As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

ObjectiveTo introduce visual teaching into the course design of medical humanistic care based on the concept of implementation science， evaluate the teaching implementation effect and feedback， and provide references for optimizing course teaching outcomes and improving students’ humanistic care competence. MethodsA visual teaching program for medical humanistic care was designed， with key steps including clarifying teaching objectives， content， methods， and curriculum assessment. This program was implemented in the medical humanistic care course teaching involving 50 elective students. Multi-dimensional evaluation of teaching effectiveness was conducted through course grades， visual teaching evaluation， and humanistic workshop assessment， combined with inductive content analysis of students’ learning experiences in the workshops. ResultsThe 50 students achieved above-average course grades （89.60±3.41） and demonstrated high satisfaction with the overall course and visual teaching. All the 6 groups obtained relatively high scores in the medical humanistic care workshops. Four themes were extracted， namely， enhancing humanistic care competencies， deepening familial and interpersonal relationships， realizing emotional expression and self-growth， and strengthening integration of humanistic care concepts with practice. ConclusionThe teaching of medical humanistic care course has achieved favorable effects， which contributes to deepening students’ understanding of humanistic care and enhancing their humanistic care competence. Students demonstrate high levels of recognition and satisfaction with the course.

Objective: To explore the setting of gray zone of Treponema pallidum (TP) testing by retrospective analysis of blood donors with single reagent reactive anti-TP results, so as to improve blood utilization and supply safety. Methods: Blood samples were collected from 112 blood donors previously deferred due to single reagent reactive TP antibody results between January 2020 and December 2023, and subjected to dual ELISA reagents and TPPA test. The gray zone panel analysis was performed on the two ELISA reagents currently used in our department. The detection rate at each concentration of the gray zone panle was counted, and the corresponding concentrations for C , C , and C and gray zone cut-off were calculated. Results: Among the 50 samples deferred by reagent 1, 19 were confirmed reactive and 31 non-reactive in supplementary testing. Among the 62 samples deferred by reagent 2, 12 were confirmed reactive and 50 non-reactive in supplementary testing. For reagent 1, the detection rate of was 56% for S/CO≥1 and 20% for 0.5≤S/CO<1, retrospectively. For reagent 2, the detection rate was 27% for S/CO≥1 and 12.5% for 0.5≤S/CO<1, retrospectively. The detection rate for S/CO≥1 was higher than those for 0.5≤S/CO<1 for both reagents. All the 112 samples were negative in TPPA test. The C concentration of reagent 1 was 1.51 mIU/mL, and the concentration range of C ±20% was 1.21-1.81 mIU/mL. The C concentration of reagent 2 was 1.45 mIU/mL, and the concentration range of C ±20% was 1.16-1.74 mIU/mL. The C and C concentration of both reagents were within the C ±20% range, suggesting that the gray zone cutoff for both Reagent 1 and Reagent 2 should be set at S/CO=0.8 (80% of the CO value). Conclusion: All anti-TP single reagent reactive samples with S/CO value within the gray zone was tested negative by TPPA. It is necessary to consider the rationality and necessity of establishing the gray zone, so as to ensure blood safety and improve the utilization rate of blood resources.

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

BackgroundAnxiety disorder is a common mental disorder， with its prevalence showing a continuous upward trend， significantly affecting the quality of life and social function of patients. Due to the lack of objective and reliable biomarkers in clinical practice， the early identification and treatment of anxiety disorder have been somewhat limited. Plasma proteins have the potential to serve as biomarkers for mental diseases， however， the causal relationship between them and anxiety disorder remains unclear. ObjectiveTo identify the plasma proteins that have a causal relationship with anxiety disorders， and to elucidate the associated biological pathways， in order to provide references for the search for biomarkers of anxiety disorders and the exploration of potential therapeutic targets. MethodsBased on the protein quantitative trait locus （pQTL） data of 4 907 plasma proteins covering 35 559 Icelandic individuals from the deCODE database， and the genome-wide association studies （GWAS） data of 50 486 patients with anxiety disorders and 330 460 healthy controls， the inverse-variance weighted （IVW） method was used as the main analysis method， supplemented by MR-Egger method， weighted median method， simple model method， and weighted model method for bidirectional Mendelian randomization analysis. Enrichment analysis of gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathways was conducted for the related proteins. Sensitivity analysis was performed using Cochran's Q test， MR-Egger intercept test， MR-PRESSO test， and leave-one-out analysis to evaluate the robustness of the results. ResultsA total of 10 plasma proteins were identified as significantly associated with anxiety disorders. Among these， SPATA9 （OR=0.856， 95% CI： 0.784–0.934， P<0.01） and PDE5A （OR=0.911， 95% CI： 0.864–0.961， P<0.01） were identified as protective factors， while CRYGD （OR=1.209， 95% CI： 1.095–1.334， P<0.01）， BTN3A3 （OR=1.045， 95% CI： 1.018–1.073， P<0.01）， SERPINB13 （OR=1.102， 95% CI： 1.040–1.168， P<0.01）， ERBB4 （OR=1.283， 95% CI： 1.109–1.484， P<0.01）， LSAMP （OR=1.096， 95% CI： 1.037–1.158， P<0.01）， ICOSLG （OR=1.283， 95% CI： 1.104–1.490， P<0.01）， DNAJB11 （OR=1.172， 95% CI： 1.076–1.277， P<0.01）， and TREML1 （OR=1.115， 95% CI： 1.054–1.179， P<0.01） were identified as risk factors. The sensitivity analysis showed that the results were robust， with no heterogeneity （Cochran's Q test P>0.05） or pleiotropy （MR-Egger intercept test P>0.05）. Enrichment analysis indicated that these plasma proteins were enriched in biological processes such as T-cell signal transduction， lymphocyte proliferation， cell membrane structure and synaptic function， as well as the intestinal immune network that produces IgA and the ErbB signaling pathway. ConclusionThis study identified 10 plasma proteins associated with anxiety disorders. The functions of these plasma proteins involve multiple biological processes such as neural development and immune regulation.

Objective To systematically evaluate the efficacy and safety of video-assisted thoracoscopic surgery (VATS) with different numbers of ports in the treatment of spontaneous pneumothorax. Methods We conducted a comprehensive search of CNKI, PubMed, The Cochrane Library, Web of Science, EMbase, Wanfang Data, and the Chinese Medical Journal Full-text Database for clinical controlled trials on VATS with different port numbers for spontaneous pneumothorax, from their inception to March 2023. Two researchers independently screened the literature and assessed its quality.The Newcastle-Ottawa Scale (NOS) was used to assess the methodological quality of cohort and case-control studies, and the Cochrane risk-of-bias tool was used to evaluate randomized controlled trials (RCT). Meta-analysis was performed using RevMan 5.4.1 software. Results A total of 107 studies were included, comprising 35 RCT, 2 cohort studies, and 70 case-control studies. All cohort and case-control studies included in the analysis had NOS scores≥7. The meta-analysis revealed that compared to two-port VATS (2P-VATS) and three-port VATS (3P-VATS), single-port thoracoscopic surgery (SPTS) was associated with less intraoperative blood loss (SMD=–1.58, 95%CI: –1.93 to –1.22, P<0.001; and SMD=–1.59, 95%CI: –2.03 to –1.14, P<0.001, respectively), shorter postoperative hospital stay (SMD=–1.05, 95%CI: –1.29 to –0.82, P<0.001; and SMD=–1.08, 95%CI: –1.39 to –0.77, P<0.001), shorter duration of postoperative chest tube drainage (SMD=–0.75, 95%CI: –1.00 to –0.50, P<0.001; and SMD=–1.23, 95%CI: –1.72 to –0.75, P<0.001), fewer postoperative complications (OR=0.34, 95%CI: 0.26 to 0.45, P<0.001; and OR=0.47, 95%CI: 0.33 to 0.68, P<0.001), and lower pain scores at 24, 48, and 72 hours after surgery (P<0.05). The operative time for SPTS was shorter than that for 2P-VATS (SMD=–0.53, 95%CI: –0.90 to –0.16, P=0.005) but showed no significant difference compared to 3P-VATS (P=0.21). When comparing 2P-VATS with 3P-VATS, 2P-VATS demonstrated less intraoperative blood loss (SMD=–1.02, 95%CI: –1.81 to –0.22, P=0.01), shorter postoperative hospital stay (SMD=–0.59, 95%CI: –1.11 to –0.06, P=0.03), shorter duration of chest tube drainage (SMD=–0.46, 95%CI: –0.85 to –0.08, P=0.02), fewer postoperative complications (OR=0.36, 95%CI: 0.22 to 0.59, P<0.001), and lower pain scores at 24, 48, and 72 hours after surgery (P≤0.05). Conclusion Both SPTS and 2P-VATS are effective and safe surgical options for spontaneous pneumothorax, deserving further promotion and application in clinical practice. However, due to limitations in the quantity and quality of the included studies, more large-sample, high-quality research is needed to validate these findings.

Objective: To develop a dual-branch deep learning framework for accurate multi-label classification of fundus diseases, addressing the key limitations of insufficient complementary feature extraction and inadequate cross-modal feature fusion in existing automated diagnostic methods. Methods: The fundus multi-label classification dataset with 12 disease categories (FMLC-12) dataset was constructed by integrating complementary samples from Ocular Disease Intelligent Recognition (ODIR) and Retinal Fundus Multi-Disease Image Dataset (RFMiD), yielding 6 936 fundus images across 12 retinal pathology categories, and the framework was validated on both FMLC-12 and ODIR. Inspired by the holistic multi-regional assessment principle of the Five Wheels theory in traditional Chinese medicine (TCM) ophthalmology, the dual-branch multi-label network (DBMNet) was developed as a novel framework integrating complementary visual feature extraction with pathological correlation modeling. The architecture employed a TransNeXt backbone within a dual-branch design: one branch processed red-green-blue (RGB) images to capture color-dependent features, such as vascular patterns and lesion morphology, while the other processed grayscale-converted images to enhance subtle textural details and contrast variations. A feature interaction module (FIM) effectively integrated the multi-scale features from both branches. Comprehensive ablation studies were conducted to evaluate the contributions of the dual-branch architecture and the FIM. The performance of DBMNet was compared against four state-of-the-art methods, including EfficientNet Ensemble, transfer learning-based convolutional neural network (CNN), BFENet, and EyeDeep-Net, using mean average precision (mAP), F1-score, and Cohen's kappa coefficient. Results: The dual-branch architecture improved mAP by 15.44 percentage points over the single-branch TransNeXt baseline, increasing from 34.41% to 44.24%, and the addition of FIM further boosted mAP to 49.85%. On FMLC-12, DBMNet achieved an mAP of 49.85%, a Cohen’s kappa coefficient of 62.14%, and an F1-score of 70.21%. Compared with BFENet (mAP: 45.42%, kappa: 46.64%, F1-score: 71.34%), DBMNet outperformed it by 4.43 percentage points in mAP and 15.50 percentage points in kappa, while BFENet achieved a marginally higher F1-score. On ODIR, DBMNet achieved an F1-score of 85.50%, comparable to state-of-the-art methods. Conclusion DBMNet effectively integrates RGB and grayscale visual modalities through a dual-branch architecture, significantly improving multi-label fundus disease classification. The framework not only addresses the issue of insufficient feature fusion in existing methods but also demonstrates outstanding performance in balancing detection across both common and rare diseases, providing a promising and clinically applicable pathway for standardized, intelligent fundus disease classification.

Objective To investigate the prognostic value of preoperative plasma fibrinogen (FIB) combined with lymphocyte-to-monocyte ratio (LMR) in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC). Methods A retrospective analysis was conducted on ESCC patients who underwent esophagectomy in the Affiliated Lihuili Hospital of Ningbo University from 2015 to 2018. Based on the cut-off values of preoperative FIB and LMR, the F-LMR scoring system was constructed, and patients were divided into three groups according to the F-LMR score. Kaplan-Meier analysis was used to assess 5-year overall survival (OS) and 5-year progression free survival (PFS), and univariate and multivariate Cox regression analyses were performed to identify prognostic factors. Results Finally 260 patients were collected, including 237 males and 23 females, with a median age of 64 years (IQR: 59-70). The 5-year OS rates for patients with F-LMR score of 0, 1, and 2 were 24.44%, 51.69%, and 67.31%, respectively, and the 5-year PFS rates were 15.56%, 42.37%, and 57.62%, respectively. Lower preoperative F-LMR scores were associated with worse prognosis. Multivariate analysis showed that deeper tumor invasion, presence of lymph node metastasis, larger tumor maximum diameter, and lower preoperative F-LMR score were independent risk factors for OS. Conclusion The F-LMR scoring system based on the preoperative FIB and LMR may serve as an effective tool for predicting the prognosis of patients with ESCC.

Objective: To analyze the school tuberculosis (TB) outbreaks and preventive treatment in Hefei from 2022 to 2024, so as to provide reference for TB prevention and control in schools. Methods: Data were collected on all school based TB outbreaks occurring during 2022-2024 in Hefei, defined as ≥2 epidemiologically linked TB cases within the same school during a single semester. Statistical analyses were performed using the Chi square test. Results: Close contacts exhibited significantly higher TB incidence (2.88%) and latent mycobacterium tuberculosis infection (LTBI) rates (13.80%) in the school TB outbreaks, compared to non close contacts (0.12% and 2.63%, respectively). Among close contacts, secondary school students showed lower TB incidence (0.48%) and LTBI prevalence (3.42%) than both primary school or younger children (0.68%, 6.95%) and college students ( 0.78% , 6.50%), with statistically significant differences ( χ 2=360.91, 6.37; 791.71, 102.03, all P <0.05). The proportion of LTBI individuals recommended for preventive therapy was higher in primary school or younger groups (98.59%) than in secondary (95.25%) or college students (86.34%) ( χ 2=25.86, P <0.01). However, among those recommended, close contacts had higher uptake (85.82%) and completion rates (87.25%) of preventive therapy than non close contacts (69.63% and 70.57%); similarly, secondary school students demonstrated higher uptake (91.21%) and completion rates (86.45%) compared to primary school or younger (88.57%, 83.87%) and college students (57.28%, 64.08%) ( χ 2=30.52, 26.72; 125.17, 38.84, all P <0.01). Subsequent TB incidence among LTBI close contacts (13.30%) and among those who did not complete preventive therapy (22.73%) were significantly higher than among non close contacts (2.80%, 2.41%), respectively ( χ 2=32.19, 13.87, both P <0.05). Conclusions In school TB outbreaks, close contacts face higher LTBI prevalence and subsequent TB risk than non close contacts. College students show notably low adherence to preventive therapy. It is necessary to take targeted measures to improve the compliance of preventive measures among students.

The development of the rare disease discipline is a crucial pathway for enhancing the diagnosis and treatment of rare diseases, cultivating specialized professionals, and fostering technological innovation. Currently, China' rare disease discipline is accelerating its development driven by both policy and demand. However, it still faces multi-dimensional challenges, including an incomplete clinical management mechanism, a shortage of interdisciplinary talents, a weak scientific research system, and limited outreach capacity. To address these challenges, this paper proposes and constructs an integrated development system with clinical diagnosis and treatment as the foundation, talent cultivation as the engine, scientific research as the support, and disciplinary outreach capacity as the extension. Specific strategies include: enhancing clinical management through artificial intelligence-assisted diagnosis systems and multidisciplinary collaboration platforms; strengthening the talent pool through textbooks, curricula, and hierarchical training mechanisms; bolstering research collaboration and translational outcomes by leveraging international data-sharing platforms, national rare disease medical centers, the State Key Laboratory of Complex Severe and Rare Diseases, and the National Key Scientific Infrastructure for Translational Medicine; and expanding grassroots outreach and public awareness through the National Rare Disease Diagnosis and Treatment Collaboration Network, the National Rare Disease Quality Control Center, and integrated media communication channels. In the future, the rare disease discipline should further deepen the integration of medicine and engineering, expand international cooperation, focus on the translational closed loop, improve the regional collaboration network, so as to build a more resilient and dynamic disciplinary ecosystem, and ultimately achieve a comprehensive improvement in the diagnosis and treatment of rare diseases.