The philosophy of “treating disease before its onset” is a fundamental concept of traditional Chinese medicine (TCM), permeating its diagnostic and therapeutic framework, and is central to clinical practice. However, current TCM diagnostic and treatment models for the “pre-disease to disease” window period face several limitations, including the lack of comprehensive clinical parameters, difficulties in characterizing and integrating heterogeneous multimodal data, and insufficient dynamic precision in interventions and efficacy evaluations. To address these issues, guided by Professor Candong Li’s theory of TCM stateology, this study focuses on integrating objective multimodal data. It proposes a new model for personalized TCM diagnosis and treatment targeting the “pre-disease to disease” window period. This approach first proposes the idea of restructuring the conceptual framework of “symptom” and integrating multi-source heterogeneous data at macroscopic, mesoscopic, and microscopic levels to form a three-dimensional assessment indicator system. By integrating graph neural networks, convolutional neural networks, attention mechanisms, and knowledge graph-guided weight allocation, this approach enables collaborative representation, alignment, and fusion of multi-source data. Subsequently, it plans to construct a multimodal fusion model at both feature and decision levels, in order to establish mappings between indicators and TCM state elements, and to screen key indicators characterizing pathological evolution during the window period. Furthermore, it proposes a technical path for enhancing model interpretability using methods such as SHapley Additive exPlanations (SHAP) and Ablation-CAM++. Finally, with state assessment as the core, it proposes the concept of constructing a dynamic evaluation method for individualized diagnosis and treatment based on time-series data analysis using algorithms such as long short-term memory (LSTM) networks and gated recurrent units (GRUs). Moreover, a causal inference framework and semi-supervised learning strategies are introduced to enable quantitative evaluation of individual intervention effects and to provide interpretable therapeutic feedback, forming a complete technical path from data representation and fusion, weight adjustment, and interpretability analysis, to dynamic diagnosis feedback. This study aims to address deficiencies in the current TCM diagnosis and treatment model during the “pre-disease to disease” window period and to provide an operational framework for the clinical practice of TCM’s “treating disease before its onset”.

Objectives: This review examines the nutritional challenges among Korean adolescents and young adults from life-course and behavioral science perspectives and proposes an integrated, community-based nutrition strategy for this critical transitional period. Methods: A narrative review was conducted following the Scale for the Quality Assessment of Narrative Review Articles guidelines. Literature published between January 2015 and June 2025 was retrieved from PubMed, Google Scholar, and Research Information Sharing Service using keywords related to adolescent and young adult nutrition, life course approaches, behavioral nutrition, and personalized nutrition. Policy documents from the World Health Organization, Food and Agriculture Organization of the United Nations, United Nations Nutrition, and Korean government agencies were also included. A total of 40 references (32 peer-reviewed articles and 8 policy reports) were analyzed. Results: Korean adolescents and young adults exhibited high rates of skipping breakfast (> 38.3%), obesity, and excessive sodium and sugar intakes, with disparities driven by socioecological determinants. The Developmental Origins of Health and Disease framework highlights adolescence as the “second window of plasticity” for reshaping long-term health trajectories. Two behavioral frameworks were synthesized: the Formation–Maintenance Model, distinguishing adolescent (Learn–Practice) and young adult (Sustain) stages, and the socioecological nutrition model, addressing multi-level influences on dietary behavior. A structural discontinuity in public nutrition support, termed the “School-to-Society Nutrition Gap,” was identified. Community-based, participatory, and digitally integrated interventions showed strong potential for sustaining behavioral change. Conclusion A personalized life-course nutrition strategy based on a Learn-Practice-Sustain framework was proposed. A Community-Linked Circular Nutrition Model was presented to bridge the gap between school-based and community-level nutrition systems, emphasizing nutrition equity and digital engagement as key drivers of sustainable health outcomes.

This issue of the Korean Journal of Aerospace and Environmental Medicine (Vol.36, No. 1) presents five articles addressing emerging topics in aerospace medicine, aeromedical evaluation, and space medicine policy. An original article proposes a neuro-adaptive cockpit communication support system integrating artificial intelligence and neurophysiological monitoring to reduce pilot cognitive workload and enhance situational awareness. Another original study examines the prevalence and aeromedical implications of cardiac conduction abnormalities among Korean Air Force pilots, providing evidence for risk-based surveillance strategies in aeromedical screening. A review article discusses the clinical value of the video head impulse test for quantitative assessment of vestibular function in pilots exposed to high-acceleration flight environments. Another review revisits the historical development and current relevance of the “1% rule,” a widely used framework for aeromedical risk assessment in aviation safety. Finally, a brief communication summarizes a panel discussion on the future development of space medicine in Korea, emphasizing interdisciplinary collaboration and national research governance.

Purpose: This study investigates the relationship between self-efficacy and teammember exchange (TMX) among aviation service students, and examines how these factors influence academic achievement and collaborative behavior. Self-efficacy, based on Bandura’s Social Cognitive Theory, is defined as an individual’s belief in their ability to overcome challenges, while TMX reflects the quality of social exchanges among team members. Methods: A convenience sample of undergraduate students from an aviation service department was recruited, yielding 65 valid responses. Self-efficacy was measured using the New General Self-Efficacy Scale along with additional validated items, and TMX was assessed with a TMX-10 scale, both utilizing a 5-point Likert scale. Data analysis included descriptive statistics, K-means clustering to identify behavioral segments, ANOVA for group comparisons, and regression analysis to explore the relationship between self-efficacy and TMX. Results: The analysis revealed four distinct behavioral clusters: confident collaborator, team player, reserved individual, and solo achiever. Results indicated that higher selfefficacy is associated with enhanced TMX and academic performance. Moreover, significant differences in self-efficacy and TMX scores were observed across the clusters, and regression analysis confirmed a positive relationship between selfefficacy and the quality of team interactions. Conclusion These findings highlight the importance of fostering both self-efficacy and effective team exchanges to optimize collaborative learning environments in aviation service education. Tailored educational interventions based on behavioral clustering can further enhance academic outcomes and prepare students for professional challenges.

Objective : To explore the causal relationship between 46 phenotypes ( including 15 seropositive case- control phenotypes and 31 quantitative antibody-measurement phenotypes) and ulcerative colitis( UC) using two- sample bidirectional Mendelian randomization( TSMR) . Methods: Single nucleotide polymorphisms ( SNPs) sig- nificantly associated with the relative abundance of the 46 antibody sera were extracted as instrumental variables ac- cording to preset thresholds . Summary statistics for UC were obtained from the OPEN GWAS database ( n = 47 745) . MR-Egger regression , weighted median method ( WME) , inverse variance weighting ( IVW) , the simple mode method (SM) , and weighted multitude method (WM) were used to estimate the causal relationship between antibody levels and UC , primarily using the IVW method . The results were assessed according to the effect indica- tor dominance ratios (OR) and 95% confidence intervals (CI) . Sensitivity analysis , heterogeneity test , gene plei- otropy test , and outlier test (MR-PRESSO) were combined to verify the stability and reliability of the results , and the causal association study was performed again using reverse Mendelian randomization(MR) . Results : IVW re- sults showed that Epstein-Barr( EB) virus EA-D antibody levels ( OR = 0. 806 , 95% CI = 0. 693 - 0. 939 , P < 0. 01) , Epstein-Barr virus EBNA-1 antibody levels ( OR = 1 . 870% , 95% CI = 1 . 480 - 2. 360 , P < 0. 000 1) , Anti-polyomavirus 2 IgG seropositivity (OR = 0. 570 , 95% CI = 0. 435 - 0. 746 , P < 0. 000 1) were associated with UC . The inverse MR analysis revealed a causal effect on anti-polyomavirus 2 IgG seropositivity , and none of the a- bove revealed genetic pleiotropy or significant heterogeneity of IVs . Conclusion EB virus EBNA-1 antibody levels are positively associated with the risk of UC , while EB virus EA-D antibody levels and anti-polyomavirus 2 IgG se- ropositivity are negatively associated with the risk of UC , indicating that they are protective factors for UC .

Objective: To elucidate the potential mechanisms by which Chinese herbal medicine (CHM) regulates gut microbiota (GM) to influence the development of primary open-angle glaucoma (POAG). Methods: Data mining, network pharmacology, and Mendelian randomization (MR) analyses (two-sample design) were conducted in integration to systematically explore the CHM-GM-POAG axis. Literature-based data mining method was applied to identify frequently used herbs and herb pairs for POAG, and the properties and meridian tropism of the herbs were analyzed as well. Target prediction and pathway enrichment analyses were performed to identify shared molecular pathways among CHM components, GM, and POAG. MR analysis was performed to assess the genetically predicted causal associations between specific microbial taxa and POAG risk. Results: Our data mining work indicated that commonly used CHMs were mainly bitter and sweet in flavors and cold in property, with meridian tropism toward the liver, lung, and kidney. The predominant therapeutic effects of the CHMs included soothing the liver and regulating Qi, promoting blood circulation, and reducing fluid retention. Representative herb pairs were Shudihuang (Rehmanniae Radix Praeparata)-Gouqi (Lycii Fructus) with Zexie (Alismatis Rhizoma), Gouqi (Lycii Fructus)-Fuling (Poria) with Shudihuang (Rehmanniae Radix), and Juhua (Chrysanthemi Flos)-Gouqi (Lycii Fructus) with Zexie (Alismatis Rhizoma). Network pharmacology revealed overlapping targets involving antioxidative, anti-inflammatory, and metabolic regulation pathways. MR analysis demonstrated that higher abundances of Ruminiclostridium 6 [odds ratio (OR) = 0.73, 95% confidence interval (CI): 0.58 – 0.92, P = 0.007], Ruminococcaceae UCG-002 (OR = 0.77, 95% CI: 0.63 – 0.96, P = 0.018), Ruminococcus torques group (OR = 0.71, 95% CI: 0.57 – 0.90, P = 0.004), and Victivallis (OR = 0.82, 95% CI: 0.70 – 0.96, P = 0.016) were causally associated with reduced POAG risk, whereas Actinomyces (OR = 1.34, 95% CI: 1.06 – 1.68, P = 0.013) and Blautia (OR = 1.39, 95% CI: 1.01 – 1.90, P = 0.042) showed positive associations. Conclusion This study revealed potential causal links between GM and POAG and provided integrative evidence that CHM may modulate the microbiota to exert neuroprotective effects. These findings offer new integrative insights into the gut-eye axis and a theoretical basis for developing microbiota-targeted CHM strategies in glaucoma management.

Diabetic kidney disease(DKD)is one of the common microvascular complications in diabetes mellitus patients,with oedema,proteinuria,and continuous decline in renal function as the main clinical manifestations,and traditional Chinese medicine(TCM)believes that diabetic kidney disease is caused by a deficiency of Qi and Yin,which runs through the whole process of the disease.In recent years,academician Tong Xiaolin's theory of"state-target theory"provides new ideas for the treatment of diabetic nephropathy.The"state"is a general term for the overall manifestation of the patient's condition.The overall manifestation of the condition of diabetic kidney disease is a"state of deficiency and impairment"with Qi and Yin deficiency as the key mechanism of the disease.The"target"refers to the specific symptoms of the disease or abnormal examination results,which are the clinical symptoms and abnormal indicators caused by diabetic kidney disease.Ginseng astragali dihuang soup is effective in the treatment of diabetic nephropathy,and the application of this formula based on the theory of state-target can make the therapeutic effect more significant,achieve the therapeutic effect of supporting positive Qi,replenishing the deficiency and benefiting the loss,and improve the clinical symptoms and the abnormal physicochemical indexes of diabetic nephropathy,and the state-target co-adjustment,which can provide a new way of thinking for the diagnosis and treatment of diabetic nephropathy for the clinicians.