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.

With the accelerating aging of world population, the prevalence and disease burden of dementia such as Alzheimer's disease is increasing annually. As one of the major risk factors for dementia, air pollution is still an urgent global concern. Studies on the association between ambient particulate matter (PM), one of the major air pollutants, and dementia, such as Alzheimer's disease, are gaining attention. This paper reviewed the current evidence of relevant epidemiological and toxicological studies to illustrate the possible mechanisms underlying the effects of PM exposure on Alzheimer's disease through inflammatory responses, oxidative stress, endocrine disruption, excitatory neurotoxicity, glial cell activation, and intestinal flora disruption, which may provide clues for mitigating the health risks of air pollution and preventing Alzheimer's disease.

Objective To identify long non-coding RNA (lncRNA) associated with rheumatoid arthritis-associated interstitial lung disease (RA-ILD) and investigate their mechanisms. Methods Peripheral blood samples were collected from RA-ILD patients (n＝3), RA patients without lung involvement (n＝3), and healthy controls (n＝3). Next-generation sequencing was performed to screen differentially expressed lncRNA. A human fibrotic lung cell model was established by inducing the MRC-5 cell line with transforming growth factor-β (TGF-β). Following siRNA-mediated knockdown of target genes, changes in inflammatory and oxidative stress-related genes were analyzed via real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). Western blotting and dual-luciferase reporter (DLR) assays were used to validate protein expression, ubiquitination levels, and nuclear translocation of oxidative stress regulators, and antioxidant response element (ARE) transcriptional activity. Rescue experiments were conducted to confirm the role of target lncRNA in oxidative stress and inflammation in fibrotic lung cells. Results High-throughput sequencing revealed significant downregulation of LINC00638 in RA-ILD patients. Knockdown of LINC00638 markedly reduced transcriptional levels of interleukin (IL)-4, nuclear factor erythroid-2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and superoxide dismutase 2 (SOD2), while increasing IL-6, IL-1β, interferon-γ (IFN-γ), and reactive oxygen species (ROS) levels. Furthermore, LINC00638 knockdown decreased Nrf2 protein expression, increased its ubiquitination, reduced nuclear translocation, and suppressed ARE transcriptional activity. In MRC-5 cells, LINC00638 knockdown combined with N-acetylcysteine treatment restored Nrf2 and HO-1 levels while reducing IL-6 expression. Conclusions LINC00638 suppresses inflammatory responses in RA-ILD by activating the Nrf2/ARE antioxidant signaling pathway, suggesting its potential as a therapeutic target for diagnosis and treatment.

ObjectiveTo analyze the influencing factors of pulmonary dysfunction among community-based population at high-risk for chronic obstructive pulmonary disease (COPD), and to establish a risk assessment model to provide a reference basis for accelerating the beforehand prevention and control of COPD and promoting the respiratory health of community-based residents. MethodsIndividuals aged >35 years old, with at least one risk factor except age illustrated in the Guidelines for Primary Diagnosis and Treatment of Chronic Obstructive Lung Disease (2018), and participated in the early screening for COPD from July 2022 to December 2023 were selected as the research subjects, and their lung function was assessed by the forceful expiratory volume in the first second after inhalation of bronchodilator (FEV₁)/ forced vital capacity (FVC) <70% and/or the ratio of FEV₁ to predicted value (FEV₁%Pred) <80% as the diagnostic criteria. In addition, risk factors related to pulmonary dysfunction were analyzed for the establishment of risk assessment model. ResultsA total of 823 individuals aged between 35‒76 years were included, among which 298 (36.21%) were diagnosed with pulmonary dysfunction, 167 (20.29%) with COPD, and 131 (15.92%) with preserved ratio but impaired spirometry. Logistic regression analysis revealed that male gender, increasing age, more frequent smoking, insufficient physical activity, recurrent wheezing, the presence of post-exercise wheezing or coughing, insensitive to airborne allergens, and history of chronic bronchitis or bronchial asthma were correlated with pulmonary dysfunction. The incidence rate of pulmonary dysfunction was 1.99 times higher in males than that in females, 1.81 times more common in those aged between 70‒76 years than those aged <60 years, 2.42 times more common in those who smoked 50‒200 pack-years than in those who smoked 0‒14 pack-years, 1.78 times higher in those who underwent physical activity <600 MET‑min·week^-1 than in those who underwent physical activity ≥600 MET‑min·week^-1, 2.61 times higher in those suffered recurrent wheezing than in those did not, 1.53 times higher in those with symptoms of post-exercise wheezing or coughing than in those without, 1.61 times higher in those insensitive to airborne allergens than those sensitive, 2.02 times higher in patients with chronic bronchitis than in those without, and 2.41 times higher in patients with bronchial asthma than in those without. The risk assessment model for pulmonary dysfunction constructed on this basis had a total score of 28 points, and the area under the subject operating characteristic (ROC) curve was 0.72, reaching the cut-off point of ROC curve while taking scores ≥10 points as the cut-off value for pulmonary dysfunction. ConclusionIn community-based high-risk COPD population, the incidence rate of pulmonary dysfunction is higher in males than that in females, in addition, which increases with the advancement of age. Smoking,insufficient physical activity,recurrent wheezing,post-exercise wheezing or coughing,insensitive to airborne allergens,and history of chronic bronchitis or bronchial asthma are high risk factors for pulmonary dysfunction. The risk assessment model constructed based on these factors has a good predictive effect in screening high-risk population of COPD, but its effectiveness in screening people at general risk needs to be further validated.