OBJECTIVE To mine and analyze adverse event signals associated with inebilizumab， and to provide reference for safe and rational clinical use. METHODS Reports of adverse event related to inebilizumab were collected from the FDA adverse event reporting system （FAERS） database， from Q2 2020 to Q4 2024. Adverse events were standardized and categorized according to the preferred term （PT） and system organ class （SOC） of the Medical Dictionary for Regulatory Activities （MedDRA） version 26.0. Signals were mined using the reporting odds ratio （ROR） method and the Bayesian confidence propagation neural network （BCPNN） method. RESULTS A total of 783 adverse event reports with inebilizumab as the primary suspected drug were identified， involving 297 patients. Most reports originated from the United States and Japan， with physicians being the primary reporters. Female patients outnumbered males， and the most common age group was 45-64 years. Using the ROR method and BCPNN method， a total of 29 valid adverse event signals were detected， involving 12 SOCs and comprising 225 adverse event reports. The five most frequently reported PTs were headache， nausea， fatigue， infectious pneumonia and arthralgia. The five PTs with the strongest signal intensity were： B-cell recovery， decreased blood immunoglobulin G， spinal compression fracture， COVID-19 and acute respiratory distress syndrome. Among the 29 valid signals for adverse event， 19 were not documented in the drug package inserts， involving 10 SOCs and comprising 107 adverse event reports. These encompassed nervous system disorders， general disorders and administration site conditions， eye disorders， among others. CONCLUSIONS Inebilizumab treatment not only causes adverse events documented in the product information， such as infections， immunoglobulin reduction and infusion-related reactions but also leads to potential signals， including B-cell recovery， spinal compression fracture. When using this drug in clinical practice， the patient’s risk of infection and baseline immune status should be assessed， relevant indicators should be closely monitored， and targeted preventive measures should be considered when necessary.

ObjectiveTo investigate the mechanism by which Gegen Qinliantang（GQT） improves skeletal muscle insulin resistance. MethodsThe db/m mice were used as the normal group， while db/db mice were assigned to a model group， low-dose （3.12 g·kg^-1）， medium-dose （6.24 g·kg^-1）， and high-dose （12.48 g·kg^-1） GQT groups， and a Western medicine group （semaglutide， 0.045 mg·kg^-1），n=6 in each group. All groups received corresponding interventions. Intraperitoneal glucose tolerance test （IPGTT）， intraperitoneal insulin tolerance test （IPITT）， and hematoxylin-eosin （HE） staining were used to evaluate insulin resistance and therapeutic efficacy. Serum lipid levels were measured using an automatic biochemical analyzer， and apoptosis in skeletal muscle was assessed via TUNEL assay. Transcriptome sequencing combined with gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） analyses was performed to identify differentially expressed genes （DEGs）. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to validate gene expression. Molecular docking was applied to evaluate the binding patterns between active components of GQT and key regulatory genes to elucidate pharmacological mechanisms. ResultsCompared with the model group， the medium-dose and high-dose GQT groups showed significantly reduced fasting blood glucose （FBG） levels （P<0.01）. Triglycerides （TG）， total cholesterol （TC）， and low-density lipoprotein cholesterol （LDL-C） were markedly decreased （P<0.01）， while high-density lipoprotein cholesterol （HDL-C） was significantly increased （P<0.01）. IPGTT， IPITT， and HE staining demonstrated that GQT enhanced insulin sensitivity and restored skeletal muscle morphology. GQT also alleviated apoptosis in skeletal muscle tissue. Transcriptome analysis revealed that GQT primarily affected biological processes such as oxidative phosphorylation， metabolic pathways， cellular processes， and protein binding. Real-time PCR results showed that CBR2， CDK6， F830016B08Rik， IL-1β， Rab27b， and COLEC12 were key regulatory genes. Molecular docking demonstrated that CBR2， IL-1β， Rab27b， and COLEC12 formed stable binding with the main active components of GQT. The therapeutic effects of high- and medium-dose GQT were comparable to those of the semaglutide group. ConclusionGQT improves skeletal muscle insulin resistance， potentially by regulating apoptosis as part of its underlying biological mechanism.

Intravitreal anti-vascular endothelial growth factor(anti-VEGF)therapy has been widely used, but the variability in its therapeutic efficacy limits individualized treatment. In recent years, the application of artificial intelligence(AI)has opened up new avenues for personalized treatment response prediction, and its core branches include machine learning(ML)and deep learning(DL). This review systematically retrieved and analyzed 41 relevant studies published up to April 2025. Comprehensive analysis reveals that AI predictive models are evolving from forecasting single endpoints(such as visual acuity or central retinal thickness)to integrating multi-dimensional endpoints(encompassing anatomical, functional, and treatment demand parameters)and generating predictive imaging outputs. In terms of technical approaches, DL models(28 studies, accounting for 68.3%)dominate this field due to their robust image interpretation capabilities, while ML models(10 studies, 24.4%)retain significant value in the analysis of structured clinical data. Cross-disease comparisons indicate that research efforts are most concentrated on age-related macular degeneration(ARMD)and diabetic macular edema(DME), with shared conceptual frameworks for model construction, yet distinct anatomical and functional indicators are prioritized for each disease. Currently, the field confronts several key challenges, including insufficient prospective clinical validation, limited model interpretability(the “black box problem”), and a scarcity of high-quality multi-center datasets. Moving forward, it is imperative to advance real-world validation and develop explainable AI techniques to expedite the clinical translation of these predictive models.

Objective Orosomucoid1 （ORM1） is a novel target in the quest for anti-fatigue pharmacotherapy. Preliminary investigations have illuminated oleuropein （OLE） as a promising candidate molecule, poised to enhance ORM1 expression. To elucidate the influence of OLE on ORM1 protein expression and assess its ramifications on muscle endurance. Methods The impact of OLE on ORM1 protein expressions within hepatocytes and liver tissue was meticulously quantified through Western blotting; the effects of OLE on muscle endurance were evaluated via the rotarod and forced swimming tests; glycogen content within liver and muscle tissues was determined utilizing a specialized kit; and PAS staining was employed to visualize glycogen deposition in the gastrocnemius muscle. Results OLE demonstrated a capacity to elevate ORM1 protein expression in hepatocytes in a time- and dose-dependent manner, concurrently prolonging the duration of swimming and rotarod performance in mice, also in a time- and dose-dependent manner. Furthermore, OLE augmented ORM1 expression in liver tissue, elevated serum ORM1 levels, and enhanced glycogen reserves within the liver and muscle. Conclusion OLE may serve to amplify muscle endurance by elevating ORM1 levels in vivo and augmenting glycogen stores within skeletal muscle.

Patients with sudden deafness encounter greater psychological challenges and communication barriers after experiencing sudden hearing loss， and traditional medical models often fail to adequately address their unique needs. This paper analyzed the current situation of emotional and behavioral changes in patients with sudden deafness， and the gap between their expectations and the reality of medical care. From the perspective of narrative medicine， the theory and characteristics of the reconstruction of the doctor-patient relationships in patients with sudden deafness were explored. The results showed that narrative medicine can enhance patients’ emotional resonance and understanding， improve the efficiency and quality of doctor-patient communication， promote the formulation of personalized treatment plans， and enhance treatment adherence and satisfaction. Based on these results， strategies and pathways for the reconstruction of doctor-patient relationships for patients with sudden deafness were proposed， including building empathetic bridges and tapping into mechanisms of emotional resonance within narrative medicine； optimizing communication strategies and promoting the application of narrative techniques in doctor-patient dialogues； connecting narrative pathways and advocating the exploration of stories and strategies in personalized treatments； as well as facilitating treatment adherence and making full use of the psychodynamic effects of narrative medicine. Narrative medicine， as a patient-centered medical practice， can effectively promote the reconstruction of doctor-patient relationships， enhance treatment effectiveness， and offer a more humane treatment experience for patients.

In the strategic context of "healthy China"， the concept of "medicine and food homology"， rooted in the culture of traditional Chinese medicine （TCM）， has received unprecedented attention. In response to population aging in China， the health of the elderly has become the focus of public health attention， and proactive health is the key to healthy aging. From the perspective of the application of medicinal and edible materials in proactive health and technological responses to population aging for the first time， this paper firstly provided a systematic overview of medicinal and edible materials and the policies related to proactive health. Second， it summarized the situation of modern technology that accelerates the research and development of medicinal and edible products， as well as the current situation of various modern biotechnologies that reveal the mechanism of action of medicinal and edible materials. Third， it discussed the application scenarios of medicinal and edible materials in proactive health and technological responses to population aging， as well as the future research and development of medicinal and edible materials. By exploring in depth the unique value and importance of medicinal and edible materials， the paper lays a theoretical foundation for improving the health care capabilities of TCM and contributes new strategies derived from TCM to healthy aging.

Objective To evaluate the current status in the implementation of GBZ/T 201.5-2015 Radiation shielding requirements for radiotherapy rooms-Part 5: Radiotherapy room of proton accelerators, identify issues in the application of its technical indicators, and provide a basis for the in-depth implementation and further revision of the standard. Methods In accordance with the Standardization Law of the People’s Republic of China and the Guidelines for Health Standards Tracking Evaluation (WS/T 536-2017), a combination of cluster sampling and stratified sampling methods was employed to select professionals involved in proton accelerator radiotherapy devices and facilities in three provinces (or municipalities directly under the central government) as the subjects of the survey. A questionnaire was developed to collect basic information about the subjects and their understanding and application of the technical indicators in the standard. A standard evaluation indicator system with a total score of 100 points was established to score the implementation of the standard (40 points), the technical content (30 points), and the effectiveness of the implementation (30 points). Results A total of 169 professionals from 107 institutions participated in the survey, with 79.88% of the respondents having at least 5 years of experience in radiation therapy and 74.56% holding intermediate or higher professional titles. The score of standard implementation was 18.3 points. The awareness rate exceeded 80%, indicating a high level of awareness about the standard. However, the scores for the dissemination and application of the standard were relatively low, accounting for 28% and 32% of their respective full marks. The technical content of the standard and the effectiveness of its implementation scored 27.0 and 26.6 points, respectively. The overall score in the evaluation of standard implementation was 72 points, with scores of 68.6, 72.3, and 75.0 for Beijing City, Shanghai City, and Jiangsu Province, respectively. Conclusion GBZ/T 201.5-2015 Radiation shielding requirements for radiotherapy rooms-Part 5: Radiotherapy room of proton accelerators is scientific and operable, and it is well-coordinated with relevant laws and standards. However, considering the development in FLASH technology and multi-chamber radiotherapy room, it is necessary to revise and improve the standard.

Objective: To explore the feasibility of constructing a lung cancer early-warning risk model based on facial image features, providing novel insights into the early screening of lung cancer. Methods: This study included patients with pulmonary nodules diagnosed at the Physical Examination Center of Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from November 1, 2019 to December 31, 2024, as well as patients with lung cancer diagnosed in the Oncology Departments of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine and Longhua Hospital during the same period. The facial image information of patients with pulmonary nodules and lung cancer was collected using the TFDA-1 tongue and facial diagnosis instrument, and the facial diagnosis features were extracted from it by deep learning technology. Statistical analysis was conducted on the objective facial diagnosis characteristics of the two groups of participants to explore the differences in their facial image characteristics, and the least absolute shrinkage and selection operator (LASSO) regression was used to screen the characteristic variables. Based on the screened feature variables, four machine learning methods: random forest, logistic regression, support vector machine (SVM), and gradient boosting decision tree (GBDT) were used to establish lung cancer classification models independently. Meanwhile, the model performance was evaluated by indicators such as sensitivity, specificity, F1 score, precision, accuracy, the area under the receiver operating characteristic (ROC) curve (AUC), and the area under the precision-recall curve (AP). Results: A total of 1 275 patients with pulmonary nodules and 1 623 patients with lung cancer were included in this study. After propensity score matching (PSM) to adjust for gender and age, 535 patients were finally included in the pulmonary nodule group and the lung cancer group, respectively. There were significant differences in multiple color space metrics (such as R, G, B, V, L, a, b, Cr, H, Y, and Cb) and texture metrics [such as gray-levcl co-occurrence matrix (GLCM)-contrast (CON) and GLCM-inverse different moment (IDM)] between the two groups of individuals with pulmonary nodules and lung cancer (P < 0.05). To construct a classification model, LASSO regression was used to select 63 key features from the initial 136 facial features. Based on this feature set, the SVM model demonstrated the best performance after 10-fold stratified cross-validation. The model achieved an average AUC of 0.8729 and average accuracy of 0.799 0 on the internal test set. Further validation on an independent test set confirmed the model’s robust performance (AUC = 0.823 3, accuracy = 0.729 0), indicating its good generalization ability. Feature importance analysis demonstrated that color space indicators and the whole/lip Cr components (including color-B-0, wholecolor-Cr, and lipcolor-Cr) were the core factors in the model’s classification decisions, while texture indicators [GLCM-angular second moment (ASM)_2, GLCM-IDM_1, GLCM-CON_1, GLCM-entropy (ENT)_2] played an important auxiliary role. Conclusion The facial image features of patients with lung cancer and pulmonary nodules show significant differences in color and texture characteristics in multiple areas. The various models constructed based on facial image features all demonstrate good performance, indicating that facial image features can serve as potential biomarkers for lung cancer risk prediction, providing a non-invasive and feasible new approach for early lung cancer screening.

Objective: To explore the correlation between traditional Chinese medicine (TCM) constitution and depressive symptom among school aged children and adolescents, so as to provide evidences for informing constitution based regulation and prevention of depressive symptom. Methods: From June to December 2024, a total of 4 729 students aged 6-14 were recruited by cluster random sampling from 10 primary schools in Baoding (Hebei Province), Heze and Liaocheng (Shandong Province). General information, TCM constitution and depressive symptom were collected. Restricted cubic spline (RCS) models were used to analyze related factors and threshold effects of depressive symptom. Binary Logistic regression was applied to examine the association between depressive symptom and TCM constitution, with subgroup analyses conducted. Results: The detection rate of depressive symptom among the included children and adolescents was 25.82%. RCS analyses indicated non linear associations between depressive symptom and age (inflection point at 10 years old), bedtime (inflection point at 22:00), and wake up time (inflection point at 6:30 ) (all P non linearity <0.01). Linear associations were observed with body mass index (BMI) and sleep duration (all P non linearity > 0.05 ). After adjusting for covariates such as age, BMI and sleep status, binary Logistic regression analyses showed that Yin deficient constitution ( OR =1.26, 95% CI =1.09-1.45) and Phlegm-dampness constitution ( OR =1.42, 95% CI =1.11-1.82) were significantly associated with depressive symptom among children and adolescents (all P <0.05). Conclusions Depressive symptom among school aged children and adolescents is primarily associated with Yin deficiency and Phlegm dampness constitutions in TCM constitution. Active attention should be paid to susceptible TCM constitution among children and adolescents. Targeted health guidance and interventions should be implemented to improve TCM constitution health status for preventing the occurrence of depressive symptom.

Perinatal depression (PND) is a critical public health issue affecting maternal and offspring health. Digital health intervention platforms, leveraging advantages in accessibility, privacy, and cost-effectiveness, demonstrate good application in PND prevention and treatment. This review systematically searched literature and policy documents published between January 2018 and March 2025 in CNKI, PubMed, Web of Science and World Health Organization. It summarized the development trajectory of digital health intervention platforms and their current applications and effectiveness in PND prevention and treatment. Existing evidence was evaluated across dimensions of efficacy, systematicity, and practicality, identifying major challenges faced by these platforms. Studies indicate that while PND digital health intervention platforms have achieved preliminary success in alleviating PND symptoms, widespread issues persist, including incomplete service closed-loop systems, low user adherence, and insufficient sustainability. Future efforts should focus on optimizing intervention content and interactive design, advancing intelligent assessment and tiered intervention strategies, strengthening continuous monitoring and crisis response mechanisms, and constructing a multidisciplinary collaborative support system. These steps are essential for achieving efficient, intelligent, and sustainable development of digital health intervention platforms for PND.