BackgroundPatients with depressive episode and schizophrenia have a high risk of suicide. The sleep electroencephalogram power spectral density characteristics of patients with depressive episode accompanied by suicidal behavior and those with schizophrenia may be different， but there is currently a lack of direct comparative studies on these two groups of patients. ObjectiveTo compare the sleep electroencephalogram power spectral density between depressive episode and schizophrenic patients with suicidal behavior， in order to provide references for exploring predictive indicators of suicidal behavior. MethodsFrom June 2018 to December 2020， 20 patients with depressive episode and 20 patients with schizophrenia who had committed suicide within the past month and were treated at the outpatient department of Shenzhen Kangning Hospital were selected. All of them met the diagnostic criteria for depressive episode or schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）. Using a random sampling method， 20 volunteers with matching gender and age to the patient groups were selected from the Cuiping community in Shenzhen as the control group. The subjective sleep of the patients was evaluated using the Insomnia Severity Index （ISI）， the Dysfunctional Belief and Attitude about Sleep （DBAS）， the Disturbing Dreams and Nightmare Severity Index （DDNSI）， and the Epworth Somnolence Scale （ESS）. The objective sleep of the patients was assessed using polysomnography. The sleep electroencephalogram was filtered and the power spectral density of the brain wave was analyzed and processed for all the subjects. The subjective and objective sleep conditions of the two patient groups were compared， and the sleep electroencephalogram power spectral density of the patient groups and the control group were also compared. ResultsA comparison of subjective and objective sleep conditions between patients with depressive episode accompanied by suicidal behavior and patients with schizophrenia accompanied by suicidal behavior showed no statistically significant differences （P>0.05）. Comparisons of sleep electroencephalogram power spectral density in the W stage （average power of α wave， total power of δ wave， average power of δ wave， average power of θ wave）， N1 stage （average power of β wave， total power of α wave， total power of δ wave）， N2 stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave）， N3 stage （average power of α wave， average power of δ wave）， and R stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave） between patients with depressive episode accompanied by suicidal behavior， patients with schizophrenia accompanied by suicidal behavior， and the control group showed statistically significant differences （P<0.05 or 0.01）. The total power of δ wave in the W stage and the average power of β wave and δ wave in the N1 stage were higher in two patient groups were higher than those of the control group. The total power of α wave and the average power of α wave in the N2 stage were lower than those of the control group， while the average power of δ wave was higher than that of the control group. The average power of α wave in the N3 stage of both patient groups were lower than that of the control group， while the average power of δ wave was higher than that of the control group. The total power and average power of α wave in the R stage were lower than those of the control group， while the total power and average power of δ wave were higher than those of the control group. All the differences were statistically significant. Patients with depressive episode accompanied by suicidal behavior had higher average powers of α wave， δ wave， and θ wave in the W stage compared with the control group， while the total power of α wave in the N1 stage was lower in the former group. All these differences were statistically significant （P<0.05）. ConclusionThe depressive episode patients accompanied by suicidal behavior have highly overlapping sleep electroencephalogram abnormal patterns with those of schizophrenia patients， mainly manifested as a general decrease in α wave power （N2， N3， R stage） and a general increase in δ wave power （W， N1， N2， N3， R stage） as well as β wave power in N1 stage. At the same time， patients with depressive episode accompanied by suicidal behavior also show specific changes， including an increase in the average power of α and θ waves during the wakefulness period （W stage）， and a decrease in the total power of α wave in N1 stage. ［Funded by Guangdong Province High-level Clinical Key Specialty （with supporting funds from Shenzhen City） （number， SZGSP013）； Shenzhen Key Medical Discipline （number， SZXK041）； Shenzhen Clinical Medicine Research Center Project （number， 20210617155253001）］

Abstract To clarify the service targets, service contents, and safeguard mechanisms of the basic public service program for student vision health management, the study grounded in the current status of child and adolescent myopia prevention and control in China and integrated with the practical experience and innovative practices of Wuhan National Demonstration Area for Student Vision Health Management, takes education as the main thread and schools as the base, consolidating resources from multiple stakeholders including education administrative departments, schools, families, and professional technical service institutions. Centering on four core components—vision health education, monitoring and record keeping, risk prevention and control, and dynamic management, the study constructs a multi tiered basic public service system for vision health management of primary and secondary school students. It further proposes the use of an intelligent management platform and a "three tier color coded early warning" mechanism (red, yellow, blue) to prevent and control student myopia at the source, providing schools with replicable and operable implementation pathways to enhance the level of student vision health management.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveGliomas in the motor functional area can damage the corticospinal tract (CST), leading to motor dysfunction. Currently, there is a lack of unified methods for evaluating the extent of CST damage, especially in patients with high surgical risk where the minimum distance from the lesion to the CST is less than 10 mm. This study aims to further clarify the classification method and clinical significance of CST morphological changes in these patients. MethodsThis retrospective study analyzed 109 high-risk functional area glioma patients who underwent neurosurgical treatment with preoperative diffusion tensor imaging (DTI) imaging and intraoperative neurostimulation guidance between 2014 and 2024. All patients had a lesion-to-tract distance (LTD) of less than 10 mm between the CST and the lesion. Preoperative DTI evaluation of CST involvement-induced morphological changes were reviewed. Patients were divided into 3 groups: 17 cases (15.6%) with symmetric CST morphology compared to the healthy side (CST symmetry), 48 cases (44.0%) with significant CST morphology changes compared to the healthy side (CST deformation), and 44 cases (40.4%) with CST overlap with the tumor (CST overlap). Then we classified patients according to preoperative assessment of tumor-induced morphological changes, and analyze postoperative motor function for each category. ResultsPostoperative pathology showed a significantly higher proportion of high-grade gliomas (HGG) in the CST overlap group compared to the other two groups (P=0.001). Logistic regression analysis showed that CST overlap was a predictor of HGG (P=0.000). The rate of total tumor resection in the CST deformation group and overlap group was lower than in the CST symmetric group (P=0.008). There was a total of 41 postoperative hemiplegic patients, with 4 cases (23.5%) in the CST symmetric group, 11 cases (22.9%) in the CST deformation group, and 26 cases (59.1%) in the CST overlap group. CST overlap with the tumor predicted postoperative hemiplegia (P=0.016). Two-way ANOVA analysis of the affected/healthy side and CST morphology groups showed significant main effects of CST grouping and healthy-affected side (P=0.017 and P=0.010), with no significant interaction (P=0.31). The fractional anisotropy (FA) value in the CST overlap group and the affected side was lower. A decrease in the FA value on the affected side predicted postoperative hemiplegia (sensitivity 69.2%, specificity 71.9%). ConclusionWe have established a method to predict postoperative hemiplegia in high-risk motor functional area glioma patients based on preoperative CST morphological changes. CST overlap leads to a decrease in CST FA values. This method can be used for precise patient management and aid in accurate preoperative surgical planning.

Objective To analyze the health effects of long-term occupational exposure to ionizing radiation on radiation workers in a nuclear power plant, and to provide a scientific basis for their occupational health monitoring. Methods In 2023, 183 radiation workers in a nuclear power plant were subjected to the analysis of blood cell parameters such as mean red blood cell count, white blood cell count (WBC), lymphocyte count, and hemoglobin count, thyroid function indicators such as serum triiodothyronine, thyroxine, and thyrotropin, as well as the chromosomal aberration rate and micronucleus rate of the lymphocytes in the peripheral blood. Results The blood cell parameters, thyroid function indicators, chromosomal aberration rate, and micronucleus rate of these radiation workers in the nuclear power plant were within normal reference ranges. Comparison among radiation workers with different ages showed statistically significant differences in triiodothyronine (H = 6.98, P < 0.05) and micronucleus rate (H = 48.44, P < 0.05). Among the three groups of radiation workers with different working years, WBC was significantly different (χ² = 3.87, P < 0.05), with the lowest WBC observed in radiation workers with ≥ 20 years of service. Thyroxine (χ² = 4.01, P < 0.05) and micronucleus rate (H = 40.95, P < 0.05) also varied significantly among these three groups. Conclusion Thyroid triiodothyronine level and micronucleus rate were affected by age, while WBC, thyroid thyroxine level, and micronucleus rate were related to working years. Targeted health management should be carried out for radiation workers in nuclear power plants to improve the awareness of radiation protection and continuously enhance their health status.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

This study examines the progress and application of Artificial Intelligence (AI) in the prevention and control of infectious diseases within Chinese healthcare institutions. It analyzes the difficulties and challenges encountered during implementation to promote the intelligent transformation and upgrading of infectious disease prevention and control. The results indicate that AI technology has made progress in areas such as infectious disease surveillance and early warning, risk assessment and emergency response, screening and detection, image-based diagnosis and analysis, and health management. Nevertheless, significant challenges remain, including limited application depth and breadth, issues with data quality and privacy protection, insufficient technological maturity and interpretability, potential legal risks, and a shortage of interdisciplinary professionals. To advance the application of AI technology in infectious disease prevention and control and support the modernization of China′s relevant systems, recommendations include strengthening policy support, establishing data standards and robust privacy protection mechanisms, increasing R&D investment, refining laws and regulations, and enhancing the training of interdisciplinary talent.

Lean six sigma (LSS) emphasizes patient demand-oriented, and continuously optimizing prolesses to achieve efficiency and standardization in medical services. Starting in 2021, a specialized children′s hospital (comprising one main campus and three branch campuses) introduced the LSS management method. Through define, measure, analyze, improve, and control, the hospital utilized tools such as questionnaire surveys, SIPOC models, and fishbone diagrams to identify pain points in the building of multi-campus child-friendly hospital and develop improvement measures.To address the main issues of insufficient cross-campus collaboration, significant disparities in service quality among different campuses, unclear functional positioning of each campus, and inadequate integration with social security mechanisms, the hospital implemented a " homogeneity-differentiation-coordination" management mode. The hospital implemented unified diagnosis and treatment standards and clinical pathways, carried out remote consultations and expert rotations, completed mutual recognition of examination and testing results, optimized child friendly labeling and child friendly environment, and built a " hospital-to-hospitals, hospital to medical schools, and hospital to community health centers" linkage platform, etc., to promote the standardization of diagnosis and treatment processes, clear functional positioning of the hospital area, and efficient resource allocation. Through practice, the outpatient appointment rate and patient satisfaction rate in the main hospital had increased from 86.72% and 98.64% in January December 2021 to 91.87% and 99.72% in January December 2024, respectively; The patient waiting time had been shortened from 26.54 minutes to 21.94 minutes, and the efficiency of medical treatment and service experience had been significantly improved. As of 2024, mutual recognition of 214 inspection and testing items had been achieved cross hospital campuses, forming a collaborative pattern of " main hospital leading, campuses support, and resource complementarity", and significantly improving the level of collaboration and child friendly connotation among multi-campus. This practice explored the integration path of multi-campus collaborative governance and child-friendly services, which could provide reference and inspiration for the similar hospitals.

Objective To design a VR-based air evacuation training system for simulating the on-board medical treatment process during air evacuation.Methods A VR-based air evacuation training system was developed which used 3D modeling technology to construct models of the medical aircraft cabin,medical devices and virtual characters to achieve scene interaction.The hardware part of the system included server computers,training terminal computers,VR equipment,3D fusion projection equipment,motion capture equipment,etc.The software of the system was developed using C++,UE4 Blueprint and C# programming languages,including two modules for medical treatment unit and medical treatment training process evaluation.The efficacy of the system was verified by the trials in air evacuation.Results The system developed successfully simulated the scenarios of tracheal tube dislodgement and increased intracranial pressure in the scenario model of open severe craniocerebral injury.The expert evaluation showed that the system gained advantages in training efficiency,low cost,safety,sense of immersion and recorded the operation data in real time to optimize the follow-up training.Conclusion The system developed delivers a virtual training environment with high-fidelity replication of real-mission conditions,enabling whole-course and immersive air evacuation drills.[Chinese Medical Equipment Journal,2025,46(3):15-20]