Objective: To compare the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) model, the Prophet model, and the Bayesian structural time series (BSTS) model in forecasting the incidence of hand, foot, and mouth disease (HFMD) , so as to provide a basis for optimizing the early warning system of this disease. Methods: Weekly incidence data of HFMD in Longgang District, Shenzhen City from 2014 to 2024 were collected. The HFMD incidence data from 2014-2019 and 2023 were used as the training set to construct SARIMA, Prophet, and BSTS models, while the data from 2024 were used as the test set to compare and evaluate the predictive performance of the three models. The technique for order preference by similarity to ideal solution (TOPSIS) method was employed to calculate the C-value. This approach integrates multiple evaluation metrics, such as the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and symmetric mean absolute percentage error (SMAPE), to comprehensively assess model performance. Results: A total of 150 111 cases of HFMD were reported in Longgang District from 2014 to 2024, with an average annual incidence of 400.72/105. The weekly incidence fluctuated between 0 and 63.78/105, exhibiting a bimodal seasonal pattern characterized by a primary peak from May to July and a secondary peak from September to October. In the training set, all three models demonstrated a good fit to the bimodal epidemic trend of HFMD, with the BSTS model achieving the best fit. The BSTS model yielded performance metrics as follows: MAE=0.124, MSE=0.050, RMSE=0.223, SMAPE=0.021, and a C-value of 1.000. In the test set, all three models, including SARIMA, Prophet, and BSTS, performed well for short-term predictions (≤16 weeks), with the Prophet model showing relatively superior predictive performance. However, the prediction accuracy of all models declined as the forecast horizon extended. During the primary peak period (May-July), the Prophet model exhibited better predictive performance, whereas the BSTS model performed relatively better during the secondary peak period (September-October). Conclusions For the short-term forecasting of weekly HFMD incidence, the Prophet model outperformed both the SARIMA and BSTS models. During the primary peak period, the Prophet model demonstrated superior predictive performance, whereas the BSTS model exhibited better accuracy in forecasting the secondary peak period.

ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

ObjectiveTo provide a reference for the rational clinical use of cold Chinese medicines by sorting and analyzing their properties， flavors， meridian tropism， primary therapeutic indications， methods of administration， dosages， and precautions as recorded in the 2020 edition of Pharmacopoeia of the People's Republic of China （Chinese Pharmacopoeia）. MethodsCold Chinese medicines for internal and external use included in the 2020 edition of Chinese Pharmacopoeia were entered one by one， and their efficacy， properties， flavors， meridian tropism， methods of administration， dosages， and usage precautions were statistically classified and summarized to guide clinical medication use. ResultsA total of 259 cold Chinese medicines for internal use were included and categorized into 18 efficacy groups， mainly comprising heat-clearing drugs， water-excreting and dampness-draining drugs， and phlegm-resolving， cough- and asthma-relieving drugs. Their predominant flavors were bitter， sweet， and pungent， and they primarily entered the liver， lung， and stomach meridians. The main methods of administration included decocting first， grinding into powder for oral use， or preparing into pills or powders， with most dosages ranging from 9 to 15 g. A total of 83 cold Chinese medicines for external use were included， involving 16 efficacy categories. Their main flavors were bitter， sweet， and pungent， primarily entering the liver， lung， and large intestine meridians. The main external application methods were grinding into powder for topical use or preparing decoctions for fumigation and washing， with most dosages ranging from 9 to 15 g. Whether for internal or external use， cold Chinese medicines should be used with caution or contraindicated in pregnant women. ConclusionThe cold Chinese medicines included in the 2020 edition of the Chinese Pharmacopoeia are mainly suitable for patients with carbuncles， swellings， and coughs. However， in clinical practice， it is necessary to strictly follow the principles of syndrome differentiation and treatment， pay attention to administration methods and dosages， and use cold medicines rationally and effectively to improve clinical efficacy.

Abnormal activation of the Janus kinase/signal transducer and activator of transcription （JAK/STAT） signaling pathway is involved in the pathogenesis of diffuse large B-cell lymphoma （DLBCL）. In recent years， inhibitors targeting JAK2 and STAT3 have emerged as promising therapeutic candidates in DLBCL. This review summarizes the efficacy and safety profiles of JAK2 inhibitors （e.g.， ruxolitinib） and STAT3 inhibitors （direct small-molecule inhibitors， the antisense oligonucleotide， and proteolysis targeting chimeras， etc.） in preclinical models and clinical trials. Accumulating evidence indicates that JAK2 and STAT3 inhibitors exhibit antitumor activity and are generally well tolerated in a subset of DLBCL patients. Meanwhile， the development of novel drug delivery systems has significantly enhanced the stability， bioavailability， and targeting ability of the compounds. Furthermore， JAK2 and STAT3 inhibitors may exhibit synergistic effects when combined with other therapy strategies （such as combinations with B-cell receptor signaling pathway inhibitors， immunomodulators， or other targeted drugs）. However， current clinical applications are still in their early stages. Future research should concentrate on precision treatment strategies based on the genetic subtyping of DLBCL， and further refine the delivery systems for inhibitors as well as combination drug regimens to improve clinical outcomes.

Objective: To investigate the factors influencing intraoperative blood transfusion in patients with hip fractures and to develop a machine learning (ML) model for predicting this risk. Methods: A total of 424 patients with hip fractures who underwent surgical treatment between November 2022 and March 2025 in our hospital were selected. Key feature variables of intraoperative blood transfusion risk were identified using the Boruta algorithm. Four different ML algorithms—support vector machine (SVM), linear discriminant analysis (LDA), mixed discriminant analysis (MDA), and extreme gradient boosting (XGBoost)—were used to develop predictive models for intraoperative blood transfusion risk. The predictive performance of the four ML models were evaluated using accuracy, precision, receiver operating characteristic (ROC) curves, precision-recall curves (PRC), precision-recall gain curves (PRGC), and F1 scores. Shapley additive interpretation (SHAP) was used to interpret the final model. Results: Among the 424 patients, 77(18.2%) received intraoperative blood transfusion. The Boruta algorithm identified albumin (ALB), activated partial thromboplastin time (APTT), types of anesthesia, types of fracture, and hemoglobin (Hb) as key feature variables for predicting intraoperative blood transfusion risk. In model evaluation, the SVM model outperforms the other three models across multiple metrics, including the area under the receiver operating characteristic curve (AUC), recall, recall gain, accuracy, precision, F1 score, and the area under the precision-recall curve (PRC-AUC). The SVM model, interpreted and visualized based on SHAP values, effectively predicted intraoperative blood transfusion risk in patients with hip fracture. A visual online application was developed based on the SVM model (https://pbo-nomogram.shinyapps.io/blood/). Conclusion: Preoperative low ALB and Hb levels, prolonged APTT, general anesthesia, and intertrochanteric fractures are risk factors for intraoperative blood transfusion in hip fracture patients. The risk prediction model for intraoperative blood transfusion constructed based on the SVM algorithm has optimal performance, which provides new ideas and methods for the clinical early identification of hip fracture patients with high transfusion risk and the implementation of targeted interventions.

Background The global prevalence of obesity is on the rise and is closely associated with various chronic non-communicable diseases such as cardiovascular diseases and diabetes. There is a relative lack of long-term dynamic studies on compound obesity among occupational populations. Objective To explore the changing trends of compound obesity among different occupational groups aged 18–59 years in nine provinces (autonomous regions, municipalities) of China from 1993 to 2018, and to provide a scientific basis for formulating targeted weight management strategies for occupational populations. Methods A total of 34519 employed adults aged 18–59 years from nine waves of the China Health and Nutrition Survey in1993, 1997, 2000, 2004, 2006, 2009, 2011, 2015, and 2018 were included. Obesity types were determined according to the Chinese Adult Weight Management Guidelines. The Joinpoint regression model was used to calculate the average annual percentage change (AAPC) and annual percentage change (APC) of compound obesity rates. Results From 1993 to 2018, the age-standardized compound obesity rate among the occupational population aged 18–59 years showed an upward trend (AAPC=6.24%, 95%CI: 5.09%, 7.41%, P<0.05). The AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, other occupational groups, service workers, and white-collar workers were 9.55% (7.51%, 11.64%), 6.18% (4.70%, 7.69%), 5.53% (2.27%, 8.90%), 4.07% (2.40%, 5.77%), and 3.89% (2.16%, 5.65%), respectively, with statistically significant differences (P<0.05). Among males, the AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, other occupational groups, service workers, and white-collar workers were 11.52% (7.71%, 15.47%), 7.28% (6.18%, 8.40%), 5.92% (2.28%, 9.69%), 5.56% (2.11%, 9.12%), and 4.22% (2.33%, 6.15%), respectively, with statistically significant differences (P<0.05). Among females, the AAPCs (95%CI) for age-standardized compound obesity rates among agricultural workers, blue-collar workers, and white-collar workers were 7.45% (6.22%, 8.69%), 3.72% (0.84%, 6.67%), and 2.41% (0.17%, 4.70%), respectively, with statistically significant differences (P<0.05). A turning point was observed in the compound obesity rate among female white-collar workers in 2006, with an APC (95%CI) of 9.69% (5.24%, 14.33%) from 2006 to 2008, showing a statistically significant difference (P<0.05), while no significant trend was found from 1993 to 2006 (P>0.05). No significant trends were observed in the age-standardized compound obesity rates among females in other occupational groups and service workers (P>0.05). Conclusion The compound obesity rate among China's occupational population is increasing rapidly, with the growth rate among agricultural workers being particularly prominent. In 2018, male white-collar workers and female agricultural workers exhibit relatively high compound obesity rates, warranting focused attention. Although the overall growth rate among service workers is slower, the expanding workforce in this sector indicates that obesity remains a serious issue. Targeted occupational health and weight management interventions are needed in the future.

Background With rising obesity rates and earlier hypertension onset among occupational populations, there is an urgent need to elucidate the long-term cardiovascular impacts of dynamic body weight patterns. Current evidence lacks trajectory modeling studies examining occupation-specific prevention strategies. Objective To investigate the association between long-term body mass index (BMI) trajectories and incident hypertension risk in Chinese working adults, and to examine occupation-specific heterogeneity in this relationship. Methods A dynamic sub-cohort of 4 413 occupational participants was constructed from ten survey waves (1991–2018) of the China Health and Nutrition Survey (CHNS). Eligible individuals had valid key BMI records at three or more independent follow-ups before the outcome event; the individual baseline was set as the year of their first participation in the survey. Group-based trajectory modeling (GBTM) was used to identify BMI change patterns. Cox proportional hazards regression was used to calculate hazard ratios (HRs) and 95% confidence interval (CI) for hypertension incidence across trajectory groups, with stratified analysis by occupational categories. Results Among 4413 occupational participants, 1441 incident hypertension cases were reported during the follow-up window. Three long-term BMI trajectories were identified: low-stable, moderate-slowly rising, and high-rising. In Model 3 with all selected confounders adjusted, compared with the low-stable group, the moderate-slowly rising group showed a significantly higher risk of incident hypertension (HR=1.28, 95%CI: 1.12, 1.45; P < 0.001), as did the high-increasing group (HR=1.80, 95%CI: 1.45, 2.23; P < 0.001). The stratified analyses revealed occupational differences in the association. Among agricultural workers, the moderate-slowly rising group (HR=1.35, 95%CI: 1.15, 1.57) and the high-rising group (HR=2.00, 95%CI: 1.50, 2.66) both exhibited significantly increased risks of hypertension (P<0.001). Conversely, among white-collar workers, an increased risk of hypertension was observed only in the high-rising group (HR=1.97, 95%CI: 1.23, 3.17; P<0.05). Conclusion Rapid BMI escalation constitutes a significant risk factor for incident hypertension in occupational populations. Targeted long-term weight monitoring and tailored interventions are recommended for high-risk occupations.

Objective: To explore the relationship of family function with sleep and externalizing problem behaviors of preschool children, so as to provide a guidance for externalizing problem prevention and intervention among preschool children. Methods: From October 2023 to January 2024, a convenience sampling method was used to select 5 138 preschool children from kindergartens in 8 districts of Wuhan City, Hubei Province. Parents completed the survey for Family Adaptability and Cohesion Scale, children s sleep habits and Child Behavior Checklist (CBCL). Spearman correlation analysis was used to examine the correlation of family function with scores of sleep quality and externalizing problem behaviors among preschool children. A mediation model analysis and bootstrap test were conducted to further investigate the mediating role of sleep quality between family function and externalizing problem behaviors. Mplus 8.7 software was used for latent profile analysis of family function. Results: The reported rates of poor sleep quality and externalizing problem behaviors among preschool children were 11.8% ( n =607), 20.0% ( n =1 026). The relevant analysis results showed that family function was negatively correlated with sleep quality and externalizing problem behaviors ( r = -0.20, -0.23), and sleep quality was positively correlated with externalizing problem behaviors ( r =0.27) ( P <0.01). The mediation effect test showed that family function negatively predicted externalizing problem behaviors ( β =-0.079) and sleep quality ( β = -0.075), while sleep quality positively predicted externalizing problem behaviors ( β =0.215) ( P <0.01). The latent profile analysis results showed that family function could be classified into 4 categories: high family function group (23.01%), upper middle family function group (44.65%), moderate family function group (26.24%) and low family function group (6.11%). Compared to high family function, the other three categories significantly positively predicted externalizing problem behaviors, and the mediating effects of sleep quality on different categories of family function were statistically significant [upper middle family function: mediation effect value was 0.022 (95% CI =0.004-0.041) and direct effect value was 0.329 (95% CI =0.263-0.396); middle family function: mediation effect value was 0.087 (95% CI =0.063-0.115) and direct effect value was 0.491 (95% CI =0.416-0.565); low family function: mediation effect value was 0.144 (95% CI =0.107-0.185) and direct effect 0.621 (95% CI =0.503-0.740)] ( P < 0.05 ). Conclusion Family function negatively predicts the externalizing problem behaviors of preschool children, and sleep quality plays a partial mediating role.

Objective To prepare and characterize caspofungin acetate-loaded solid lipid nanoparticles using glycerol monostearate （CAS-SLNs）, and investigate the antifungal effect of potentiation on Candida albicans in vitro and in vivo. Methods A high performance liquid chromatography method was established for the determination of caspofungin acetate （CAS）. CAS-SLNs were prepared by the melt-emulsification method and characterized. The minimum inhibitory concentration （MIC） and the inhibitory effect on Candida albicans biofilm were determined. A systemic infection model of Candida albicans was established in mice, and the growth curve models for body weight and fungal load of kidneys of the animals were investigated after intravenous infection. Results The retention time of CAS was 6.8 min. The calibration curve showed good linearity, and the precision and stability met the requirements of the assay. Transmission electron microscopy revealed that CAS-SLNs were spherical, with a particle size of （135.97±1.73） nm. The Zeta potential was （19.33±0.37） mV, drug loading was （7.55±0.68）%, and encapsulation efficiency was （67.71±1.74）%. CAS-SLNs showed significant in vitro antifungal inhibition with a MIC of 9.78×10⁻⁴ g/ml, which was significantly better than CAS group and the physical mixture group of CAS and GMS, as well as the same biofilm inhibition was observed （P<0.001）. Pharmacodynamic studies demonstrated that CAS-SLNs maintained stable body weight gain compared to the control （P<0.01） and CAS groups in Candida albicans invasive infection model, and that CAS-SLNs significantly reduced renal fungal burden load relative to the CAS group （P<0.05）. In vivo study revealed that a stable body weight was maintained in CAS-SLNs group compared to the control group （P<0.01） in Candida albicans invasive infection model. CAS-SLNs also significantly reduced renal fungal load compared to the CAS group （P<0.05）. Conclusion CAS-SLNs significantly enhanced the antifungal effects of CAS in vitro and in vivo, which provided a valuable insight for the research of new formulation of CAS.

ObjectiveTo investigate the mechanism of Acanthopanacis Senticosi Radix et Rhizoma seu Caulis extract （ASH） in treating Parkinson's disease （PD） in mice by Data-Independent Acquisition （DIA） proteomics. MethodsThe α-Synuclein （α-Syn） transgenic PD mice were selected as suitable models for PD， and they were randomly assigned into PD， ASH （61.25 mg·kg^-1）， and Madopar （97.5 mg·kg^-1） groups. Male C57BL/6 mice of the same age were selected as the control group， with eight mice in each group. Mice were administrated with corresponding drugs by gavage once a day for 20 days. The pole climbing time and the number of autonomic activities were recorded to evaluate the exercise ability of mice. Hematoxylin-eosin staining was employed to observe neuronal changes in the substantia nigra of PD mice. Immunohistochemistry （IHC） was employed to measure the tyrosine hydroxylase （TH） activity in the substantia nigra and assess the areal density of α-Syn in the striatum. DIA proteomics was used to compare protein expression in the substantia nigra between groups. IHC was utilized to validate key differentially expressed proteins， including Lactotransferrin， Notch2， Ndrg2， and TMEM 166. The cell counting kit-8 （CCK-8） method was used to investigate the effect of ASH on the viability of PD cells with overexpression of α-Syn. Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR） and Western blot were employed to determine the protein and mRNA levels of Lactotransferrin， Notch2， Ndrg2， and TMEM 166 in PD cells. ResultsCompared with the control group， the model group showed prolonged pole climbing time， diminished coordination ability， reduced autonomic activities （P<0.01）， and reduced swelling neurons. Compared with the model group， ASH and Madopar reduced the climbing time， increased autonomic activities （P<0.01）， and ameliorated neuronal damage. Compared with the control group， the model group showed a decrease in TH activity in the substantia nigra and an increase in α-Syn accumulation in the striatum （P<0.01）. Compared with the model group， the ASH group showed an increase in TH activity and a reduction in α-Syn accumulation （P<0.05）. DIA proteomics revealed a total of 464 differentially expressed proteins in the model group compared with the control group， with 323 proteins being up-regulated and 141 down-regulated. A total of 262 differentially expressed proteins were screened in the ASH group compared with the model group， including 85 proteins being up-regulated and 177 down-regulated. Kyoto encylopedia of genes and genomes （KEGG） pathway analysis indicated that ASH primarily regulated the Notch signaling pathway. The model group showed up-regulation in protein levels of Notch2， Ndrg2， and TMEM 166 and down-regulation in the protein level of Lactotransferrin compared with the control group （P<0.01）. Compared with the model group， ASH down-regulated the protein levels of Notch2， Ndrg2， and TMEM 166 （P<0.05） while up-regulating the protein level of Lactotransferrin （P<0.01）. The IHC results corroborated the proteomics findings. The cell experiment results showed that compared with the control group， the modeling up-regulated the mRNA and protein levels of Notch2， Ndrg2， and TMEM 166 （P<0.01）， while down-regulating the mRNA and protein levels of Lactotransferrin （P<0.01）. Compared with the model group， ASH reduced the mRNA and protein levels of Notch2， Ndrg2， and TMEM 166 （P<0.01）， while increasing the mRNA and protein levels of Lactotransferrin （P<0.05， P<0.01）. ConclusionASH may Synergistically inhibit the Notch signaling pathway and mitigate neuronal damage by down-regulating the expression of Notch2 and Ndrg2. Additionally， by up-regulating the expression of Lactotransferrin and down-regulating the expression of TMEM166， ASH can address brain iron accumulation， intervene in ferroptosis， inhibit mitophagy， and mitigate reactive oxygen species damage， thereby protecting nerve cells and contributing to the treatment of PD.