive rates and mean optical density values in brain tissues were decreased （P<0.01）. ConclusionHuanglian Jiedutang can effectively regulate the expression of neutrophil-related chemokines in exosomes from plasma and brain tissues of MCAO mice， thereby reducing neutrophil infiltration in the brain and achieving therapeutic effects.

Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective: To investigate the prevalence of depressive symptoms and their associated factors among students in Zhejiang Province, so as to provide evidence for targeted prevention strategies. Methods: A stratified cluster random sampling method was used to select 23 829 college students and primary and secondary school students aged 11-22 years in Zhejiang Province from December 2019 to February 2020. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale (CES-D). Three machine learning algorithms, including Logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost), were applied to construct predictive models, and key associated factors were identified by comparing model performance. Results: The detection rate of depressive symptoms among students in Zhejiang Province was 19.92%; the rates were 17.20% in boys and 22.87% in girls( χ 2=164.89, P <0.05). The CES-D total score was 9.00(4.00,13.00). Multiple Logistic regression analysis revealed that loneliness had the strongest association with depressive symptoms ( AOR =9.58, 95% CI =8.90-10.30), while bullying exposure ( AOR =4.39, 95% CI =4.02-4.80), female students( AOR =1.81, 95% CI =1.68-1.94)，never eating breakfast ( AOR = 2.34，95% CI =2.00-2.67) and overweight/obesity( AOR =1.10，95% CI =1.08-1.12) were significant associated factors of depressive symptoms among students (all P <0.05). Analysis based on the XGBoost model produced highly consistent results, identifying the above 5 factors as the core features with the highest correlation strength (all P <0.05). Conclusions Female, loneliness, bullying exposure, frequency of weekly breakfast and BMI are strongly associated with depressive symptoms among students. Mental health education for high risk groups should be strengthened, and coordinated prevention efforts between families and schools are recommended.

Objective To systematically evaluate the therapeutic effects of different surgical procedures for ischemic mitral regurgitation (IMR). Methods Computer searches were conducted in CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, Embase, and Web of Science, with the search time limit from the inception of the databases to February 2024. Two researchers independently screened the literature, extracted data, used the Cochrane bias risk assessment tool to evaluate the quality of the included studies, and used Stata 17.0 software to analyze the data. Results A total of 19 randomized controlled trials involving 6139 patients were finally included, involving six surgical procedures, and the overall quality of the included studies was relatively high. The results of the network meta-analysis showed that the 30-day all-cause mortality rate of mitral valve repair (MVr) was significantly lower than that of coronary artery bypass grafting (CABG) [OR=0.24, 95%CI (0.07, 0.87), P<0.01], mitral valve replacement (MVR) [OR=0.43, 95%CI (0.23, 0.79), P=0.02], CABG+MVR [OR=0.21, 95%CI (0.04, 0.95), P=0.03] and transcatheter mitral valve edge-to-edge repair (TEER) using MitraClip [OR=0.13, 95%CI (0.02, 0.87), P<0.01]. The 30-day all-cause mortality rate of CABG+MVr was significantly lower than that of CABG [OR=0.56, 95%CI (0.33, 0.93), P=0.02] and CABG+MVR [OR=0.48, 95%CI (0.24, 0.94), P=0.04], and the best probability ranking results showed that MVR might be the most effective in reducing the 30-day all-cause mortality rate. The incidence of renal complications in CABG+MVr was significantly lower than that in CABG+MVR [OR=0.42, 95%CI (0.21, 0.83), P=0.01]; the best probability ranking results showed that CABG+MVr might be the most effective in reducing renal complications. Conclusion The current limited evidence suggests that CABG+MVr and MVr may be the best surgical intervention methods for IMR patients at present. Due to the limitations of the number and quality of included studies, the above conclusions still need to be verified by more high-quality studies.

Objective: To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents. Methods: A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model. Results: The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05). Conclusion The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.

OBJECTIVE To systematically evaluate the quality of the Heat-clearing and symptom-relieving formula and screen potential marker components that influence the quality of the formula. METHODS The contents of 11 components （calycosin-7- O - β -D-glucoside， ononin， hyperoside， isoquercitrin， baicalin， baicalein， cryptotanshinone， tanshinone Ⅱ A ， tanshinone Ⅰ， senkyunolide A， ferulic acid） in the Heat-clearing and symptom-relieving formula were determined by high-performance liquid chromatography-tandem mass spectrometry （HPLC-MS/MS）. Using the contents of the aforementioned components as variables， cluster analysis （CA）， principal component analysis （PCA）， and orthogonal partial least squares-discriminant analysis （OPLS-DA） were conducted using OriginPro 2024 software and SIMCA 14.1 software； marker components affecting the quality of the Heat-clearing and symptom-relieving formula were then screened based on the criteria of variable importance in the projection （VIP） value＞1 and P ＜0.05. The comprehensive evaluation of 20 batches of samples was carried out using the entropy weight-technique for order preference by similarity to ideal solution（TOPSIS） and grey correlation analysis （GCA） methods. RESULTS The contents of the above 11 components were 7.993-72.866， 4.542-31.228， 727.666-1 901.884， 496.846-1 293.279， 1 995.501-6 779.150， 54.500-241.280， 150.302-304.339， 79.698-189.206， 257.118-682.418， 5.498-21.687， 7.524-26.935 μg/g. CA， PCA and OPLS-DA results showed that 20 batches of samples were grouped into 2 categories. Q1， Q3， Q4， Q7-Q9， Q12， Q15， Q16 were grouped into one category， and the rest were grouped into another category； VIP values of ferulic acid， tanshinone Ⅱ A ， baicalin， cryptotanshinone， calycosin-7- O - β -D-glucoside and ononin were all greater than 1 （ P ＜0.05）. Both the entropy weight-TOPSIS and GCA methods showed that the samples ranked in the top 11 according to the euclidean distance and relative correlation degree were Q2， Q5， Q6， Q10， Q11， Q13， Q14， Q17-Q20. CONCLUSIONS The established HPLC-MS/MS method is rapid， accurate and highly sens itive. Combined with chemical pattern recognition analysis， entropy weight-TOPSIS and GCA methods， this method can be used to evaluate the quality of the Heat-clearing and symptom-relieving formula. Ferulic acid， tanshinone Ⅱ A ， baicalin， cryptotanshinone， calycosin-7- O - β -D-glucoside and ononin may be the marker components that affect the quality of this formula. The overall quality of 11 batches of the Heat-clearing and symptom-relieving formula， including Q17， is relatively superior.

Climate change is altering the Earth's water cycle system. The resulting three extreme weather events—heatwaves, droughts, and extreme precipitation—impacts urban and rural water security through multi-layered mechanisms. A primary structural disparity exists between urban and rural systems: while urban areas benefit from comprehensive and standardized pipe networks that ensure terminal water quality, rural areas often suffer from "last mile" vulnerability due to inadequate infrastructure and outdated purification facilities. Extreme weather can directly alter the microbial community structure, concentrations of chemical pollutants and physicochemical properties of source water. These alterations interfere with the efficiency of water treatment processes and ultimately compromise the integrity of distribution systems. Because distribution networks often lack real-time monitoring and adaptive response capabilities, they have emerged as the most vulnerable link in the "water source-water treatment-distribution system" chain. Based on a systematic analysis of these chain-wide impacts, this paper proposed a series of control strategies, including security frameworks based on multi-model coupling and water source protection measures, improvement of water treatment technologies, optimization of distribution systems, and development of new water quality monitoring methods. These strategies aim to enhance the climate adaptability of urban and rural drinking water systems through multi-dimensional intervention, providing a theoretical basis for constructing climate-resilient water infrastructure.

IgA nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and a major cause of chronic kidney disease and kidney failure. IgAN exhibits marked heterogeneity in clinical presentation, histopathology, and pathogenic mechanisms, contributing to variable treatment responses and prognosisamong patients. Precise risk assessment and individualized intervention are therefore of critical importance. This review systematically traces the evolution of IgAN management from traditional risk stratification toward biomarker-driven precision medicine. We first review the clinical utility and limitations of established risk stratification tools, including the KDIGO guidelines, the Oxford MEST-C classification, and the International IgAN Prediction Tool. We then discuss emerging biomarkers closely linked to disease pathogenesis, including galactose-deficient IgA1 (Gd-IgA1), anti-Gd-IgA1 autoantibodies, B cell activating factor (BAFF), a proliferation-inducing ligand (APRIL), and complement components, as well as the targeted therapies they have informed. In addition, urinary biomarkers and multi-omics approaches show promise for dynamic disease monitoring and individualized risk stratification.

Elderly patients with primary membranous nephropathy (PMN) exhibit significant prognostic heterogeneity and poor tolerance to immunotherapy. However, there is a lack of early prognostic prediction tools specifically for this population. This study aimed to develop a prognostic prediction model applicable to elderly PMN patients.