This paper has constructed a traditional Chinese medicine （TCM） specialized disease dataset platform for mixed hemorrhoids based on a multimodal large model， and the preliminary application has been validated. The platform uses StarRocks to establish a four-level data warehouse system， enabling the aggregation， cleaning， and standardization of multi-source heterogeneous data. Using DeepSeek-R1-Distill-Qwen-7B as the base model， domain fine-tuning is performed through low-rank adaptation （LoRA） technology. Combined with LLaMA-3.3 natural language processing and reasoning chain techniques， the platform enables intelligent parsing and structured extraction of unstructured TCM medical records. It accurately identifies six major categories and 28 subcategories of entities， including symptoms and syndromes， with a fine-tuned model F1 score of 93.8%. The platform has established a high-quality specialized disease dataset containing more than 50,000 medical records and has been applied in a real-world study involving 17,831 patients， preliminarily verifying the efficacy of TCM heritage surgery.

Metabolic dysfunction-associated fatty liver disease （MAFLD） has become the most common chronic liver disease worldwide. Its pathological process is centered on the “two-hit” theory， with gut-liver axis dysregulation running through the entire disease course from steatosis to liver cirrhosis and even hepatocellular carcinoma， and it forms an extensive cross-system regulatory mechanism with the metabolic， cardiovascular， renal， and psychological and nervous systems through multi-dimensional pathways such as the “gut-liver-brain axis”， the “liver-kidney axis”， and the “liver-heart axis”. Disease progression is not limited to the liver itself， and it also involves functional imbalance of multiple organ systems throughout the body. This article systematically elaborates on the association mechanism of “liver pathological progression-multi-axis regulation-comorbidity occurrence” in MAFLD， proposes synergistic management strategies integrating early screening based on risk stratification， targeted intervention， and multidisciplinary diagnosis and treatment， and analyzes the limitations of current research and future development directions， in order to provide a theoretical basis and practical guidance for precise diagnosis and treatment and individualized management of MAFLD.

Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.

Objective To explore the association of diabetes status with the development of tuberculosis (TB) among the community population in Shanghai, and to provide evidence for the formulation of tuberculosis prevention and control strategies. Methods This population-based cohort study was based on Shanghai Suburban Adult Cohort and Biobank (SSACB) in China. The baseline data were acquired by questionnaires, physical examinations and blood biochemistry tests. TB incidence was obtained by matching with TB management information system data. A Cox proportional risk model was established to assess the risk of tuberculosis. Results A total of 36 014 research subjects were included, with an average age of 56.3±11.3 years, of which 14 587 (40.5%) were male. Over 6 years of follow-up, 47 individuals progressed to tuberculosis (incidence rate: 19.8 per 100 000 person-year, 95% CI: 14.6 -26.4). An increased risk of TB was observed in participants with newly diagnosed diabetes compared with those without diabetes (adjusted hazard ratio [aHR], 2.73; 95% CI, 1.19 - 6.28). Conclusion The risk of tuberculosis in newly diagnosed diabetic patients is significantly increased, and strengthening tuberculosis screening for this population should be considered in practical work.

Objective To study the spatial distribution of the incidence of pulmonary tuberculosis in Hubei Province and its influencing factors, so as to improve the theoretical basis for scientific development of tuberculosis prevention and control measures in the future. Methods The data of reported incidence of tuberculosis and related influencing factors in various counties and districts of Hubei Province in 2020 were collected. Global Moran's I index, hotspot analysis and geographically weighted regression (GWR) model analysis were used to calculate the spatial autocorrelation of the incidence of tuberculosis, and to analyze the influencing factors affecting the incidence rate of tuberculosis. Results There were obvious regional differences in the space distribution of the incidence rate of tuberculosis. Hot spot analysis showed positive spatial correlation and obvious clustering. The GWR model (AICc=784.251) in this study had higher AICc value compared to the ordinary least squares regression (OLS) model (AICc=804.2585). The GWR model showed that the increase in the proportion of the population aged 65 and above and the proportion of the ethnic minority population had a significant promoting effect on the increase of the incidence rate of tuberculosis, and there was significant spatial heterogeneity. The effect of PM_2.5 concentration on the incidence rate of pulmonary tuberculosis varied in different regions, and the degree of effect was also different. Conclusion The proportion of people aged 65 and above and the proportion of ethnic minorities may significantly influence the incidence of pulmonary tuberculosis. The effect of PM_2.5 concentration varies in different regions, so targeted measures should be formulated according to the situation in different regions.

Objective To explore the impact of mindful diet intervention on dietary behaviors,body composition,and mindfulness levels in overweight/obese children.Methods A total of 74 over-weight/obese children who sought treatment at a tertiary-level hospital in Hunan Province were selected as study subjects.They were randomly divided into experimental group and control group using the random number table method,with 37 cases in each group.The control group implemented a conven-tional body weight management program,while the experimental group received mindful diet interven-tion in addition to the conventional program.Changes in body mass index(BMI),body fat percent-age,visceral fat area,dietary behaviors,and mindfulness levels were compared between the two groups before and after intervention.Results Before intervention,there were no statistically signifi-cant differences in general information,body composition,dietary behaviors,and mindfulness levels between the two groups(P＞0.05).After 8 weeks of intervention,the BMI,body fat percentage,and visceral fat area of children in both groups were lower than those before intervention.The scores for e-motional diet,restrictive diet,and external diet were also lower than those before intervention,while the mindfulness levels were higher than those before intervention,with statistically significant differ-ences(P＜0.05).The experimental group showed better results than the control group in terms of BMI,body fat percentage,visceral fat area,scores for emotional diet,restrictive diet,and external di-et,as well as mindfulness levels(P＜0.05).Conclusion Mindful diet intervention can effectively improve dietary behaviors,reduce body fat percentage and visceral fat area,and enhance mindfulness levels in overweight/obese children.

Objective The ketogenic diet(KD)is a dietary intervention with potential therapeu-tic effects on polycystic ovary syndrome(PCOS),yet the existing evidence remains controversial.Fur-thermore,there is a lack of evidence-based medicine data for a comprehensive assessment of the safety of KD in the treatment of PCOS.This study aims to systematically evaluate,through a meta-analysis,the effects of KD on body composition,metabolic indicators,and reproductive hormone levels in over-weight/obese patients with PCOS,and to explore its safety and clinical applicability.Methods This study systematically searched PubMed,Web of Science,Embase,Cochrane Library,China National Knowledge Infrastructure(CNKI),Wanfang Database,and VIP Database.Randomized controlled trials(RCT)on KD for the treatment of PCOS were included,with the search time frame spanning from the establishment of each database to May 31,2025.Two researchers independently screened and extracted data according to inclusion and exclusion criteria,and assessed the quality of the in-cluded literature using the Cochrane Handbook.The Q-test and inconsistency index(I2)were used to evaluate the heterogeneity of the results.Based on the level of heterogeneity,a fixed-effects model or a random-effects model was selected for data pooling.Sensitivity analysis was employed to explore the robustness of the results.Results A total of 7 RCT studies involving 495 overweight/obese subjects were included in this study.Body composition analysis revealed that,compared with the control group,KD significantly reduced body mass index,body weight,waist circumference,waist-to-hip ra-tio,total fat mass,and visceral fat area in overweight/obese patients with PCOS(P＜0.05),but had no significant effect on fat-free mass.Analysis of glucose and lipid metabolism indicated that KD sig-nificantly decreased fasting blood glucose,fasting insulin,insulin resistance index,and triglycerides(P＜0.05),but had no significant impacts on total cholesterol,low-density lipoprotein cholesterol,or high-density lipoprotein cholesterol.Reproductive hormone analysis showed that KD significantly reduced luteinizing hormone,the ratio of luteinizing hormone to follicle-stimulating hormone,and total testosterone levels,while significantly increased sex hormone-binding globulin levels(P＜0.05),but had no significant effect on follicle-stimulating hormone.Sensitivity analysis suggested that the results were relatively robust.In terms of safety,no serious adverse reactions were observed during the KD intervention;however,further verification through high-quality RCTs with larger sample sizes and long-term interventions is still required.Conclusion KD can effectively improve body composition,glucose metabolism,lipid metabolism indicators,and reproductive hormone levels in overweight/obese patients with PCOS.This study confirms that KD significantly increase sex hormone-binding globulin level and reduce visceral fat area.It is found that KD has a more pronounced effect on impro-ving triglycerides compared to its effects on low-density lipoprotein cholesterol and high-density lipo-protein cholesterol.The current evidence does not indicate significant safety risks associated with KD,but relevant conclusions still require further confirmation with more high-quality evidence.

Objective : To investigate the mechanism of action of benvitimod (BVM) in the treatment of atopic der- matitis (AD) . Methods : HaCaT cells were stimulated by TNF-α and IFN-γ , and the cells were grouped into NC group , TNF-α/IFN-γ group , TNF-α/IFN-γ BVM group , and TNF-α/IFN-γ BVM ML385 group. The AD model of DNCB-induced Balb/c mice was divided into CON group , DNCB group , DNCB + BVM group , and DNCB + TAC group. The efficacy of BVM and its roles in antioxidant and pyroptosis regulation were evaluated. Results: Compared with the control group , BVM inhibited the inflammatory response of HaCaT cells stimulated by TNF-α and IFN-γ , and ameliorated the skin lesions and inflammation in the DNCB-induced AD mouse model ; at the same time , it significantly increased the expression of nuclearfactorerythroid-2-relatedfactor2 (NRF2)-related anti-oxida- tive stress proteins , and significantly reduced the expression of cellular reactive oxygen species (ROS) levels and pyroptosis proteins. At the same time , the levels of NRF2-related antioxidative stress proteins significantly in- creased , and the levels of ROS and pyroptosis proteins significantly decreased. Conclusion BVM activates the NRF2/ROS/NLRP3 pathway to inhibit pyroptosis , thereby reducing the inflammatory response in AD.

Objective : To analyze the epidemiological characteristics of tuberculosis in Urumqi and assess the im⁃pact of the national health examination policy , as well as COVID⁃19 prevention and control measures , on tuberculo⁃sis incidence in Xinjiang. Methods: The seasonal patterns of pulmonary tuberculosis were examined using the seasonal index method and circular distribution analysis. An Interrupted Time Series (ITS , Interrupted Time Series) model was employed to investigate how the national health examination policy and COVID_19 interventions influenced trends in tuberculosis incidence in Urumqi. Results: From 2013 to 2021 , a total of 19 ,049 cases of tuberculosis were reported in Urumqi. The peak incidence day occurred on May 25th , indicating a consistently high rate throughout the year, particularly during spring and summer months. The results of the interrupted time series model indicated that the initial monthly incidence rate of pulmonary tuberculosis in Urumqi was 5. 05 per 100 ,000. From January 2013 to September 2016 , the incidence rate of pulmonary tuberculosis showed a slow upward trend , and the upward trend was significant (β1 = 0. 039 ,P < 0. 05) . After the implementation of the universal health checkup policy , the incidence rate of pulmonary tuberculosis showed a slow downward trend , and the downward trend was significant(β3 = - 0. 109 ,P < 0. 05) . After the outbreak of the COVID_19 epidemic in January 2020 , the incidence rate of pulmonary tuberculosis in Urumqi first dropped rapidly and then entered a slow upward stage , and the upward trend was significant(β5 = 0. 082 , P < 0. 05) . Conclusion It is recommended that public health authorities prioritize timely identification of potential TB patients during periods with elevated incidence rates observed in spring and summer months. While significant progress has been made through implementing national health examinations policies , attention must be directed towards understanding how ongoing epidemics affect TB patient detection. Thus , enhancing surveillance efforts and intervention strategies are essential in adapting to this new normal. Key words tuberculosis ; seasonal index method ; circular distribution method ; national health examination ; COVID_19 ; interruption time series

Objective:To assess common errors in head and neck CT angiography (CTA) image reports using four types of large language models (LLM), namely GPT-4, DeepSeek, ERNIE Bot and SparkDesk, and to assess the feasibility of using existing LLMs to support quality control of radiology reports in Chinese.Methods:The study was a cross-sectional study. Totally 1 000 head and neck CTA image reports were randomly selected using the simple random sampling method from Xuanwu Hospital, Capital Medical University in 2023, including 500 primary reports and 500 finalized reports. Two radiologists collaboratively identified six types of errors in the reports: description errors, writing errors, left-right confusion errors, diagnostic omissions, logical sequence errors, and other errors. The overall quality of the reports was assessed using a 5-point Likert scale. Subsequently, GPT-4, DeepSeek, ERNIE Bot and SparkDesk models were employed to detect the same six types of errors in the imaging reports and to provide overall scoring. The results from manual review were considered the gold standard for calculating F1 score to evaluate model performance. Intra-class correlation coefficients ( ICC) were used to assess the consistency between manual scores and the overall scores from the four LLMs. Results:In the primary imaging reports, the proportions of manually detected errors were as follows: descriptive errors 2.6% (13/500), writing errors 0.6% (3/500), left-right confusion errors 0, diagnostic omissions 6.4% (32/500), logical sequence errors 5.2% (26/500), and other errors 0. In the finalized imaging reports, the proportions of errors across the six categories were 0.2% (1/500), 0, 0, 0, 0, and 0.2% (1/500), respectively. For error detection in the primary imaging reports, the F1 scores of GPT-4 for the six error types were 0.992, 0.997, 0.997, 0.967, 0.980, and 0.992, respectively. DeepSeek achieved F1 scores of 0.980, 0.955, 0.981, 0.920, 0.995, and 0.960; ERNIE Bot scored 0.982, 0.990, 1.000, 0.956, 0.976, and 0.999; and SparkDesk achieved 0.985, 0.995, 1.000, 0.961, 0.982, and 1.000. In the detection of errors in finalized imaging reports, GPT-4′s F1 scores were 0.994, 0.995, 0.998, 0.973, 0.989, and 0.993; DeepSeek scored 0.968, 0.965, 0.985, 0.971, 0.991, and 0.983; ERNIE Bot achieved 0.996, 0.992, 1.000, 0.983, 0.999, and 0.997; and SparkDesk achieved 0.999, 0.999, 1.000, 1.000, 1.000, and 0.999. The consistency between GPT-4, DeepSeek, and SparkDesk models and human ratings was moderate, with ICC values of 0.514, 0.560, and 0.515 respectively (all P0.001); in contrast, the overall score of ERNIE Bot showed poor consistency with human ratings, with an ICC of 0.221 ( P0.001). Conclusion:LLMs demonstrate high accuracy in detecting errors in head and neck CTA imaging reports. The overall scoring of report quality shows moderate consistency with manual assessments, indicating a certain feasibility for automated quality control in reporting.