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）］

Background The power industry is characterized by typical shift work systems, with 24-hour uninterrupted work demands, high intensity and high standard job characteristics, as well as emergent task pressure, which exposes employees to the long-term dual pressure of shift work and occupational stress and may lead to occupational burnout. It not only endangers the physical and mental health of employees, but also threaten the safe and stable operation of the power system. Objective To explore the impact of shift work and occupational stress, as well as their potential interaction, on occupational burnout among employees in power enterprises. Methods From November 2024 to April 2025, cluster sampling was used to select 1378 workers from two power companies in Fuzhou. A self-designed questionnaire, the Effort-Reward Imbalance model, and the Maslach Burnout Inventory were used to investigate the participants’ general information，shift work patterns, occupational stress, and occupational burnout. Statistical analysis was conducted using SPSS 19.0 software. Chi-square test was employed for intergroup comparison. Logistic regression was used to examine the associations between shift work, occupational stress, and job burnout. The multiplicative interaction and additive interaction between shift work and occupational stress on occupational burnout were evaluated. Results A total of 1378 questionnaires were distributed, and 1113 were valid questionnaires, with an effective rate of 80.77%. Among the participants, 37.92% were engaged in shift work, the positive rate of occupational stress was 29.83%, and the positive rate of occupational burnout was 55.80%. The logistic regression analysis showed that after adjusting for confounding factors, the risks of occupational burnout in the non-shift x occupational stress group and the shift x occupational stress group were 1.59 times (95%CI: 1.12, 2.27; P=0.01) and 4.07 times (95%CI: 2.56, 6.45; P<0.01) higher than that in the non-shift x non-occupational stress group. A multiplicative interaction (shift work and occupational stress b=0.75, P=0.01, OR=2.12, 95%CI: 1.18, 3.80) and an additive interaction (relative excess risk ratio=2.24, 95%CI: 0.54, 3.94; attributable fraction=0.55, 95%CI: 0.32, 0.78; interaction index=3.71, 95%CI: 1.47, 9.40) between shift work and occupational stress on job burnout were identified. Conclusion Shift work and occupational stress are risk factors for occupational burnout among employees in power enterprises, and there is a synergistic interaction between these two factors in terms of their impact on occupational burnout.

Military training represents one of the most essential activities for troops during peacetime,of which the prevention and treatment of training-induced injuries are a very important part.Recent findings of research suggest that cold atmospheric plasma(CAP)exhibits a distinctive and multifaceted superiority in terms of broad-spectrum sterilization,rapid blood coagulation and healing promotion for wounds.Consequently,CAP has good prospects of applications in diverse fields such as clinical medicine,emergency rescue and military medicine.Based on a review of the research progress in plasma medicine,the applicability of CAP in the prevention and treatment of military training injuries was discussed in this paper by focusing on the urgent issues related to military training injury,including the typical application scenarios and methods for CAP,the safety and effectiveness of plasma trauma prevention and treatment,and the key issues facing the prevention and treatment of military training injuries.

OBJECTIVE To standardize the use of sterile powder for injection redissolution solvent and intravenous drugs diluent solvent， and ensure the safety of clinical drug use. METHODS The intravenous drug resolvent generation system and the intravenous drug solvent incompatibility rules library were constructed and operated by prescription-checking pharmacist team in our hospital by formulating a list of intravenous drugs needed to be dissolved with sterilized water for injection and a contraindication list of intravenous solvent compatibility. The unreasonable medical orders reviewed and intervened in our hospital from January to April 2023 （before the implementation of the intravenous drug solvent incompatibility rules library） and from May to August 2023 （after the implementation） were analyzed statistically to compare the number of unreasonable solvent selection orders， interception rate， and the success rate of pharmacists’ interventions for unreasonable solvent selection orders before and after the implementation. RESULTS Before the implementation of the solvent incompatibility rules library， a total of 5 229 groups of medical orders with unreasonable solvent selection in our hospital were identified， among which there were 1 204 groups of seriously unreasonable medical orders， with interception rate of 23.03% and the success rate of pharmacists’ intervention of 15.90%. After the implementation of the solvent incompatibility rules library， the total number of medical orders with unreasonable solvent selection was 3 258 groups， among which there were 1 148 groups of seriously unreasonable medical orders， with interception rate of 35.24% and success rate of pharmacists’ intervention of 24.83%， being significantly higher than before implementation （P＜0.01 or P＜0.001）. CONCLUSIONS The establishment and application of the intravenous drug resolvent generation system and the solvent incompatibility rules library can significantly increase the interception rate of unreasonable solvent selection orders and the success rate of pharmacists’ interventions, and ensure the safety of clinical drug use.

Objective:Clinical characteristics and diagnosis and treatment process was reported and analyzed of a patient with brucellosis complicated with thyroid abscess, providing reference for the clinical diagnosis of brucellosis complicated with thyroid abscess.Methods:Clinical medical records of a patient with brucellosis complicated with thyroid abscess who was treated at the General Surgery Department of Yanchi County People's Hospital in Wuzhong City, Ningxia Hui Autonomous Region in November 2021 were collected. The clinical manifestations, blood routine, brucella antibodies, thyroid function, bacterial culture, thyroid ultrasound and other examination results, as well as the diagnosis and treatment process, were comprehensively analyzed. Results:The patient was a male, 61 years old, who presented with a neck mass without typical clinical manifestations of brucellosis. Thyroid ultrasound revealed a space occupying lesion, and the preliminary diagnosis was thyroid cystadenoma. Thyroid right lobe and isthmus resection surgery was performed. During the operation, it was found that some of the thyroid glands were tightly adhered to the cervical blood vessels, so the resection surgery was changed to abscess drainage, and the drainage fluid was purulent and bloody. The bacterial culture result of thyroid purulent fluid (intraoperative puncture fluid and postoperative drainage fluid) was brucella lamblia, and the serum brucella test tube agglutination test titer was 1 ∶ 400 (+++). The patient improved and was discharged after local drainage and anti brucella treatment. Follow up for 4 months showed no abnormalities. Conclusions:Brucellosis which begins with a local infection of the thyroid gland is extremely rare, with no characteristic clinical manifestations, and is prone to misdiagnosis. Timely correction of the surgical plan during the treatment process avoids the removal of the patient's thyroid, which has a certain clinical reference value.

Objective:To explore the effects of Tongdu Tiaoshen acupuncture on vascular endothelial function and inflammatory factors in patients with mild cognitive impairment (MCI) after ischemic stroke (IS).Methods:A retrospective analysis was performed on the clinical data of 71 patients with MCI after IS in the hospital between January 2020 and September 2022. According to different treatment methods, they were divided into Tongdu Tiaoshen acupuncture group ( n=31, Tongdu Tiaoshen acupuncture + oral nimodipine tables) and routine body-acupuncture group ( n=40, routine body-acupuncture group + oral nimodipine tables). Both groups were treated for 2 courses (14 d/course). Before and after treatment, levels of serum NO and endothelin-1 (ET-1) were detected by radioimmunoassay, and levels of serum basic fibroblast growth factor (bFGF) and vascular endothelial growth factor (VEGF), plasma homocysteine (Hcy) and IL-6 were detected by ELISA. The cognitive function of patients was evaluated and intelligence level by Montreal Cognitive Assessment Scale (MoCA), Mini-Mental State Examination(MMSE) and the clinical curative effect was also evaluated. Results:The total response rates in Tongdu Tiaoshen acupuncture group and routine body-acupuncture group were 90.32% (28/31) and 70.00% (28/40), and the difference between the two groups was statistically significant ( χ2=4.33, P=0.037). After treatment, levels of plasma Hcy and IL-6 in Tongdu Tiaoshen acupuncture group were lower than those in the routine body-acupuncture group ( t=2.57, 9.36, P<0.05 or P<0.01). After treatment, levels of serum bFGF, VEGF and NO in Tongdu Tiaoshen acupuncture group were significantly higher than those in the routine body-acupuncture group ( t=10.03, 9.29, 8.17, P<0.01), while ET-1 level was significantly lower than that of the routine body-acupuncture group ( t=2.41, P=0.019). After treatment, MoCA score [(28.24±4.45) vs. (25.32±4.34), t=2.78], MMSE score [(28.73±1.44) vs. (28.02±1.22), t=2.25] in Tongdu Tiaoshen acupuncture group were higher than those in the routine body-acupuncture group ( P<0.01). Conclusion:Tongdu Tiaoshen acupuncture is beneficial to improve vascular endothelial function, reduce levels of inflammatory factors, promote the recovery of cognitive function and improve curative effect in patients with MCI after IS.

A retrospective analysis was made on the clinical data and gene mutation characteristics of 2 children admitted to the Children′s Hospital of Zhejiang University School of Medicine for epilepsy without periventricular nodules caused by the ARF1 gene mutation from August 2023 to February 2024, and relevant literature was reviewed.Both patients presented with seizures and psychomotor retardation, and 1 of them was diagnosed with West syndrome.Whole exome sequencing confirmed that the 2 patients carried a missense mutation in the ARF1 gene (c.55C>A, p.R19S).Brain magnetic resonance imaging (MRI) of 2 patients revealed no obvious abnormalities.A summary analysis of 5 cases of ARF1 gene mutations reported in three foreign literatures showed that patients with ARF1 gene mutations usually presented with seizures, developmental delay, hypotonia, mental retardation, and motor stereotypies.MRI showed periventricular nodular heterotopia, corpus callosum dysplasia, subcortical white matter abnormalities, and delayed myelination.This study found for the first time that ARF1-related disorders can occur without significant brain structural malformations, indicating that there are inconsistencies in neuroimaging findings, adding valuable phenotypic information to this gene.The differences in imaging findings may be the result of genetic background or variation in ARF1-interacting proteins, or may be caused by altered regulatory mechanisms of protein activity.

Objective To explore the value of deep learning models in predicting axillary lymph node(ALN)metastasis of breast cancer based on intratumoral and peritumoral dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI).Methods A retrospective analysis was conducted on cases from Tianjin Medical University Cancer Hospital and Laoshan Branch of Affiliated Hospital of Qingdao University,involving a total of 850 lesions in 850 patients.The region of interest within the tumor was delineated at the largest area of the lesion on the first enhancement images and automatically expanded by 3 mm and 6 mm in a conformal fashion.Deep learning prediction models based on ResNet50 were developed via intratumoral,peritumoral,and intratumoral combined peritumoral models,respectively,and a comprehensive prediction model was developed by integrating semantic features of imaging reports.Cases from Tianjin Medical University Cancer Hospital were randomly divided into training and test cohorts in a 7∶3 ratio,while cases from Laoshan Branch of Affiliated Hospital of Qingdao University served as the external validation cohort.The area under the curve(AUC),accuracy,sensitivity,specificity,F1-score,and Brier-score were calculated,respectively.Results The model incorporating intratumoral,peritumoral(3 mm),and semantic features demonstrated the highest performance,with AUC of 0.801[95％confidence interval(CI)0.765-0.845],0.781(95％CI 0.745-0.817),and 0.752(95％CI 0.700-0.793)in the training cohort,test cohort,and external validation cohort,respectively,and there was no significant difference in AUC between combined model and intratumoral/peritumoral model,respectively,but it demonstrated the higher sensitivity and F1-score,and the lower Brier-score.Conclusion Incorporating peritumoral images into the conventional model based on intratumoral images enhanced the predictive ability of ALN metastasis in breast cancer.

Background Dentists are a high-risk population of work-related musculoskeletal disorders (WMSDs), where the body part with the highest prevalence is the neck. Objective To analyze potential influencing factors of neck pain among dentists, and explore a prediction model of neck pain in dentists. Methods Dentists from different hospitals in Fuzhou were selected as study subjects by stratified cluster sampling according to hospital characteristics (dental hospitals, general hospitals, and dental clinics). The basic information, presentation of WMSDs, and its influencing factors were investigated by using the Chinese version of Musculoskeletal Disorders Questionnaire and the Subjective Workload Assessment Technique. A total of 655 questionnaires were collected, of which 603 were valid, with an effective rate of 92.1%. Multiple logistic regression was used to analyze potential influencing factors of neck pain in dentists. A prediction model of neck pain of dentists was constructed by using neural network model, and the prediction efficiency of the model was evaluated. Results The neck was the body part with the highest prevalence (43.8%, 264/603) of WMSDs among dentists. The results of multiple logistic regression analysis showed that female (OR=2.709, 95%CI: 1.852-3.962, P <0.001), working age of 10-<20 years (versus <10 years, OR=3.836, 95%CI: 2.471-5.957, P<0.001), keeping head up or down for a long time (OR=8.492, 95%CI: 2.203-32.731, P=0.002), holding head sideways for a long time (OR=2.210, 95%CI: 1.376-3.550, P<0.001), maintaining the same sitting spot for a long time (OR=4.336, 95%CI: 2.192-8.579, P<0.001), and psychological load value ≥70 (versus <40, OR=1.901, 95%CI: 1.038-3.480, P=0.037) increased the risk of neck pain in dentists. Sufficient operating space (OR=0.507, 95%CI: 0.302-0.850, P=0.010) and doing some exercise during work break (OR=0.670, 95%CI: 0.453-0.991, P=0.045) reduced the risk of reporting neck pain among dentists. A neural network prediction model of dentists' neck pain was constructed with 1 hidden layer and 6 hidden layer neurons. The percentage of correct prediction of training set was 89.6%, and the percentage of correct prediction of test set was 83.9%. The order of importance of the independent variables included in the model were working age, holding head sideways for a long time, psychological load, etc. The result of neural network model of neck pain among dentists showed that the area under the curve of receiver operator characteristic (ROC) was 0.940 (95%CI: 0.922-0.958, P<0.001). When the maximum diagnostic value was determined by the ROC curve, the sensitivity was 84.8%, the specificity was 91.2%, and the Youden Index was 0.760. Conclusion Neck pain of dentists is affected by many factors, such as individual factors (gender and working age), ergonomic factors (keeping various postures and operations for a long time, operating space, etc.), psychological factors (different levels of psychological load) and so on. The neural network model can be used as a prediction tool to explore the risk of reporting neck pain among dentists.

Objective:To investigate the changes in gray matter volume (GMV) and abnormalities in structural covariant network (SCN) patterns in patients with chronic pontine infarction (PI).Methods:Patients with unilateral chronic PI (case group) with the first onset admitted to the First Affiliated Hospital of Zhengzhou University and Tianjin Medical University General Hospital from October 2014 to June 2021 were prospectively included. At the same time, healthy subjects matched with age, gender and education years (normal control group) were included. High-resolution three-dimensional T 1 structural MRI images and behavioral scores of the subjects were collected. The voxel-based morphometry and two-sample t test were used to explore the differences in GMV between the groups. Using GMV differential brain regions as seed points, SCN was constructed to explore the abnormality of structural covariant patterns in patients with PI. Spearman rank correlation analysis was used to analyze the correlation between GMV in differential brain regions and behavioral scores. Results:A total of 60 patients with PI were enrolled, including 33 left PI and 27 right PI, while 34 healthy controls were also enrolled. Compared with the normal control group, the GMV in bilateral posterior cerebellar lobe decreased significantly in the left PI group, and the GMV in left anterior and posterior cerebellar lobes and the right posterior cerebellar lobe decreased significantly in the right PI group (Gaussian random field correction with voxel level P<0.001 and cluster level P<0.05, cluster voxel >20), and there was a significant correlation between GMV values in the left anterior and posterior cerebellar lobes and the right posterior cerebellar lobe and the motor function score ( P<0.05). In addition, compared with the normal control group, the right PI group had broader covariate brain regions and a significant increase in the number of structural connections between covariate brain regions (family-wise error correction with voxel level P<0.05, cluster voxel >20). Conclusions:The GMV in bilateral posterior cerebellar lobe decreases significantly in patients with chronic PI, and were secondary to broader covariate brain regions and structural connections. This may be the neural mechanism of impaired behavioral function in patients with PI.