ObjectiveTo observe the clinical efficacy of Sanren Runchang formula in treating constipation-predominant irritable bowel syndrome （IBS-C） by regulating the brain-gut axis and the effects of the formula on serum levels of 5-hydroxytryptamine （5-HT）， vasoactive intestinal peptide （VIP）， and substance P （SP）. MethodsA randomized controlled design was adopted， and 72 IBS-C patients meeting Rome Ⅳ criteria were randomized into observation and control groups （36 cases）.The observation group received Sanren Runchang formula granules twice daily， and the control group received lactulose oral solution daily for 4 weeks. IBS Symptom Severity Scale （IBS-SSS）， IBS Quality of Life Scale （IBS-QOL）， and Bristol Stool Form Scale （BSFS） were used to assess clinical symptoms， and bowel movement frequency was recorded. The Self-Rating Anxiety Scale （SAS） and Self-Rating Depression Scale （SDS） were employed to evaluate psychological status. ELISA was employed to measure the serum levels of 5-HT， VIP， and SP. ResultsThe total response rate in the observation group was 91.67% （33/36）， which was higher than that （77.78%， 28/36） in the control group （χ²=4.50， P<0.05）. After treatment， both groups showed increased defecation frequency and BSFS scores， decreased IBS-SSS total score， abdominal pain and bloating scores， IBS-QOL health anxiety， anxiety， food avoidance， and behavioral disorders scores， SAS and SDS scores， serum 5-HT and VIP levels， and increased SP levels （P<0.05， P<0.01）. Moreover， the observation group showed more significant changes in the indicators above than the control group （P<0.05， P<0.01）. The SP level showed no significant difference between the two groups. During the 4-week follow-up， the recurrence rate was 5.88% in the observation group and 31.25% in the control group. No adverse events occurred in observation group， and 2 cases of mild diarrhea occurred in the control group. ConclusionSanren Runchang formula demonstrated definitive efficacy in alleviating gastrointestinal symptoms and improving the psychological status and quality of life in IBS-C patients， with a low recurrence rate. The formula can regulate serum levels of neurotransmitters such as 5-HT and VIP， suggesting its potential regulatory effect on the brain-gut axis through modulating neurotransmitters and neuropeptides. However， its complete mechanism of action requires further investigation through detection of additional brain-gut axis-related biomarkers.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.

OBJECTIVE To explore comprehensive management and potential issues associated with long-term prescriptions medications of psychiatry， in order to provide a reference for the comprehensive management of long-term prescriptions of psychiatry in psychiatric hospitals and other medical institutions’ pharmacies. METHODS Starting from the applicable principles for long-term prescriptions of psychiatry， this study introduced the standardized assessment and precautions before issuing long-term prescriptions， the formulation and adjustment of the drug list， as well as the rational management of the long-term prescriptions. It also analyzed potential issues that may arise in the comprehensive management of long-term prescription medications and proposed corresponding countermeasures and suggestions. RESULTS & CONCLUSIONS Prior to initiating long-term prescriptions， a standardized assessment should be conducted on patients from the aspects of their psychiatric condition and long-term potential risk factors， pharmacological treatment plans and other non-pharmacological therapies， physical illnesses. Additionally， healthcare providers should fulfill their obligation to inform patients or their family members. The comprehensive management of long-term prescription medications should be jointly established and improved by multiple departments， and the formulation of drug catalogs should avoid including drugs with potential social harm or medication risks while complying with policy requirements. Furthermore， measures such as adding special identifiers to long-term prescriptions， providing patients with reminders about （No.YGLX202537） prescription expiration， or offering online consultations can also effectively enhance the rationality of medication use under long-term prescriptions. Currently， the implementation of long-term prescriptions in psychiatry remains challenged by inconsistencies in prescription duration， incomplete coverage of diagnostic categories， poor patient adherence， and the risk of deviation in clinical assessments. In this regard， measures such as collaborating with multiple departments to strengthen long-term prescription information management， providing matching pharmaceutical services， ensuring the quality and rationality of long-term prescription implementation， and using modern methods to screen high-risk patients can be taken to improve patient medication compliance and safety.

This study applies a PEST-SWOT hybrid analysis framework to address key challenges in promoting the"In-ternet Plus"full-process management model for mental disorders.Key issues include the imbalance in service resource distribu-tion between urban and rural areas,insufficient effectiveness of digital technologies,and the lack of coordinated multi-stakeholder mechanisms.By analyzing macro-environmental factors,such as policy,economy,society,and technology,alongside internal strengths,weaknesses,opportunities,and threats,the study underscores the significant advantages and challenges of implemen-ting the"Internet Plus"model in mental disorder management.To achieve better promotion outcomes,it is crucial to enhance le-gal and policy frameworks,strengthen technological innovation,optimize service delivery models,and establish collaborative mechanisms among stakeholders.

Objective:To investigate the status of psychological distress, self-compassion, and self-management behaviors among patients with type 2 diabetes mellitus (T2DM), and explore the mediating role of self-compassion in the relationship between diabetes distress and self-management behaviors, and to provide a theoretical basis for the psychological intervention of patients with T2DM.Methods:A convenience sampling method was adopted to select 221 patients with T2DM hospitalized in the Department of Endocrinology and Metabolism, the First Hospital of China Medical University from November 2023 to April 2024. The General Information Form, the Diabetes Distress Scale-17, the Self-Compassion Scale and the Summary of Diabetes Self-Care Activity were utilized for investigation. A structural equation model was constructed with AMOS 24.0 to analyze the relationships among psychological distress, self-compassion, and self-management behaviors, and the mediating effect of self-compassion was tested using the Bootstrap method.Results:A total of 221 patients with T2DM were included, including 138 males and 83 females, aged (54.52 ±10.42) years old. The total score of psychological distress of patients with T2DM was (34.55 ± 18.82) points, the total score of self-compassion was (94.22 ± 26.04) points, and the total score of self-management behavior was (40.81 ± 22.64) points. Psychological distress in T2DM patients was significantly negatively correlated with both self-compassion ( r=-0.850, P<0.01) and self-management behaviors ( r=-0.736, P<0.01). In contrast, self-compassion was significantly positively correlated with self-management behaviors ( r=0.743, P<0.01). Self-compassion partially mediated the relationship between diabetes-related psychological distress and self-management behaviors, with a mediation effect size of -0.456. Conclusions:Psychological distress among T2DM patients is at a moderate level, and their self-management behaviors require urgent improvement. Psychological distress not only directly impacts self-management behaviors but also indirectly influences them through self-compassion. Healthcare professionals should prioritize enhancing patients′ self-compassion levels to mitigate the negative effects of psychological distress on their health behaviors.

This study applies a PEST-SWOT hybrid analysis framework to address key challenges in promoting the"In-ternet Plus"full-process management model for mental disorders.Key issues include the imbalance in service resource distribu-tion between urban and rural areas,insufficient effectiveness of digital technologies,and the lack of coordinated multi-stakeholder mechanisms.By analyzing macro-environmental factors,such as policy,economy,society,and technology,alongside internal strengths,weaknesses,opportunities,and threats,the study underscores the significant advantages and challenges of implemen-ting the"Internet Plus"model in mental disorder management.To achieve better promotion outcomes,it is crucial to enhance le-gal and policy frameworks,strengthen technological innovation,optimize service delivery models,and establish collaborative mechanisms among stakeholders.

Objective:To investigate the status of psychological distress, self-compassion, and self-management behaviors among patients with type 2 diabetes mellitus (T2DM), and explore the mediating role of self-compassion in the relationship between diabetes distress and self-management behaviors, and to provide a theoretical basis for the psychological intervention of patients with T2DM.Methods:A convenience sampling method was adopted to select 221 patients with T2DM hospitalized in the Department of Endocrinology and Metabolism, the First Hospital of China Medical University from November 2023 to April 2024. The General Information Form, the Diabetes Distress Scale-17, the Self-Compassion Scale and the Summary of Diabetes Self-Care Activity were utilized for investigation. A structural equation model was constructed with AMOS 24.0 to analyze the relationships among psychological distress, self-compassion, and self-management behaviors, and the mediating effect of self-compassion was tested using the Bootstrap method.Results:A total of 221 patients with T2DM were included, including 138 males and 83 females, aged (54.52 ±10.42) years old. The total score of psychological distress of patients with T2DM was (34.55 ± 18.82) points, the total score of self-compassion was (94.22 ± 26.04) points, and the total score of self-management behavior was (40.81 ± 22.64) points. Psychological distress in T2DM patients was significantly negatively correlated with both self-compassion ( r=-0.850, P<0.01) and self-management behaviors ( r=-0.736, P<0.01). In contrast, self-compassion was significantly positively correlated with self-management behaviors ( r=0.743, P<0.01). Self-compassion partially mediated the relationship between diabetes-related psychological distress and self-management behaviors, with a mediation effect size of -0.456. Conclusions:Psychological distress among T2DM patients is at a moderate level, and their self-management behaviors require urgent improvement. Psychological distress not only directly impacts self-management behaviors but also indirectly influences them through self-compassion. Healthcare professionals should prioritize enhancing patients′ self-compassion levels to mitigate the negative effects of psychological distress on their health behaviors.

Objective:To develop a convolutional neural network model of whole slide imaging of cerebrospinal fluid cells for rapid and accurate identification and classification of tumor cells in cerebrospinal fluid.Methods:A total of 8 692 cerebrospinal fluid cytology smears from Huashan Hospital Affiliated to Fudan University from January 2nd, 2019, to December 27th, 2024. As randomly assigned, the training set included 4 941 benign and 1 745 malignant samples, while the validation set comprised of 1 368 benign and 638 malignant samples. Whole-slide digital images were acquired using a cytopathology scanner, cells (clusters) were annotated for classification, and a deep learning model was constructed via tiled image patches for cell detection and classification. Model performance was evaluated using accuracy, sensitivity, specificity, and other indicators. The classification efficiency of manual microscopy was compared.Results:The model achieved a mean precision of 96.75% for cerebrospinal fluid cell classification. For malignant tumor cells, the classification accuracy was 96.61% (mAP=98.36%, AUC=0.97). Subtype classification accuracies for epithelial/epithelioid tumors and small round cell tumors were 97.13% (AUC=0.98) and 95.58% (AUC=0.93), respectively. Compared with manual microscopy, which took (9.70±0.82) minutes for classifying 200 cells, (18.27±1.21) minutes for 500 cells, and often exceeded 60 minutes or infeasible for full slides, the AI model took (3.46±0.49) seconds for 200 cells, (6.76±0.82) seconds for 500 cells, and a median of 48.57 seconds for full slides ( P<0.001), representing an efficiency improvement of approximately 161-170 times, significantly enhancing diagnostic efficiency. Conclusion:This fully automated hierarchical deep learning model enables efficient and accurate tumor cell identification and classification in CSF, providing an effective auxiliary tool for the rapid diagnosis of meningeal carcinomatosis.

The incidence and mortality of venous thromboembolism (VTE) are high in critically ill patients, and there is still a risk of VTE and bleeding after the use of fixed-dose low molecular weight heparin (LMWH) for prophylaxis. The level of anti-factor Ⅹa is not up to standard after LMWH prophylaxis in patients with surgery or trauma. The condition of critically ill patients is complicated, and the proportion of patients with low antithrombin Ⅲ is high, which can affect the prophylactic efficacy of LMWH and contribute to VTE occurrence. There is currently no consensus on whether adjusting LMWH dose according to anti-factor Ⅹa levels can reduce VTE occurrence in critically ill patients. High-quality multicenter randomized controlled studies are needed in the future to establish new approaches for precise prevention of VTE in critically ill patients.

Based on the concept definition and research status of the core competencies for home-based elderly caregivers,combined with the current development situation of China's elderly care industry and the relevant experience of Japan,Germany,and other countries in the construction of elderly care service systems,this paper sorted out that the core competencies for home-based elderly caregivers in China at this stage,such as elderly care skills,legal and ethical qualities,communication skills,and digital intelligence application capabilities,were relatively weak and cannot meet the comprehensive requirements of the current complex social environment,the individual needs and complex psychology of disabled elderly,and traditional concepts for caregivers.By closely integrating the active aging strategy proposed by the Party and our country,it was clear that home-based elderly caregivers should possess four core competencies,including comprehensive elderly care skills,basic legal and ethical qualities,good communication skills,and necessary informatization application capabilities.It was recommended that training institutions and universities enhance the core competencies for home-based elderly care caregivers by conducting training courses in elderly care,basic legal ethics,communication skills,and the use of smart devices,with a view to providing references for the sustainable development of elderly care.