ObjectiveBiochemistry and Molecular Biology, a discipline that elucidates life phenomena at the molecular level, serves as a core foundational course in medical education. It provides the theoretical basis for studying other basic and clinical medical subjects, as well as for understanding pathogenesis, disease diagnosis, and treatment. However, its complex content and highly abstract concepts have posed a dual challenge to traditional teaching models: “inefficient instruction” and “inadequate learning outcomes”. Within limited classroom hours, how to engage students and stimulate their intrinsic motivation, and how to help them recognize, understand, and develop a passion for biochemistry from the perspective of the discipline’s essence, have long been key focuses of curriculum research. MethodsUsing the lipid metabolism chapter as an example, this study employs “Rain Classroom”, a generative artificial intelligence (AI)-assisted platform, to support education in four dimensions: teaching, learning, evaluation, and research. In teaching, it assists instructors through virtual experiments, lesson preparation support, knowledge mapping, and assignment design. For learning, it serves as an intelligent study assistant for students, providing automated assignment review, enabling educational resource sharing, and facilitating personalized learning pathways. In evaluation, the platform automates assignment grading, analyzes student performance data, and offers diagnostic feedback and teaching recommendations. In research, it aids educators in collecting and analyzing teaching data, as well as searching for and summarizing relevant literature. ResultsThe results indicate that an educational model integrating teacher-led instruction, student-centered learning, and generative AI assistance significantly enhances teaching quality, students’ self-directed learning abilities, and knowledge mastery. Furthermore, with the support of generative AI, curriculum-based ideological education—focusing on cutting-edge disciplinary advances and topical medical issues—helps cultivate students’ medical spirit of “honoring life and healing the wounded”, thereby fostering the establishment of appropriate professional values. Finally, while generative AI presents both opportunities and challenges for higher education, this study also analyzes potential risks in its teaching applications, emphasizing the need for both instructors and students to avoid over-reliance and to ensure that technological tools consistently serve the fundamental goals of education. ConclusionThis study demonstrates that integrating generative AI, specifically via the “Rain Classroom” platform, can effectively enhance biochemistry education. By supporting teaching, learning, evaluation, and research, this approach improves both educational effectiveness and student outcomes. It also facilitates the incorporation of cutting-edge knowledge and professional ethics, nurturing a patient-centered mindset. Additionally, the study addresses potential implementation risks to ensure that such technological tools remain aligned with the core purpose of education.

Objective To investigate the value of 3.0 T MRI in-phase/opposed-phase (IP-OP) imaging features in the quantitative assessment of hepatic steatosis after liver transplantation. Methods Clinical data of 115 patients who underwent liver transplantation and completed MRI IP-OP examination and liver biopsy within 3 months were retrospectively collected. According to the gold standard of pathological results, patients were divided into the steatosis group (n=18) and the non-steatosis group (n=97). The relative signal intensity of hepatic parenchyma was measured on MRI IP-OP sequences, and the hepatic fat fraction (HFF) was calculated. Differences in clinical data and imaging features between the two groups were compared, and the efficacy of HFF in the diagnosis of graft hepatic steatosis was evaluated using the receiver operating characteristic (ROC) curve. Results Among the 115 recipients, 18 cases were diagnosed with hepatic steatosis by liver biopsy, including 13 cases of mild steatosis, 3 cases of moderate steatosis and 2 cases of severe steatosis. Compared with the non-steatosis group, the steatosis group had a lower proportion of hepatitis B virus (HBV)-related hepatocellular carcinoma, higher proportions of HBV-related liver failure and alcoholic liver cirrhosis, and higher platelet levels (all P<0.05). There were statistically significant differences in hepatic imaging features between the two groups (all P<0.05). The ROC curve showed that the area under the curve (AUC) of the quantitative value calculated by IP-OP in the diagnosis of graft hepatic steatosis was 0.925 (95% confidence interval 0.870-0.980). Conclusions 3.0 T MRI IP-OP sequence may accurately and non-invasively quantitatively assess the severity of hepatic steatosis after liver transplantation, which is of great value for the early detection of graft hepatic steatosis and the guidance of clinical intervention.

[摘 要] 目的：探究着丝粒蛋白M（CENPM）在脑胶质瘤中的表达特征、临床预后价值及其对肿瘤恶性生物学行为的调控机制，为脑胶质瘤的精准治疗提供潜在靶点。方法：基于中国胶质瘤基因组图谱（CGGA）和癌症基因组图谱（TCGA）数据库分析CENPM在胶质瘤中的表达及其与患者临床病理特征和预后的相关性。通过基因本体论（GO）分析、京都基因与基因组百科全书（KEGG）富集分析和单细胞转录组分析探索CENPM的生物学功能和作用机制。WB法检测CENPM在胶质瘤细胞（LN-18、LN-229、U-138MG、U-251MG）和正常胶质细胞（HEB）中的表达；构建CENPM敲低细胞后，通过CCK-8、集落形成、Transwell和划痕实验评估恶性表型改变。结果：CENPM在WHO高级别胶质瘤中呈高表达（P < 0.05），与肿瘤恶性程度正相关。高表达组患者总体生存期显著短于低表达组（P < 0.01），Cox回归证实CENPM是影响胶质瘤患者预后的独立危险因素（P < 0.05）。功能富集分析结果显示CENPM相关基因主要富集于细胞周期调控、PI3K-Akt通路和免疫相关过程。单细胞分析结果显示CENPM主要在CD8⁺ T细胞高表达，并通过PTN-PTPRZ1/NCL配受体调控细胞通信。体外实验证实CENPM在胶质瘤细胞表达高于正常胶质细胞（LN-18：P < 0.01，LN-299：P < 0.05）；敲低CENPM显著抑制迁移（P < 0.05），但增强集落形成，提示其在肿瘤进展中的双重调控作用。结论：CENPM作为胶质瘤独立预后危险因子，通过调控细胞周期、PTN通路和免疫微环境驱动肿瘤进展，其差异化调控机制（抑制迁移、促进增殖）具有潜在的临床转化价值，可作为分子分型和靶向治疗候选标志物。

Background: High-mobility group box protein 1 (HMGB1) is a chromatin-binding protein involved in arthritis, ischemia, sepsis, atherosclerosis, neurodegenerative disorders, meningitis, and cancer. HMGB1 exhibits dual roles in cancer, acting as either a tumor suppressor or oncoprotein depending on context. Objective: This research aimed to elucidate HMGB1’s functional significance in cutaneous squamous cell carcinoma (cSCC). Methods: We overexpressed HMGB1 in cSCC cell lines using recombinant adenovirus and examined its effects on cell proliferation, colony formation, and cell migration. Results: Immunohistochemical analysis revealed elevated HMGB1 expression levels in cSCC tissue relative to normal epidermis. To assess the influence of HMGB1, we employed recombinant adenoviruses expressing HMGB1 to transduce SCC cell lines (SCC12 and SCC13). Enhanced HMGB1 expression significantly promoted cellular proliferation and colony formation capacity.Notably, HMGB1 overexpression elevated the levels of proliferation regulators, including P63, SOX2, CDK4 and CDK6. Furthermore, HMGB1 overexpression substantially enhanced tumor invasiveness, accompanied by upregulation of epithelial-mesenchymal transition (EMT) biomarkers. Mechanistically, overexpression of HMGB1 enhanced transforming growth factor-β signaling by increasing phosphorylation of SMAD2/3, the key mediators of EMT. Conclusion These data imply that HMGB1 acts as a tumor-promoting factor in cSCC.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

To address the growing challenge of an increasing number of elderly lung cancer patients amidst China's aging population and to fill the gap in quality control standards for surgical treatment in this special population, this study aimed to develop a standardized surgical evaluation system for elderly lung cancer patients tailored to China's national conditions. The system was established through a literature review, integrated the pathophysiological characteristics of elderly patients, and was constructed following review, feedback, and revision by experts from multiple thoracic surgery centers. Employing a 100-point scoring system, it comprises three primary domains: physical infrastructure and geriatric adaptability foundational conditions (10 points); management level and perioperative care models (20 points); and technical proficiency and clinical outcomes (70 points). The system places a strong emphasis on geriatric adaptability, proposing specific, quantifiable indicators for age-friendly facility modifications, control of elderly-specific complications, multidisciplinary collaboration, and standardized perioperative management. It provides a convenient and measurable assessment tool for quality control in the surgical treatment of elderly lung cancer in China, which is expected to promote the standardization and homogenization of diagnosis and treatment.

OBJECTIVE To investigate the current status of informatization tools applied to antimicrobial stewardship in county hospitals in China， and to provide a reference for promoting the informatization development of antimicrobial stewardship in county hospitals.METHODS From August to September 2025， an online questionnaire survey was conducted among 1 007 county hospitals across 31 provinces（autonomous regions， and municipalities） in China. The survey focused on the application of four types of informatization tools：the real-time monitoring system for antimicrobial use， the pre-prescription review system， the irrational use warning system， and the electronic prescription evaluation system（hereinafter referred to as the “monitoring system”“review system”“warning system”“evaluation system”，respectively）. Correlation analysis and binary Logistic regression analysis were employed to explore the influencing factors.RESULTS Of the county hospitals， 80.83% were equipped with at least one type of informatization tool for antimicrobial stewardship， while 19.17% had no relevant tool. Only 18.87% of the hospitals were equipped with all four types of tools. The monitoring system exhibited the highest equipped rate （70.80%）， whereas the warning system was equipped in only 33.96% of the hospitals. Four types of tools are evenly and adequately deployed in the eastern region， the central and western regions have far lower deployment rates of intervention tools including review system and warning system， accompanied by prominent intra-provincial gaps. The total number of the health technicians， hospital grade， and prescription review rate of outpatient antibacterial drug were significantly and positively correlated with the deployment rates of the four informatization tools （ P ＜0.05）. The results of the Logistic regression model fitting indicated that the model of the review system was rated “excellent” [area under the receiver operating characteristic curve （AUC）＝0.81]， and the model of the warning system was rated “further improvement” （AUC＝0.67）. The total number of health technicians was significantly positively correlated with the deployment rates of all four types of informatization tools （all P ＜0.05）.CONCLUSIONS The informatization of antimicrobial stewardship in county hospitals in China remains in the initial stage of transitioning from “passive statistics” to “active prevention and control”， with challenges such as structural imbalance and regional disparities. In the future， differentiated support strategies should be implemented， the allocation of resources should be optimized， to enhance the level of refined antimicrobial stewardship.

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.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Objective To evaluate the value of postoperative radiotherapy (PORT) in patients with stage ⅢA-N2 non-small cell lung cancer who received complete resection and chemotherapy. Methods Patients with stage ⅢA-N2 non-small cell lung cancer who received complete resection and chemotherapy were chosen from the SEER Research Plus Database [17 Registries, November 2012 Submission (2000-2019)]. The patients were divided into a PORT group and a non-PORT group according to whether the PORT was used. To balance baseline characteristics between non-PORT and PORT groups, R software was used to conduct a propensity score matching (PSM) with a ratio of 1 : 1 and a matching tolerance of 0.01. Both the Cox regression analysis and Kaplan-Meier survival analysis were conducted to evaluate the value of PORT in terms of overall survival (OS) and disease-specific survival (DSS). Results In total, 2468 patients with stage ⅢA-N2 non-small cell lung cancer were enrolled, including 1078 males and 1390 females with a median age of 65 (58-71) years. There were 1336 patients in the PORT group, and 1132 patients in the non-PORT group. Cox regression analysis showed that PORT was not significantly associated with OS (multivariate analysis: HR=1.051, 95%CI 0.949-1.164, P=0.338) and DSS (multivariate analysis: HR=1.094, 95%CI 0.976-1.225, P=0.123). No statistical difference was found in the OS or DSS between non-PORT group and PORT group after PSM analysis (P＞0.05). Conclusion PORT does not have a survival benefit for patients with stage ⅢA-N2 non-small cell lung cancer who received complete resection and chemotherapy.