ObjectiveTo study the effect of Bufei Tongbi decoction on pulmonary fibrosis in diabetic rats via the transforming growth factor-β₁ （TGF-β₁）/phosphorylated Smad family member 3 （p-Smad3） signaling pathway. MethodsStreptozotocin （60 mg·kg^-1） and bleomycin （24.80 U·kg^-1） were used to prepare the rat model of diabetes with pulmonary fibrosis by intratracheal injection. Sixty rats were randomly assigned into blank， model， low-， medium-， and high-dose （3.98， 7.95， and 15.90 g·kg^-1， respectively） Bufei Tongbi decoction， and pirfenidone （0.36 mg·kg^-1） groups （n=10）. The successfully modeled rats in each group were administrated with corresponding agents once per day for four consecutive weeks. After drug administration， fasting blood glucose and lung function indicators were measured. Chemical immunoassay was employed to determine the serum levels of hydroxyproline （Hyp）， hyaluronic acid （HA）， and laminin （LN）. The lung index was determined by the wet and dry methods. The pathological changes in the lung tissue were observed by hematoxylin-eosin （HE） staining， and the degree of fibrosis was detected by Masson staining. The mRNA and protein levels of TGF-β₁， p-Smad3， Smad3， α-smooth muscle actin （α-SMA）， collagen type Ⅰ alpha 1 （Col1A1）， and fibronectin were determined by PCR and Western blotting， respectively. ResultsCompared with the blank group， the model group showed alveolar septa thickening， obvious thickening of the basement membrane of pulmonary blood vessels， severe destruction of the alveolar structure， structural disarrangement of the lung parenchyma， and an increase in the proportion of inflammatory cell infiltration in the lung tissue， together with a large amount of blue collagen deposition and a large amount of collagen fibroplasia in the bronchial wall， vessel wall， interstitium， and alveolar wall， which indicated severe fibrosis. Bufei Tongbi decoction groups and the pirfenidone group showed lower fasting blood glucose level （P<0.05） and higher forced vital capacity （FVC）， cytoplasmic dynein （Cydn）， FEV_0.3/FEV ratio， and lung index （P<0.05） than the model group. Moreover， these groups demonstrated alleviated lung fibrosis， elevated Hyp， HA， and LN levels， down-regulated mRNA levels of α-SMA， Col1A1， and fibronectin， and down-regulated protein levels of TGF-β₁， Smad3， p-Smad3， α-SMA， Col1A1， and fibronectin （P<0.05）. ConclusionBufei Tongbi decoction can inhibit pulmonary fibrosis in diabetic rats by inhibiting the TGF-β₁/p-Smad3 signaling pathway.

[Objective] To evaluate the feasibility of a novel outpatient infusion model for blinatumomab in two acute lymphoblastic leukemia (ALL) patients, aiming to address challenges of poor treatment tolerance, high healthcare costs, and compromised quality of life, thereby providing clinical insights for broader adoption of this approach. [Methods] Two post-allogeneic hematopoietic stem cell transplantation (allo-HSCT) patients undergoing blinatumomab maintenance therapy were selected to evaluate the efficacy of the outpatient infusion model. Patient selection criteria, nursing protocols, standardized workflows, and advancements in infusion practices were systematically analyzed combined with a review of global developments in this field. [Results] Both patients completed outpatient blinatumomab infusion without severe adverse events, demonstrating preliminary feasibility and safety of this model. The novel approach enhanced treatment convenience, reduced hospitalization costs, and improved quality of life. [Conclusion] Despite the limited sample size, this pilot study highlights the potential of outpatient blinatumomab administration as a viable alternative to traditional inpatient regimens.

OBJECTIVE To study the safety of Shuangshu decoction in rats and its efficacy in improving functional dyspepsia （FD） in rats. METHODS In safety test， 40 rats were divided into blank control group， Shuangshu decoction low-dose， medium- dose and high-dose groups [108， 216， 324 g/（kg·d）， calculated by raw medicine， the same applies below]； they were given relevant medicine intragastrically， for continuous 14 days. The mortality and toxic reactions of rats were recorded， and the organ indexes of the liver， kidney， spleen， lung and heart of rats were calculated； the pathological morphological changes in the liver， kidney， spleen， lung， heart， stomach， duodenum， and colon were observed to evaluate the acute toxicity of Shuangshu decoction. Another 40 rats were grouped and administered in the same way for 30 consecutive days. The mortality and toxic reactions of the rats were recorded， and the corresponding organ indexes were calculated. The pathological morphological changes in the corresponding organs were observed， and blood routine and serum biochemical indicators were measured， in order to assess the subacute toxicity of Shuangshu decoction. In pharmacodynamic experiments: 50 rats were divided into blank control group， model group， and Shuangshu decoction low-， medium-， and high-dose groups （9.45， 18.9， 37.8 g/kg）， with 10 rats in each group. Except for blank control group， rats in all other groups were used to establish the FD rat model by subcutaneous injection of loperamide （3.5 mg/kg）. Rats in each group were administered the corresponding drug solution/normal saline intragastrically， once a day， for 14 consecutive days. After the last medication， fecal moisture content， intestinal propulsion rate， gastric emptying rate and serum level of motilin were all detected， and interstitial cell of Cajal （ICC） ultrastructure of rats was observed in colon tissue. RESULTS The safety experiments showed that no death occurred in each dose group， and no significant difference was found in organ coefficient， routine blood and serum biological index， compared to blank control group （P＞0.05）； no abnormality was found in organ appearance and pathological sections. The results of the pharmacodynamic experiments showed that， compared with the blank control group， the fecal moisture content， gastric emptying rate， intestinal propulsion rate， and serum motilin levels in the model group were significantly decreased （P＜0.05）； in the colonic tissue， the mitochondria in the ICC exhibited severe swelling with the disappearance of cristae， and the endoplasmic reticulum was dilated. Compared with model group， the rats in Shuangshu decoction high-dose group showed significant increases in the above quantitative indicators （P＜ 0.05）； additionally， there was a large number of mitochondria in the ICC of the colonic tissue， with clear cristae and regular arrangement. CONCLUSIONS Shuangshu decoction is safe and has a beneficial improving effect on FD rats； its mechanism of action may be related to the regulation of gastrointestinal hormone expression to promote gastric emptying and intestinal propulsion， as well as the repair of mitochondrial structure in ICCs to restore gastrointestinal function.

Objective: To explore the relationship between school sports environment and physical activity levels of middle school students, so as to provide theoretical and empirical support for optimizing school sports environment and enhance adolescent physical activity. Methods: Using multi-stage random cluster sampling, from September to December 2023, 1 329 junior and senior high school students from Xuancheng City of Anhui Province, Lianyungang City of Jiangsu Province, Wuhan City of Hubei Province, Qiqihar City and Suihua City of Heilongjiang Province, and Shenzhen City of Guangdong Province were selected. The International Physical Activity Questionnaire-Short Form (IPAQ-SF) assessed students physical activity levels, and the questionnaire on the characteristics of school sports environment was developed to evaluate the factors of school sports environment. Multivariate ordered Logistic regression was performed to analyze the correlation between school sports environment factors and physical activity levels, and the analytic hierarchy process determined the weight of key influencing factors. Results: The results showed that weekly vigorous physical activity time was [60 (25, 90)] minutes, moderate physical activity time was [60 (30, 90)] minutes, light physical activity time was [105 (40, 200)] minutes, and sedentary behavior time was [ 3 300 (2 100, 4 500)] minutes, only 10.53% of the students met World Health Organization physical activity recommendations, and 89.69% of the students averaged >8 h daily sedentary time. Multivariate ordered Logistic regression showed that adequate sports equipment significantly promoted physical activity across all intensities and reduced sedentary time ( OR = 4.97, 11.54, 4.03, 0.11); diverse sports activities improved vigorous and moderate physical activity while reducing sedentary time ( OR =4.20, 14.06, 0.17); and peer encouragement was associated with increased low-intensity physical activities and decreased sedentary time ( OR =10.40, 0.15)( P <0.05). The analytic hierarchy process weighting analysis identified the top three influential factors related to physical activity among middle school students: sufficient sports equipment, varied physical education activities, frequent peer encouragement, the influence weight accounts for 23.55% , 14.18% and 11.77% of the total, respectively. Conclusion Key school sports environmental factors for adolescent physical activity level include ensuring adequate sports equipment and class availability, diversifying activity content, fostering peer support, and cultivating an active sports culture and a comprehensive approach encourage students participation in extracurricular physical activities.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: To analyze the distribution characteristics of fluoride and trichloromethane in drinking water in rural schools in Guizhou Province and assess their health risks, so as to provide a scientific basis for ensuring the safety of drinking water in rural schools. Methods: During the dry season (March to May) and wet season (July to September) of 2020 to 2022, 788 rural primary and secondary schools in agricultural counties (districts) in Guizhou Province were selected for investigation by using a direct sampling method. A total of 1 566 drinking water samples were collected from these schools, and the mass concentrations of fluoride and trichloromethane in the water samples were detected. The Mann-Whitney U test was used for intergroup comparison, and a health risk assessment model was employed to evaluate the health risks of students oral intake of fluoride and trichloromethane. Results: From 2020 to 2022, the mass concentrations of fluoride and trichloromethane in the drinking water of rural schools in Guizhou Province all met the standards, and the ranges were no detection to 0.99 mg/L and (no detection to 0.06)×10 -3 mg/L, respectively. The mass concentrations of fluoride in dry and wet seasons were 0.05(0.05,0.10), 0.05(0.05,0.10) mg/L, the mass concentrations of trichloromethane were [0.02(0.02,1.00)]×10 -3 , [0.02(0.02,1.00)]×10 -3 mg/L, the mass concentrations of fluoride in factory water and terminal water were 0.05(0.05,0.05), 0.05(0.05,0.10) mg/L, and the differences were not statistically significant ( Z=-0.04, -0.88, - 0.98 , P >0.05). There was a statistically significant difference in the mass concentration of trichloromethane between factory water and peripheral water [0.02(0.02,0.02)×10 -3 , 0.02(0.02,1.05)×10 -3 mg/L]( Z=-2.16, P < 0.05 ). The non-carcinogenic risk assessment values for students oral exposure to fluoride and trichloromethane were in the range of 0.01(0.01,0.03)-0.03(0.03,0.06) and [0.26( 0.26 ,14.54)]×10 -4 -[0.52(0.52,48.62)]×10 -4 , respectively, all of which were at acceptable levels; the carcinogenic risk assessment values for oral exposure to trichloromethane were in the range of [0.08(0.08, 4.51 )]×10 -7 -[0.16(0.16,15.07)]×10 -7 , indicating a low risk. Conclusions The health risks of students expore to fluoride and trichloromethane in drinking water in rural schools of Guizhou Province are low. It is necessary to strengthen the standardized management of disinfection in some rural drinking water projects and the monitoring of fluoride in water sources to reduce the exposure risk to children.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Metabolites produced as intermediaries or end-products of microbial metabolism provide crucial signals for health and diseases, such as metabolic dysfunction-associated steatotic liver disease (MASLD). These metabolites include products of the bacterial metabolism of dietary substrates, modification of host molecules (such as bile acids [BAs], trimethylamine-N-oxide, and short-chain fatty acids), or products directly derived from bacteria. Recent studies have provided new insights into the association between MASLD and the risk of developing chronic kidney disease (CKD). Furthermore, alterations in microbiota composition and metabolite profiles, notably altered BAs, have been described in studies investigating the association between MASLD and the risk of CKD. This narrative review discusses alterations of specific classes of metabolites, BAs, fructose, vitamin D, and microbiota composition that may be implicated in the link between MASLD and CKD.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.