Jinrong Zeng

T cell immunosenescence refers to the progressive functional decline of T lymphocytes with aging, characterized by the phenotypic markers, mitochondrial dysfunction, and the senescence‐associated secretory phenotype (SASP), representing a pivotal aspect of overall immune aging. This review systematically elucidates the critical role of T cell immunosenescence in the pathogenesis of common inflammatory skin diseases, including psoriasis, atopic dermatitis, rosacea, and seborrheic dermatitis. Senescent T cells drive the production of a disease‐specific SASP via internally dysregulated signaling networks such as NF‐κB, JAK‐STAT, p38 MAPK, and PI3K‐Akt‐mTOR pathways, thereby shaping and sustaining a chronic cutaneous inflammatory microenvironment that promotes disease chronicity and recurrence. Furthermore, this review summarizes current therapeutic strategies targeting these senescence‐associated pathways and SASP components, discussing both biological agents and small molecule inhibitors. Finally, we propose future research directions focusing on the direct targeting of senescent T cells or their upstream regulatory hubs to achieve deep disease remission and overcome therapeutic resistance.

Background: The research aimed to explore the application effectiveness, advantages, and disadvantages of Team-Based Learning (TBL) in undergraduate cosmetic dermatology education and to analyze directions for pedagogical improvement using interpretable machine learning (IML). Methods: A total of 154 undergraduate clinical medicine students from Xiangya School of Medicine, Central South University were included as study subjects. Using the cosmetic dermatology chapter (two teaching units) from the Dermatology and Venereology course, a comparative design was implemented between traditional Lecture-Based Learning (LBL) and interest-oriented TBL. Teaching feedback was collected through questionnaires, and IML and correlation analysis were applied to identify key nodes for pedagogical optimization. Results: Surveys showed that 83.8% of students reported increased learning interest, 84.4% were willing to engage in post-class self-directed learning, 81.2% were satisfied with the course, and 86.4% desired more TBL courses. Recognition of teaching components revealed that 87.0% preferred the presentation part, 89.0% endorsed the teamwork part, 80.5% agreed with the questioning part, and 95.5% valued the discussion part. Compared to LBL, TBL significantly improved self-directed learning capability ( P < 0.001) and knowledge mastery capability ( P = 0.004), but showed weaker improvement in independent thinking capability ( P = 0.028). IML revealed that the most important feature determining the enthusiasm for cosmetic dermatology and TBL was the enhancement of independent thinking capability. Course satisfaction was primarily influenced by improved self-directed learning capability. Correlation analysis indicated that the recognition of most teaching components positively correlated with learning interest in cosmetic dermatology and satisfaction with TBL, except that students with higher recognition of the Teamwork Part ( r = -0.432) and Questioning Part ( r = -0.900) paradoxically exhibited resistance to the implementation of additional TBL courses. Conclusion: TBL effectively enhances students’ learning interest and comprehensive competencies in cosmetic dermatology education, demonstrating strong potential for broader application. However, significant opportunities for refinement persist in instructional design.

Traditional teaching in undergraduate dermatology and venereology often prioritizes theoretical knowledge over clinical competency development. To address

With the continuous advancement of deep space exploration missions, maintaining astronaut skin health has become a critical medical issue affecting the safety and effectiveness of long-duration missions. Deep space environmental stressors, including microgravity, ionizing radiation, lunar dust exposure, and microbiome dysbiosis, can synergistically disrupt the skin barrier structure, leading to immune homeostasis imbalance and impaired wound healing. In recent years, research on skin protection in deep space has gradually evolved into a systematic "multi-dimensional integrated protective" framework. From the engineering protection perspective, optimization of multi-layer composite spacesuit structures, the use of hydrogen-rich and boron-containing shielding materials, as well as cabin temperature-humidity regulation and debris-resistant technologies, have greatly enhanced environmental defense capacity. From the biomedical protection perspective, functional hydrogels, antimicrobial dressings, and active compounds derived from traditional Chinese medicine have demonstrated remarkable potential in repairing the skin barrier, modulating immunity, and providing antioxidant defense. Meanwhile, the development of skin microecological interventions and wearable physiological monitoring systems has fostered a trend toward personalized health management. Future research should focus on elucidating the interactive mechanisms among the space environment, skin, and immune barrier, while exploring intelligent monitoring and nanotechnology-based protection strategies. Establishing a predictive and preventive skin health safeguarding system will provide comprehensive medical support for future deep space missions.

Depressive and anxiety disorders are among the most common mental disorders worldwide and are associated with unhealthy lifestyle behaviors. The Life's Simple 7 (LS7) guideline proposed by the American Heart Association aims to reduce cardiovascular risk by improving behaviors such as diet and physical activity, but its impact on mental health is not yet fully clear. This study examined the association between LS7 scores and symptoms of anxiety and depression in adults undergoing routine health examinations. Data were collected from individuals who underwent health examinations from May 2015 to December 2024 at the Health Management Center of the Third Xiangya Hospital. All participants completed the LS7 assessments, the Self-Rating Depression Scale (SDS), and the Self-Rating Anxiety Scale (SAS). Participants were categorized into 4 LS7 score groups: Low (≤7), average (8-9), good (10), and excellent (11-14). Those with SDS or SAS≥50 were classified as having mental disorder symptoms; with this group, SAS≥50 indicated anxiety, SDS≥50 indicated depression, and SDS and SAS≥50 indicated comorbid anxiety-depression. Binary logistic regression was used to assess associations between LS7 score and mental symptoms, calculating odds ratio (OR) and 95% confidence interval (CI). A restricted cubic spline (RCS) regression model was used to analyze the dose-response relationship between LS7 score (continuous variable) and the risk of mental symptoms. Nodes were set at the 5th, 35th, 65th, and 95th percentiles of the LS7 score, with the 5th percentile as the reference point. All models were adjusted for covariates such as gender, age, living alone, drinking status, education level, and sleep quality. Logistic regression framework was used to fit and calculate the adjusted OR (aOR) and 95% CI. Nonlinear relationship tests were also conducted. Subgroup analysis was performed to explore the interaction between gender, age, drinking habits, education level, and other factors and the LS7 score in influencing the risk of mental symptoms. A total of 5 449 participants were included; 1 363 (25.01%) had depressive symptoms, 398 (7.30%) had anxiety symptoms, and 259 (4.75%) had comorbid anxiety-depression. The prevalence of mental symptoms decreased significantly as LS7 scores increased. Univariate and multivariate Logistic regression indicated that LS7 score≥8 was protective against mental symptoms. Multivariate Logistic regression demonstrated moderate discriminative ability (AUC=0.672). Among individuals with anxiety, depression, or comorbid symptoms, LS7 score distributions showed a graded decrease from poor to excellent groups. After adjustment, an excellent LS7 score was associated with a 39% lower risk of depression (aOR=0.61, 95% CI 0.47 to 0.78, PaOR=0.37, 95% CI 0.22 to 0.59, PaOR=0.34, 95% CI 0.17 to 0.62, P=0.001). The AUC values of the anxiety model, depression model, and comorbid anxiety and depression model were 0.632, 0.672, and 0.619, respectively. All models demonstrated moderate discriminatory ability, which was statistically significant, but their capacity to distinguish cases from non-cases was limited. RCS analysis confirmed a linear inverse relationship between LS7 score and mental symptom risk. Not smoking and regular physical activity were the strongest protective behaviors. Subgroup analysis suggested stronger protective effects in men, younger adults (≤60), non-drinkers, and those with higher education levels, and revealed a significant interaction between alcohol use and LS7 score (P for interaction=0.021), indicating that alcohol consumption may weaken the protective effect of LS7. Ideal healthy lifestyle behaviors, as reflected by higher LS7 scores, are associated with lower risks of anxiety and depression in adults. Promoting LS7-based lifestyle practices may serve as a practical and effective strategy for the prevention and management of anxiety and depression in both clinical and daily life settings.