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.

AIM: To examine differences in etiology, risk factors, gender, and acute-phase manifestations of retinal artery occlusion(RAO)patients in different age groups, highlighting age-related heterogeneity.

METHODS:This retrospective comparative cohort study enrolled patients with RAO. Patients were divided into <50 y group and ≥50 y group. Etiological classification was based on modified TOAST criteria. Comparisons assessed the prevalence of risk factors, etiological distribution, sex ratio, and, in cases of acute central retinal artery occlusion(CRAO), fundus characteristics and visual outcomes.

RESULTS:This study included a total of 145 RAO patients,which were divided into two groups based on age: <50 y group(15 females and 13 males)with the mean age of 36.64±9.72 y, and ≥50 y group(38 females and 79 males)with the mean age of 63.50±9.54 y. Hypertension(46.4% vs 85.5%)and diabetes(3.6% vs 27.4%)were less prevalent in <50 y group(both P<0.001). The <50 y group was characterized predominantly by stroke of other determined etiology(SOE, 35.7% vs 2.6%, P<0.001), whereas the ≥50 y group was dominated by small artery occlusion(SAO, 35.9%)and large artery atherosclerosis(LAA, 31.6%), the incidence rates were significantly higher in the ≥50 y group than in the <50 y group(both P<0.001). Females were more frequently represented in <50 y group(53.6% vs 32.5%, P=0.039). Multivariable analysis demonstrated that LAA was independently linked to older age and SOE to younger age. Boxcarring occurred exclusively in ≥50 y patients\〖39.5%(17/43)vs 0, P=0.011\〗.

CONCLUSION:The RAO patients<50 y predominantly present with non-atherosclerotic causes and a higher proportion of females, whereas patients≥50 y are mainly affected by atherosclerosis driven etiologies and show signs of reduced vascular compensatory capacity. These findings indicate that age-related differences in RAO should be taken into account when determining etiologic evaluation and management strategies.

Objective: To explore the plasma metabonomic characteristics of patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome. Methods: One hundred and three patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome were enrolled from November 2023 to February 2024 in the First Teaching Hospital of Tianjin University of Traditional Chinese Medicine and 54 healthy individuals were recruited. The general data of the two groups were analyzed, and the plasma metabolite content was detected using ultra-high performance liquid chromatography-Orbitrap mass spectrometry. Construct an orthogonal partial least squares discriminant analysis model to screen metabolites with significant intergroup changes. The variable importance in projection≥ 1, |log2FC|>1, and P<0.05 were used as the criteria for the screening of differential metabolites. Annotate differential metabolites using internal databases and the human metabolome database, and perform pathway analysis using MetaboAnalyst website. Results: There was no statistically significant difference in gender and age between the two groups.Seventeen potential differential metabolites were identified. The D-4′-phosphopantothenate, 2, 6-dichloroindophenol, 4-methylphenol, hypoxanthine, 11, 12-epoxyeicosatrienoic acids, oleamide, 3-phenyllactic acid contents were higher in patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome than in healthy individuals(P<0.05); 3-anisic acid, 3-iodo-octadecanoic acid, mebendazole, β-alanine, citric acid, trans-aconitic acid, geranyl diphosphate, lysophosphatidylcholine(18∶2), phosphatidylethanolamine(18∶1), and caprolactam contents were lower in patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome than in healthy individuals(P<0.05). Ten metabolic pathways were identified, including the key metabolic pantothenate and coenzyme A biosynthesis pathways. Conclusion Metabolic differences were observed between patients with type 2 diabetes mellitus and turbid toxin accumulation syndrome and healthy individuals, and the underlying mechanism may involve the pantothenate and coenzyme A biosynthesis pathways, jointly mediated by D-4′-phosphopantothenate and β-alanine.

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.

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.

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.