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.

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.

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.

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.

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 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.

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.

Objective:To explore the application effects of the goal-oriented teaching method based on mind mapping in the teaching of stomatology practical courses.Methods:From September 2022 to September 2023, 52 fourth-year students of clinical stomatology at Harbin Medical University were divided into test group and control group for practical teaching, with 26 cases in each group. The test group received goal-oriented teaching based on mind mapping, while the control group received traditional teaching, for 20 class hours in both groups. The two groups were compared in terms of general data, theoretical and practical assessment scores, the score of the self-rating scale of self-directed learning (SRSSDL) and the score of critical thinking disposition inventory-Chinese version (CTDI-CV) before and after training, and student satisfaction with teaching activities. SPSS 25.0 software was used to perform the t-test or χ2 test. Results:After completing the practical training courses, the test group showed significantly higher scores than the control group in multiple-choice questions [(16.85±1.39) vs. (15.33±2.21)], fill-in-the-blank questions [(17.21±1.98) vs. (16.01±2.02)], short answer questions [(17.47±2.27) vs. (15.23±2.45)], case analysis [(34.36±2.79) vs. (32.57±3.02)], and practical assessment [(84.69±4.73) vs. (80.57±4.21)] (all P<0.05). The SRSSDL score and CTDI-CV score were improved in both groups, and were significantly higher in the test group [(215.29±10.42) and (357.49±17.80)] than in the control group [(200.23±11.42) and (342.23±17.26)] (both P<0.05). The students of the test group were significantly more satisfied with teaching activities than those of the control group ( P<0.05). Conclusions:Compared with the traditional teaching method, the goal-oriented teaching method based on mind mapping is more effective in stomatology practical teaching, which can improve students' self-directed learning ability and critical thinking ability, promote their mastery of theoretical knowledge, enhance their clinical practice ability, and increase their satisfaction with teaching activities.