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.

Objective: To explore whether digital facial and tongue diagnostic technologies can support the assessment of coronary heart disease (CHD) patients for coronary artery stenosis severity, and examine potential associations between digital tongue diagnosis features and myocardial biomarkers. Methods: The TFDA-1 face and tongue diagnosis instrument and the TDAS analysis system were used to perform intelligent visual examination and analysis of the facial and tongue in CHD patients who attended the Department of Cardiology at Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine between October 2, 2023 and July 31, 2024. Variables were screened using principal component analysis (PCA) and multicollinearity analysis to construct four machine learning models, including random forest, LightGBM, decision tree, and naive Bayes, for the early prediction of coronary artery stenosis severity. Model performance metrics, including sensitivity, specificity, precision, F1 score, accuracy, and the area under the receiver operating characteristic (ROC) curve (AUC), were evaluated. Visual analyses were performed using the SHapley Additive exPlanations (SHAP) interpreter and decision curve analysis. For patients after percutaneous coronary intervention (PCI), a conceptual model linking cardiac biomarkers and tongue diagnosis was constructed using the partial least squares structural equation modeling (PLS-SEM), and its validity was assessed. Results: A total of 459 CHD patients were enrolled and assigned to a PCI group and a non-PCI group (which comprised two subgroups: mild stenosis or less group, moderate stenosis or greater group). For sublingual vein (SV) features, the PCI group had lower SV-a and SV-b than the other groups (P < 0.01 and P < 0.05, respectively). For tongue surface features, the PCI group had significantly higher tongue body (TB)-L, TB-a, and TB-b (P < 0.05, P < 0.01, and P < 0.001, respectively), as well as higher tongue coating (TC)-a and TC-b (P < 0.01 and P < 0.001, respectively). Age, SV-a, SV-b, creatine kinase-myocardial band (CK-MB), CK, TC-a, lip-L, and lip-b were incorporated in the machine learning models. The random forest model performed best, with an AUC of 0.924, an F1 score of 0.839, precision of 0.807, accuracy of 0.864, sensitivity of 0.873, and specificity of 0.839. Decision curve analysis indicated that both LightGBM and random forest had clinical utility. PLS-SEM confirmed the pathway relationships: myocardial biomarkers → TB and myocardial biomarkers → TC (coefficient = – 0.238, t = 2.239, P = 0.025, and coefficient = – 0.270, t = 2.522, P = 0.012, respectively). Conclusion This study developed a noninvasive early warning model for coronary artery stenosis in patients with CHD. It applied PLS-SEM to investigate the association between post-PCI cardiac biomarkers and tongue diagnosis, and validated the proposed association chain. These findings suggest that intelligent traditional Chinese medicine (TCM) visual diagnosis integrated with modern digital technology may support CHD risk assessment and comprehensive health management.

Objective:To investigate the distribution of health needs and healthcare workforce demands among potential service users in community health service institurions (CHSIs) and establish a comprehensive health needs profile for targeted service development.Methods:This is a cross-sectional study. A questionnaire survey (55 items for adults and 39 items for minors) was conducted among 564 residents aged 3-65 in Dapuqiao Subdistrict, Shanghai from March to May 2024. A health sketch model was developed, encompassing five dimensions (intake, basal metabolism, consumption, influencing factors, and somatosensory perception). Health issues were mapped to standardized healthcare services, and annual standardized workloads (SW) were calculated to quantify human resource demands. Results:Among 534 valid responses (94.68% response rate), 355 from the adults and 179 from minors, the top health issues for adults were irregular diet, nutritional imbalance, obesity, somatic fatigue, and disordered eating; for minors, they were nutritional imbalance, medication overuse, insufficient physical activity, picky eating, and anorexia. The total annual SW required to address these needs was 3 906 807.93. Among them, the total SW for each age group was as follows: the total annual SW demand for children aged between 3 and 5 years old was 24 108.90, for children aged between 6 and 11 years old was 141 355.70, for adolescents aged between 12 and 17 years old was 29 813.74, 223 475.50 for 18-24 year olds, 476 426.53 for 25-34 year olds, 1 221 105.84 for 35-44 year olds, 812 200.22 for 45-54 year olds; and 978 321.50 for 55-65 year olds. Workforce allocation analysis revealed a total demand for 139.84 standardized personnel, with rehabilitation therapists (38.16), general practitioners (35.69), and nurses (27.34) being the top three required roles.Conclusions:Health needs and workforce demands vary significantly across age groups. This study provides a data-driven framework for optimizing community health services through stratified health needs profiling and precision resource allocation. Future strategies should prioritize tailored interventions and workforce planning to bridge service gaps and enhance health outcomes.

Objective:To investigate the descrepancy between current supply and demand based on standardiized workload for rational human resource allocation in community health service centers.Methods:A retrospective study was conducted in Dapuqiao Community Health Service Center of Shanghai Huangpu District from January 1st to December 3lst 2023. The current status of demand and supply were analyzed using the 2023 data of the institution. The standardised workload was measured according to the potential basic medical and public health service needs based on the disease profile and population groups in the community. The discrepancy between the current supply and theoretical demand was analyzed.Results:A total of 36 634 patients paid 277 262 visits in outpatient clinics of Dapuqiao Community Health Service Center in 2023. There are total 161 employees in the center, 124 of whom are female (77.02%). The actual calibrated workload of basic medical care and public health service in the center calculated on fee-based medical service items in 2023 was 2 888 425.61 and 455 898.35, respectively; while the theoretically calibrated workload was 5 416 492.42 and 711 230.94, respectively. The center employed 131 medical and health workers currently, calibrated as 90.67 employees based on current demand, while it should be 183.74 calibrated on the theoretical demand, there was a certain discrepancy between the current staffing and the standard staffing based on the standardized workload calculation.Conclusion:At present, the actual standardized workload of basic medical and public health services in Dapuqiao Community Health Service Center still has room for improvement, but there is a certain gap between the current human resource allocation and the demand.

This consensus was developed by the Orthodontic Society of the Chinese Stomatological Association to provide a systematic, scientific, and practical guideline for informed consent in orthodontic care. Orthodontic treatment is typically lengthy, highly individualized, and involves multiple factors such as growth and development, occlusal function, and facial esthetics. Rapid technological advances and diverse risk profiles make the traditional reliance on orthodontist experience or institutional templates insufficient to ensure patients′ full understanding and autonomous decision-making. To address this, the expert panel conducted extensive reviews of domestic and international guidelines, analyzed representative dispute cases, and performed multicenter patient-clinician surveys. Using a multi-round Delphi method, the group established a standardized informed consent framework covering the initial consultation, treatment, and retention phases. The consensus emphasizes that informed consent is not only a fundamental legal and ethical requirement but also a key step in building trust, improving patient compliance, and enhancing treatment satisfaction. Orthodontists should clearly and comprehensively explain treatment plans, potential risks, uncertainties, and associated costs, while respecting the autonomy of patients or guardians, and maintain continuous communication and dynamic evaluation throughout the treatment process. The release of this consensus provides unified and authoritative guidance for clinical orthodontics, helping to standardize informed consent, enhance its transparency, safeguard patient rights, reduce medical risks, and promote high-quality, sustainable development of orthodontic practice.

Background: Bone cancer pain (BCP) is not adequately addressed by current treatment methods, making the exploration of effective management strategies a topic of significant interest. Bone marrow mesenchymal stem cells (BMSCs) seem to be a potential way for managing BCP, yet little is known about the mechanisms underlying the efficacy of this potential treatment. Methods: We established the male C57BL/6 mice BCP models. Behavioral tests, X-ray, bone histology, western blotting, and immunofluorescence were used to verify the analgesic effect of BMSCs. Results: Intramedullary injection of Lewis lung carcinoma cells into the femur successfully generated the mice BCP models. The number of c-Fos-positive neurons and phosphorylated mitogen-activated protein kinase (MAPK) proteins in the spinal dorsal horn of the BCP mice increased. Intrathecal injection of BMSCs temporarily improved the BCP mice’s mechanical and thermal hyperalgesia without affecting motor function. This effect may be related to inhibiting spinal microglia and p-p38 MAPK activation. The analgesic effect of BMSCs may be related to the homing effect mediated by CXCR4. Conclusions Intrathecal injection of BMSCs can temporarily inhibit mechanical and thermal hyperalgesia in BCP mice without affecting motor function. This effect may be related to the inhibition of p-p38 protein expression and the inhibition of microglia but not to p-ERK and p-JNK.

Background: Bone cancer pain (BCP) is not adequately addressed by current treatment methods, making the exploration of effective management strategies a topic of significant interest. Bone marrow mesenchymal stem cells (BMSCs) seem to be a potential way for managing BCP, yet little is known about the mechanisms underlying the efficacy of this potential treatment. Methods: We established the male C57BL/6 mice BCP models. Behavioral tests, X-ray, bone histology, western blotting, and immunofluorescence were used to verify the analgesic effect of BMSCs. Results: Intramedullary injection of Lewis lung carcinoma cells into the femur successfully generated the mice BCP models. The number of c-Fos-positive neurons and phosphorylated mitogen-activated protein kinase (MAPK) proteins in the spinal dorsal horn of the BCP mice increased. Intrathecal injection of BMSCs temporarily improved the BCP mice’s mechanical and thermal hyperalgesia without affecting motor function. This effect may be related to inhibiting spinal microglia and p-p38 MAPK activation. The analgesic effect of BMSCs may be related to the homing effect mediated by CXCR4. Conclusions Intrathecal injection of BMSCs can temporarily inhibit mechanical and thermal hyperalgesia in BCP mice without affecting motor function. This effect may be related to the inhibition of p-p38 protein expression and the inhibition of microglia but not to p-ERK and p-JNK.

Background: Bone cancer pain (BCP) is not adequately addressed by current treatment methods, making the exploration of effective management strategies a topic of significant interest. Bone marrow mesenchymal stem cells (BMSCs) seem to be a potential way for managing BCP, yet little is known about the mechanisms underlying the efficacy of this potential treatment. Methods: We established the male C57BL/6 mice BCP models. Behavioral tests, X-ray, bone histology, western blotting, and immunofluorescence were used to verify the analgesic effect of BMSCs. Results: Intramedullary injection of Lewis lung carcinoma cells into the femur successfully generated the mice BCP models. The number of c-Fos-positive neurons and phosphorylated mitogen-activated protein kinase (MAPK) proteins in the spinal dorsal horn of the BCP mice increased. Intrathecal injection of BMSCs temporarily improved the BCP mice’s mechanical and thermal hyperalgesia without affecting motor function. This effect may be related to inhibiting spinal microglia and p-p38 MAPK activation. The analgesic effect of BMSCs may be related to the homing effect mediated by CXCR4. Conclusions Intrathecal injection of BMSCs can temporarily inhibit mechanical and thermal hyperalgesia in BCP mice without affecting motor function. This effect may be related to the inhibition of p-p38 protein expression and the inhibition of microglia but not to p-ERK and p-JNK.

Background: Bone cancer pain (BCP) is not adequately addressed by current treatment methods, making the exploration of effective management strategies a topic of significant interest. Bone marrow mesenchymal stem cells (BMSCs) seem to be a potential way for managing BCP, yet little is known about the mechanisms underlying the efficacy of this potential treatment. Methods: We established the male C57BL/6 mice BCP models. Behavioral tests, X-ray, bone histology, western blotting, and immunofluorescence were used to verify the analgesic effect of BMSCs. Results: Intramedullary injection of Lewis lung carcinoma cells into the femur successfully generated the mice BCP models. The number of c-Fos-positive neurons and phosphorylated mitogen-activated protein kinase (MAPK) proteins in the spinal dorsal horn of the BCP mice increased. Intrathecal injection of BMSCs temporarily improved the BCP mice’s mechanical and thermal hyperalgesia without affecting motor function. This effect may be related to inhibiting spinal microglia and p-p38 MAPK activation. The analgesic effect of BMSCs may be related to the homing effect mediated by CXCR4. Conclusions Intrathecal injection of BMSCs can temporarily inhibit mechanical and thermal hyperalgesia in BCP mice without affecting motor function. This effect may be related to the inhibition of p-p38 protein expression and the inhibition of microglia but not to p-ERK and p-JNK.

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.