Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Background Prenatal exposure to fine particulate matter (PM_2.5) is closely associated with cortical damage and neuroinflammation in offspring. The cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway is a key regulator of inflammation and may be subject to epigenetic regulation. Objective To investigate the role of cGAS-STING pathway activation in PM_2.5-induced cortical damage in offspring mice during pregnancy and the underlying epigenetic regulatory mechanisms. Methods Open field tests were used to assess depressive-like behavior in offspring mice. Morphological analysis was conducted to evaluate cortical damage and microglial activation in offspring brains. Real-time fluorescent quantitative PCR (RT-qPCR) and Western blot (WB) were performed to detect changes in the expression of key molecules in the cGAS-STING pathway in cortical tissue. A PM_2.5-induced microglial cell injury model was established in BV2 cells. Microglial activation was observed, cell viability was measured using the Cell Counting Kit-8 (CCK-8), and the expression levels of inducible nitric oxide synthase (iNOS) and key molecules in the cGAS-STING pathway were detected by RT-qPCR and WB. Bioinformatics analysis was performed to explore the epigenetic regulatory association between the STING signaling pathway and lysine-specific demethylase 5A (KDM5A). Changes in KDM5A mRNA and protein expression, as well as the protein level of histone H3 lysine 4 trimethylation (H3K4me3), were detected in an in vitro PM_2.5 injury model. Using small interfering RNA (siRNA) technology, the KDM5A gene was silenced in BV2 cells exposed to PM_2.5. The protein expression of H3K4me3 was detected to evaluate improvements in microglial activation, changes in inflammatory markers such as iNOS and mannose receptor (CD206), and alterations in the cGAS-STING pathway. Results Compared with the control group, the total distance of offspring mice in the PM_2.5 group was significantly reduced, and both the distance traveled and the time spent in the central area of the open field were significantly decreased (P<0.01, P<0.001), indicating depressive-like behavior in the offspring mice. Compared with the control group, the offspring mice in the PM_2.5 group exhibited disorganized cortical structure and significantly activated microglia (P<0.01), with significantly increased mRNA and protein levels of cGAS and STING (P<0.05, P<0.01, or P<0.001). The in vitro experiments demonstrated that the PM_2.5 treatment induced BV2 cells to polarize toward the M1 phenotype, exhibiting a distinct amoeboid morphology, with upregulated expression of the pro-inflammatory factor iNOS (P<0.05, P<0.01, or P<0.001) and activation of the cGAS-STING pathway (P<0.05, P<0.01). The analysis of RNA-seq data from KDM5A knockout cells revealed significantly downregulated STING expression, suggesting that KDM5A may activate the STING signaling pathway. The in vitro experiments further confirmed that the PM_2.5-treated BV2 cells exhibited significantly elevated mRNA and protein levels of KDM5A (P<0.01), while the H3K4me3 protein levels were markedly reduced (P<0.05). After silencing KDM5A in BV2 cells exposed to PM_2.5, compared with the PM_2.5+siNC group, the PM_2.5+siKDM5A group showed no obvious microglial activation and polarized toward the M2 phenotype, with significantly decreased expression levels of iNOS, cluster of differentiation 16 (CD16), and interleukin-1β (P<0.05, P<0.01), and significantly increased expression levels of anti-inflammatory factors CD206, YM1, and interleukin-10 (P<0.01, P<0.001). Meanwhile, the expression levels of cGAS and STING were also reduced (P<0.05, P<0.01). Conclusion KDM5A activates microglia through the cGAS-STING pathway, thereby contributing to PM_2.5-induced cortical damage in offspring mice during pregnancy.

Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Chronic obstructive pulmonary disease （COPD） is a chronic respiratory disease that poses a significant threat to global health， exhibiting high morbidity， disability and mortality rate， with its prevention and treatment situation becoming increasingly critical. The pathogenesis of COPD is complex， and the underlying cellular and molecular biological mechanisms remain incompletely elucidated. Programmed cell death （PCD） is the process wherein cells actively undergo demise to maintain internal environmental stability in response to certain signals or specific stimuli. Contemporary medical research indicates that the dysregulation of PCD patterns such as apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis is closely related to the onset and progression of COPD. Clarifying the molecular mechanisms of PCD in COPD may provide novel perspectives for in-depth understanding and prevention of the disease. Traditional Chinese medicine （TCM） is characterized by holistic regulation. In recent years， extensive research has been conducted in the TCM field focusing on modulating apoptosis， necroptosis， pyroptosis， autophagy， and ferroptosis for the treatment of COPD， yielding remarkable achievements. Therefore， this study systematically explored the molecular mechanism of PCD in COPD and reviewed the potential mechanisms and intervention status of TCM targeting PCD in COPD， aiming to provide insights and references for the clinical prevention， treatment and in-depth research of COPD.

Modern cataract surgery has completely moved beyond the traditional vision-restoring model and has fully entered a new era of refractive cataract surgery(RCS)centered on precise refractive correction. Its core objective is to provide patients with personalized visual experiences characterized by full-range, clear, and comfortable vision. Currently, although diagnostic and therapeutic technologies for RCS are rapidly evolving, there remain many bottlenecks in the precise management of the entire perioperative process that urgently need to be addressed. Preoperatively, the measurement consistency among ocular biometry devices based on different detection principles remains poor, and systematic measurement errors cannot be completely eliminated. Moreover, the individualized selection of intraocular lenses(IOLs)relies heavily on surgeons' clinical experience, lacking a standardized quantitative decision-making framework, which makes it difficult to achieve precise personalized matching. Intraoperatively, the quality of continuous curvilinear capsulorhexis is affected by multiple factors such as ocular anatomical characteristics and surgical proficiency, and its stability cannot be reliably ensured. Various intelligent surgical navigation systems are compromised by intraoperative ocular conditions, and their clinical performance fails to meet theoretical expectations. At the postoperative stage, existing IOL optical designs and materials have inherent limitations. The longterm prevention and control of posterior capsule opacification(PCO)remains a core factor restricting patients' long-term high-quality visual outcomes. This article systematically reviews the precise diagnostic and therapeutic challenges and core bottlenecks across the preoperative, intraoperative, and postoperative stages of RCS. It further explores frontier technological directions—including cross-device error compensation models, artificial intelligence-assisted decision-making, preoperative VR-based visual simulation, and the construction of intelligent surgical ecosystem platforms—to delineate targeted solutions and optimization pathways. This review aims to provide references and insights for the standardized clinical implementation, technological innovation, and future research endeavors in precision diagnosis and treatment of RCS.

Objective:To evaluate the diagnostic value of non-targeted detection of metabolic fingerprinting in pulmonary nodules and to analyze the clinical effective model of multi-omics for assessing the malignant risk of pulmonary nodules.Methods:A total of 73 patients who underwent chest CT and completed pathological diagnosis and non-targeted detection of metabolic fingerprinting at Shandong Provincial Hospital Affiliated to Shandong First Medical University from November 2021 to October 2024 were selected as the research subjects. According to the postoperative histopathological diagnosis, the patients were divided into the lung malignant nodule group (61 cases) and the lung benign nodule group (12 cases). General clinical data of the patients, including sex, age, smoking history, and family history of tumors, as well as imaging data, including nodule density, nodule size, nodule location, nodule number, and special imaging manifestations (spiculation, lobulation, vacuole sign, vascular convergence sign, etc.), and non-targeted detection of metabolic fingerprinting results were collected. The above data were compared between the two groups of patients, and the receiver operator characteristic (ROC) curve was drawn to evaluate the predictive value of each model. Results:There were statistically significant differences in age ( t=4.41, P<0.001), nodule size ( Z=2.67, P=0.008), nodule density ( χ2=4.64, P=0.031), and spiculation ( χ2=7.67, P=0.006) between the lung malignant nodule group and the lung benign nodule group. There were no statistically significant differences in sex, smoking history, family history of lung cancer, nodule number, nodule location, lobulation, vacuole sign, vascular convergence sign, pleural indentation sign, calcification sign, bronchial truncation sign, vascular supply sign, and bronchial air sign (all P>0.05). The number of non-targeted detection of metabolic fingerprinting high-risk patients in the lung malignant nodule group (36 cases) was significantly higher than that in the lung benign nodule group (0 case) ( χ2=13.97, P<0.001). ROC curve analysis showed that the area under the curve of the Brock model combined with non-targeted detection of metabolic fingerprinting was 0.930 (95% CI: 0.872-0.988), which was greater than that of the Brock model (0.856, 95% CI: 0.769-0.942, Z=0.27, P=0.040) and non-targeted detection of metabolic fingerprinting (0.768, 95% CI: 0.650-0.887, Z=0.30, P=0.004) alone. Conclusions:Non-targeted detection of metabolic fingerprinting risk assessment may serve as a non-invasive method to assist the Brock model in the diagnosis of pulmonary nodules and has good application value. The combination of the Brock model and non-targeted detection of metabolic fingerprinting can more accurately distinguish the benign and malignant nature of pulmonary nodules.

Facing of mounting resource constraints and rising demands for personalization in medical education,regional anatomy teaching urgently requires transformation.In this paper,we focus on the regional anatomy of the thoracic wall,in order to explore a novel AI-driven teaching paradigm.Anchored in the core principle of"virtual-real integration with cadaveric dissection as the cornerstone,"the paradigm redefines educational objective and constructs an intelligent,closed-loop teaching model integrating students,computers,and instructors.Leveraging the robust support of digital intelligence(e.g.,DeepSeek),this paradigm incorporates interactive method including group collaboration,branching instruction,and gamified assessments.It achieves a comprehensive intelligent transformation of the entire teaching process-from goal setting and plan customization to activity implementation,task completion,outcome exchange,multidimensional evaluation,and reflective iteration.This new paradigm centers on medical students and leverages digital intelligence to activate deep personalized learning potential.It seamlessly integrates fundamental anatomical knowledge with clinical scenarios(e.g.,key anatomy in breast cancer surgery,flap design in breast reconstruction),and significantly enhances clinical decision-making abilities,scientific research and innovative thinking,as well as medical humanistic literacy,paving a new path for intelligent medical education.

Objective To explore the integration value of mobile virtual reality devices in the classroom teaching of human anatomy,and to evaluate their potential impact on the in-depth construction of human anatomy knowledge,the cultivation of spatial cognitive ability,and the transformation of teaching paradigms from the perspectives of cognitive load theory and situated learning.Methods The undergraduate students majoring in clinical medicine in Peking University were selected as the research objects.Among them,students in grade 2019 were the control group,and students in grade 2022 were the experimental group,introducing movable virtual anatomy equipment and other teaching auxiliary method in theory and practice courses.The final exam scores of the two groups of students were compared,and a questionnaire survey was conducted for the experimental group after the course,and the survey result were statistically analyzed.Results The final examination result showed that the average score of the experimental group was 82.47±10.19,and the average score of the control group was 74.82±16.56,which was significantly higher in the experimental group than in the control group,with statistical significance(P＜0.05).The questionnaire survey result showed that compared with traditional classroom teaching,94.62％of students preferred the new auxiliary teaching mode such as VR,96.77％of students believed that VR assisted teaching could achieve the traditional teaching effect or better,95.7％of them think that it improved students' interest in learning human anatomy,and 98.92％thought that it improved students' knowledge of anatomy.Conclusion The application of mobile virtual reality devices in anatomy classroom teaching provides immersive and interactive 3D visualization teaching scenarios,effectively reducing students' cognitive load on abstract and complex anatomical structures,promoting spatial understanding and knowledge internalization,significantly improving teaching effectiveness and self-learning ability,thus changing the traditional anatomy teaching mode and laying a solid foundation for the development of future medical education and the cultivation of medical talents.

Objective To explore how to organically integrate the human anatomy curriculum with medical imaging,thereby enhancing medical students' spatial understanding and 3D reconstruction skills,and strengthening their anatomical foundation and clinical competence.This approach aims to bridge the gap between basic science and clinical practice while cultivating clinical thinking abilities.Methods In this study,the medical imaging knowledge was introduced into the anatomy curriculum in Peking University,enabling students to better understand the human body structure and its relationship to the clinical practice with aid of the ultrasound and MRI method.After the course concluded,we evaluated the examination result and learning satisfaction data from the anatomy course.Results The result showed that students provided positive feedback,showing increased interest in learning,enhanced initiative,significant improvement in their anatomy grades(P＜0.01),and a notable enhancement in their ability to apply basic knowledge to solve clinical problems(P＜0.05).Conclusion The integrated teaching approach of medical imaging and human anatomy courses provides innovative ideas and practical method for medical students to learn the basic medical course and enhance their clinical skills in the future.

BackgroundAttention deficit hyperactivity disorder （ADHD） is a neurodevelopmental disorder characterized by age-inappropriate inattention， excessive activities incongruous with setting， and emotional impulsivity. Subthreshold ADHD （sADHD） is clinically defined as the presence of ADHD symptoms that do not meet the full diagnostic criteria for ADHD. Children with sADHD exhibit deficits in executive function， demonstrate more conduct， learning， and anxiety-related problems compared to typically developing children， and show even poorer working memory performance than children diagnosed with ADHD. Currently， there is limited epidemiological research on sADHD in China， with few studies simultaneously investigating the prevalence of both ADHD and sADHD in children. ObjectiveTo investigate the prevalence of ADHD and sADHD among children aged 6–13 years in Chongqing， analyzing their distribution characteristics within this population， with the aim of providing references for developing preventive measures against both ADHD and sADHD. MethodsFrom October to November 2023， a total of 3 398 students in grades 1–6 from six primary schools in Jiangbei District， Chongqing were selected using a stratified cluster random sampling method. The occurrence of ADHD and sADHD was evaluated by using the short version （18-item version） of the Swanson， Nolan， and Pelham IV rating scales （SNAP-IV） and the Chinese vision of Schedule for Affective Disorder and Schizophrenia for School-aged Children-Present and Lifetime Version （K-SADS-PL）. ResultsThe ADHD detection rate among children in Chongqing was 1.90% （95% CI： 0.014–0.024）. Boys showed a significantly higher ADHD detection rate than girls （χ²=7.733， P=0.005）. No statistically significant differences were found in ADHD detection rates across different grades or age groups （χ²=7.347， 12.362， P>0.05）. The sADHD detection rate was 6.32% （95% CI： 0.054–0.072）. Similarly， boys exhibited significantly higher sADHD detection rates than girls （χ²=21.005， P<0.01）. Significant differences emerged across different grades （χ²=20.559， P=0.001）， while no statistically significant difference was observed in age groups （χ²=12.070， P=0.060）. ConclusionThe ADHD detection rates were comparable across all grade levels and age groups from 6–13 years old. Second-grade children demonstrated notably higher sADHD rates compared to other grades， while boys demonstrated higher prevalence rates than girls for both ADHD and sADHD. ［Funded by Science and Health Joint Medical Research Project in Jiangbei District， Chongqing City in the Second Half of 2023 （number， 2023JBKWLH022）］