Aging is commonly associated with declines in functional fitness that can be effectively attenuated through mid-to long-term, multifaceted physical activity. However, physical activity performed by older adults often aims to maintain, rather than improve, physical fitness. Martial arts are increasingly recognized as suitable multimodal interventions for older adults, as they integrate balance, flexibility, motor control, and cognitive engagement. Within this framework, taekwondo may represent a feasible activity to preserve and enhance functional fitness. Moreover, intergenerational approaches (combining younger and older participants in shared training sessions) may further support adherence, motivation, and social-cognitive stimulation. Despite this potential, long-term programs involving novice older adults remain largely unexplored. Therefore, this study aimed to evaluate the effect of an 8-month intergenerational adapted taekwondo training program for older novice practitioners. This single-arm pre-post observational study used a volunteer convenience sample without a control group. Twenty-one seniors (14 females and 7 males: 63-83 years) participated twice-weekly 60-min taekwondo training for 8 months with one weekly session performed together with 21 children (6-13 years). The "American Alliance for Health, Physical Education, Recreation, and Dance" test battery was used to assess the seniors' functional fitness before and after the intervention based on flexibility, upper-body strength, aerobic endurance, agility/dynamic balance, and coordination. Linear mixed-effects models for repeated measures examined time and sex effects. Significant (p < 0.05) improvements were observed in aerobic endurance and coordination, with normative compliance increasing from 14.3% to 33.3% and from 66.7% to 95.2%, respectively. No significant changes were found in upper body strength, agility/dynamic, or flexibility, though males outperformed females in the Chair sit-and-reach and endurance tests. Despite the limited sample size and the lack of a control group, which limit causal inference and generalizability, the program was associated with improvements in selected functional fitness domains, particularly aerobic endurance and coordination, whereas flexibility, agility/dynamic balance, and upper-body strength did not change significantly, suggesting that intergenerational adapted taekwondo may represent a feasible long-term physical activity option for novice older adults.
Functional decline in activities of daily living (ADL) is considered a marker of ageing and Alzheimer's disease. However, there is a lack of performance-based instruments specifically designed to assess ADL in adults and older adults with Down syndrome. To describe the adaptation process of the Direct Assessment of Functional Status (DAFS) to assess the functional capacity of adults with Down syndrome. The Direct Assessment of Functional Status-Brazilian Version (DAFS-BR) was administered to 15 adults with Down syndrome (nine men and six women) who were divided into two diagnostic groups: stable cognition and suspected dementia or cognitive impairment. The process was conducted in two phases: phase one was characterized by an adaptation in the tasks. In phase two, (cultural and semantic) equivalences were verified, as well as structural aspects, including layout and instructions. This phase was essential for verifying the applicability and comprehensibility of newly adapted tasks. The DAFS-BR was adapted for the time orientation, communication (telephone use), moneyhandling skills, and shopping skills domains, considering the target population. The adaptation process of the DAFS-BR for people with Down syndrome was made considering linguistic, psychological, and cultural idiosyncrasies in the target population, with the input of experts with relevant experience in each domain. After psychometric studies, the Direct Assessment of Functional Status-Down Syndrome (DAFS-DS) could be considered the first ecological instrument for evaluating functional status in adults with Down syndrome in Brazil to enhance both clinical practice and research. O declínio funcional nas atividades da vida diária (AVD) é considerado um marcador do envelhecimento e da doença de Alzheimer. No entanto, há falta de instrumentos de avaliação baseados em desempenho especificamente desenhados para avaliar a AVD em adultos e idosos com síndrome de Down (SD). Descrever a adaptação da Avaliação do Estado Funcional (DAFS) para avaliar a capacidade funcional de adultos com síndrome de Down (SD). A DAFS-BR foi aplicada em 15 adultos com SD (nove homens e seis mulheres) divididos em dois grupos diagnósticos: cognição estável e suspeita de demência ou comprometimento cognitivo. O processo foi conduzido em duas etapas: na primeira, foram realizadas adaptações nas tarefas e, na segunda, foram verificadas equivalências (culturais e semânticas), aspectos estruturais, incluindo layout e instruções. Esta etapa foi essencial para verificar a aplicabilidade e a compreensibilidade das tarefas recém-adaptadas. A DAFS-BR foi adaptada nos domínios de orientação temporal, comunicação (uso do telefone), capacidade de gestão financeira e habilidades de compras, considerando a população alvo. O processo de adaptação da DAFS-BR para SD foi realizado considerando-se as particularidades linguísticas, psicológicas e culturais da população alvo, com a participação de especialistas com experiência relevante na área e em cada domínio. Após estudos psicométricos, o DAFS-SD poderá ser considerado o primeiro instrumento ecológico para a avaliação do estado funcional em adultos com síndrome de Down no Brasil, visando aprimorar tanto a prática clínica quanto a pesquisa.
There is a critical lack of reliable, high-quality epidemiological data on mental health and/or social and emotional wellbeing (SEWB) outcomes for First Nations children, partly, due to the limited availability of culturally valid assessment tools. This review aims to assess the cultural validity of mental health and SEWB assessment tools used with First Nations children aged 4-12 years in Australia, and identify gaps, strengths, and opportunities for reform that enhance cultural safety, and self-determination in assessment practices. A systematic search of five electronic databases (Web of Science, PubMed, PsycINFO, Informit, and CINAHL) identified English-language studies (1980-2025) assessing mental health or SEWB in Aboriginal and/or Torres Strait Islander children aged 4-12 years. Data on assessment tools were extracted and their cultural validity analysed using the First Nations Cultural Validity Assessment Tool. Tools were classified, as bespoke, culturally adapted or generic, using the CBSPATSISP definitions. This review examined the cultural validity across 10 studies, including 11 unique tools and 16 assessments of cultural validity. Three tools were bespoke, eight culturally adapted, and five generic. Over three quarters of tools used to assess SEWB or mental health in First Nations children had poor or limited cultural validity. Two bespoke SEWB tools were identified, although none specifically targeted mental health. Culturally valid assessment tools for First Nations children remain limited, with research predominantly relying on inappropriate measures. Improving the measurement of mental health and SEWB outcomes requires a shift towards First Nations-led, co-designed tools grounded in Indigenous knowledges, strengths, and cultural frameworks. The evidence base was limited by reliance on published academic sources, which may have missed community-used assessment tools, a focus on cultural validity rather than broader study quality, and limited psychometric reporting for some First Nations-specific measures. PROSPERO (CRD42024542866). 13 May 2024. www.crd.york.ac.uk/PROSPERO/view/CRD42024542866.
Artificial intelligence (AI) is reshaping clinical practice, yet formal AI education in medical curricula has lagged significantly behind-a gap particularly acute in low- and middle-income countries (LMICs). This narrative review examines AI integration in medical education across LMICs, with primary contextual focus on sub-Saharan Africa and African health systems within this broader framing. Available evidence suggests that a substantial proportion of medical students globally may lack formal AI education despite growing clinical AI adoption among physicians, with LMICs and African contexts disproportionately underrepresented in AI-in-medical-education literature. African contexts face compounding implementation challenges-infrastructure deficits, data scarcity, algorithmic bias in externally designed tools, and regulatory gaps-yet possess distinctive contextual opportunities. Applying a structured critical counterargument analysis, the review interrogates both the rationale for integration and the strongest arguments for delay. The review's contribution lies in its LMICs-and-Africa-centred framing, its integration of three complementary theoretical frameworks, and its policy-oriented, phased implementation synthesis-dimensions not addressed in aggregate by existing reviews. AI integration in medical education in LMICs is a context-sensitive priority. The risks of unplanned inaction-widening competency gaps and forfeiture of iterative evaluation data-should be weighed against the risks of implementation, with careful, locally adapted, phased approaches offering the most defensible pathway forward.
Survivors of suicide loss (SLSs) represent a unique group that faces a heightened risk of developing complications related to grief, often characterized by ruminating on the reasons behind their loved one's suicide, which can affect their supportive social networks. Grief rumination is considered a transdiagnostic risk factor for mental health diseases, including prolonged grief. We evaluated the psychometric and reliability of the Iranian Utrecht Grief Rumination Scale (UGRS) among SLSs. This cross-sectional study, conducted between 2023 and 2024, investigated the psychometric properties of the Persian version of the UGRS. The scale was adapted for the Iranian population through a rigorous translation process encompassing forward translation, reconciliation, and back-translation. A sample of 170 suicide survivors, recruited via convenience and snowball sampling, completed a battery of instruments, including the UGRS, the Prolonged Grief Disorder scale - 13 (PG-13-R), the Hospital Anxiety and Depression Scale (HADS), and the Ruminative Response Scale (RRS). Confirmatory factor analysis (CFA), alongside assessments of concurrent, convergent, and divergent validity, was employed to evaluate the construct validity of the UGRS. Reliability was assessed using Cronbach's alpha and test-retest reliability over a 4-week interval. Data analysis was performed utilizing SPSS 26 (IBM, USA), Amos 26 (IBM, USA), and Mplus 8.3 (Muthén & Muthén, USA. The results of CFA showed that the second-order five-factor hierarchy had more appropriate fit indices than the five correlated factors in suicide survivors (ΔCFI = -0.014, ΔTLI = -0.021, ΔRMSEA = -0.012; ΔSRMR = -0.014). UGRS exhibited a moderate correlation with brooding, indicating a convergent validity, and an HTMT index of less than. 090 in all subscales, indicating its divergent validity. UGRS exhibited a positive correlation with prolonged grief and anxiety and depression, which confirms its concurrent validity. Internal consistency was supported by Cronbach's alpha and McDonald's omega for all subscales; test-retest reliability was also acceptable (ICC = 0.85). The Persian UGRS exhibited good psychometric properties, validating its application to assess grief rumination among suicide-loss survivors in both clinical and research contexts.
Global agricultural productivity is increasingly destabilized by climate change-driven droughts, floods, extreme heat, and severe storms. Although the climate-smart agriculture (CSA) framework addresses these challenges, implementation has focused mainly on plant genetics and agronomic inputs, leaving the adaptive potential of the crop microbiome underexplored. Here, we examine the agricultural use of synthetic microbial communities (SynComs) through the "crop holobiont" concept, in which plants and their associated microbiota function as an integrated, responsive system rather than through plant genomes alone. Pioneer plants in extreme environments may serve as reservoirs of stress-adapted microbes and provide a strategic toolkit for advancing CSA. SynComs assembled from these microbes can act not only as nutrient suppliers but also as dynamic physiological modulators that enhance crop phenotypic plasticity under climatic stress. We propose a roadmap for crop microbiology that integrates synthetic ecological engineering, with broad implications for CSA.
Residents contribute substantially to clinical teaching; however, many lack formal preparation for their role as educators. Despite rising expectations within competency frameworks, evidence from multicultural, rapidly evolving training environments remains limited. This study aimed to assess residents' perceptions of their educator role, evaluate self-reported teaching competency and involvement, and identify learning needs to inform the development of a context-sensitive Residents-as-Teachers program. A cross-sectional needs assessment survey was conducted among all 322 medical and surgical residents in a large academic health system between May and July 2025. A validated, locally adapted questionnaire assessed perceptions, teaching involvement, and learning needs. Data were analysed using descriptive statistics, bivariate analyses, and multivariable linear regression to identify independent predictors of positive perceptions of the educator role. A total of 291 residents participated (response rate 90.4%), representing 18 specialties across medical and surgical disciplines. Residents reported spending a mean of 35.8% of their training time engaged in teaching activities. Overall perceptions of the educator role were positive (mean total score 49.99/60), while self-reported teaching competency was moderate. A consistent interprofessional teaching gap was identified, with nurses ranked least frequently taught by over 80% of residents and receiving the lowest competency rating. Residents expressed strong interest in structured teaching-skills training, preferring interactive instructor-led formats over online self-paced learning. In multivariable regression, interest in a future educator role (p <0.001) and competency in teaching medical students (p =0.038) were the strongest independent predictors of positive educator perceptions. These preliminary findings indicate that residents play a substantial yet underprepared role in clinical teaching. Results suggest that structured, contextually responsive Residents-as-Teachers programs prioritizing motivation, teaching competency, and interprofessional education may help address identified gaps and support the development of future clinician-educators. Longitudinal and implementation-focused research is needed to evaluate whether such programs improve observed teaching performance and learner outcomes in diverse postgraduate training environments.
Research suggests that approach and avoidance-decreasing or increasing self-stimulus distance, respectively-influence self-evaluation. However, this conclusion typically stems from examining approach and avoidance as a pair, while no empirical research has satisfactorily isolated the unique causal contribution of each behaviour. To address this gap, three experiments (N Total = 1929) used an adapted Manikin Task incorporating a proper control condition (i.e., no distance change) to first isolate the effect of approach, relying on both reaction time and self-report measures. Furthermore, by incorporating avoidance in the last experiment, this task allowed us to oppose model-based theoretical predictions. Results did not reveal any behaviour-specific effects. Nevertheless, the proposed methodology opens new avenues for investigating the behavioural determinants of self-construal.
Objective: The MEchanick Transculturalization Research and Innovation ConSortium/Bernard Lown Scholars in Cardiovascular Health Program Consensus Conference on Dysglycemia-Based Chronic Disease (DBCD) Transculturalization in Chile convened on November 20, 2023, in Santiago, Chile. The conference generated affirmed and emergent concepts, key strategies, and specific implementation tactics to improve type 2 diabetes (T2D) care in Chile. Findings: Important affirmed concepts included: (1) implementing a comprehensive approach to T2D management beyond glycemic control; (2) addressing unique challenges for early detection and treatment of T2D; and (3) applying expanded roles of telemedicine. Important emergent concepts included: (1) adopting transculturalized chronic care models such as DBCD; (2) recognizing prediabetes as a critical DBCD target to prevent T2D and T2D complications, especially cardiovascular disease; and (3) implementation of the DBCD model for individual and population health. Key strategies included: (1) validation of culturally adapted T2D risk assessment tools; (2) integration of social determinants of health (SDOH) and ethnocultural factors into DBCD care strategies/tactics; and (3) promotion of equity in healthcare access for all people comprising diverse populations. Finally, specific implementation tactics included: (1) focusing on patient-centered public policies; (2) ensuring access to effective treatments; and (3) using culturally relevant resources for education and prevention. When coordinated, these strategies and tactics mitigate DBCD progression, thereby enhancing healthcare outcomes. Conclusions and recommendations: Expert consensus emphasizes the need for a comprehensive approach to T2D management in Chile, leveraging transculturalized lifestyle medicine, validated risk assessment tools, SDOH, and patient-centered public policies. This process should begin with incorporating eHealth technologies, validation studies, and then translation into clinical practice guidelines. As this templated methodology is applied to other regions of the world, the resulting compendium of concepts, strategies, and tactics can foment a more effective preventive health culture and optimize DBCD care across the ethnocultural spectrum.
Background: The lack of child-friendly, second-line drug-resistant tuberculosis (DR-TB) medication in South Africa often leads to the use of adult formulations, which are not always suitable for children. Caregiver experiences in preparing and administering this treatment and the impact on parent-child relationships are poorly represented in the literature. Objective(s): To assess parental acceptability regarding the preparation and administration of DR-TB medications for young children, utilizing Wademan's acceptability framework. Methods: Seven caregivers of eight children who had been diagnosed with DR-TB between June 2019 and February 2022 and initiated treatment at a referral hospital in KwaZulu-Natal participated in the study. Individual in-depth interviews with three caregivers and one focus group discussion with four caregivers were used to gather data, which were analyzed using part of the acceptability framework for TB in children developed by Wademan et al. [1]. Findings: Despite challenges, caregivers were adept at navigating DR-TB medication regimens, highlighting their critical role in inventive preparation methods to enhance palatability and strategic administration practices for children. Adult medications were adapted where necessary, and caregivers employed various techniques to ensure adherence. The acceptability of treatment was affected by medication palatability, preparation and administration, appeal and side effects (usability), and the interface between caregivers and the healthcare system (integration). Staying engaged in care threatened not only family resources but also the parent-child relationship. The daily struggle was between children often resisting medication and caregivers needing to find ways for the children to take medication, for instance, by begging, reasoning with, threatening, and forcing them. Conclusions: Despite all formulations having adverse effects, caregivers and children preferred child-friendly formulations due to their ease of preparation and administration. Child-friendly formulations of DR-TB medications should be widely available and be the standard of care in all settings.
Tomato (Solanum lycopersicum L.) is one of the most economically important horticultural crops in China, and Xinjiang is the main region in China for processing tomato production. The establishment of a robust in vitro regeneration system is a fundamental prerequisite for genetic improvement and cultivar innovation in this crop. Among the factors influencing regeneration efficiency, exogenously applied plant growth regulators (PGRs) are the most important because they regulate endogenous phytohormone homeostasis and signaling pathways. In this study, true leaf explants of the processing tomato Ligeer 87-5 were used to optimize combinations of 6-benzyladenine (6-BA) and indole-3-acetic acid (IAA) and to establish an efficient in vitro regeneration system. Full strength MS medium supplemented with 2 mg/L 6-BA and 0.2 mg/L IAA was optimal for callus induction and organogenic competence, resulting in a callus induction rate of 97.00%, an embryogenic cell incidence of 63.88%, and an adventitious bud formation rate of 21.33% after 20 days; the budding rate further increased to 63.00% after 30 days. For rapid shoot induction, a medium composed of MS + 1 mg/L 6-BA + 0.2 mg/L IAA yielded the highest adventitious bud formation rate, reaching 89.00% after 10 days. Rooting was most effective on MS medium supplemented with 0.2 mg/L IAA, achieving a 100% rooting rate after 21 days, an average root length of 11.76 cm, a 76.67% acclimatization rate after 28 days, and a 100% survival rate after hardening and transplantation. Collectively, the stage-specific application of different media substantially improved true-leaf regeneration efficiency in processing tomato plants, providing a robust platform for future genetic transformation and molecular breeding.
Infections with respiratory viruses such as SARS-CoV-2 and influenza are significant international public health concerns. While patients with cancer remain the most vulnerable group, they show poor vaccine response in general. Immunological data in this population are limited and mainly focus on serological parameters. However, in these patients, cellular, and especially T-cell, responses often seem to be induced more reliably than humoral responses. To gain further insights into vaccine-induced immunity, the RESPONSE study will analyze the effect of early and late booster vaccination on humoral and cellular responses, with special focus on T cell-induced immune responses. In addition, we aim to investigate factors influencing humoral and cellular vaccine-induced immunity in patients with hematological and oncological malignancies, including state of disease, treatment, and demographic factors. Humoral immune responses will be assessed by measuring binding and neutralizing antibodies using standardized assays. Cellular immunity will be evaluated using functional assays such as flow cytometry and FluoroSpot, as well as in-depth analyses using additional exploratory assays as appropriate. Immune responses will be correlated with clinical parameters, including disease status, treatment, and demographic factors. This study was initiated following ethics approval and is currently recruiting participants. Enrollment commenced on March 25, 2025, and is ongoing, whereas biosample collection and follow-up visits are nearing completion for most participants. Final data cleaning, dataset integration, and statistical analyses of adaptive immune responses are planned from the third quarter of 2026 onward. This study intends to lay a foundation for a structured translational research platform on vaccination to aim for best protection from infection by different respiratory pathogens. Long-term objectives are reaching best possible protection from vaccine-preventable disease with a first focus on influenza infection. In addition, we plan to investigate vaccine-induced immune responses to the recently approved respiratory syncytial virus vaccine using this platform and possibly extend this to further vaccines in the future. Urgent questions, such as the influence of different targeted therapies on vaccine immune response, will be part of these projects. ClinicalTrials.gov NCT06612515; https://clinicaltrials.gov/study/NCT06612515. DERR1-10.2196/88520.
Early self-management is essential for preventing the progression from prediabetes to diabetes, particularly among older adults who often experience difficulties maintaining stable health behaviors during the early adaptation stage. Illness acceptance represents an important cognitive response to disease-related stress, while depression reflects a common emotional reaction during early disease awareness. However, the psychological mechanisms linking illness acceptance and early self-management in older adults with prediabetes remain insufficiently understood. This study aimed to examine the relationships among illness acceptance, depression, and early self-management in older adults with prediabetes, and to investigate the mediating role of depression within the stress-cognitive appraisal-coping framework. A cross-sectional study was conducted among 400 older adults with prediabetes recruited from multiple hospitals in Zhejiang Province, China, between June and December 2025. Participants completed validated measures assessing illness acceptance (Acceptance of Illness Scale), depressive symptoms (PHQ-3), and self-management behaviors (Self-Management Scale). Pearson correlation analysis was used to assess associations among variables. Mediation analysis was conducted using PROCESS Model 4 with bias-corrected bootstrapping after adjustment for demographic and clinical covariates. Illness acceptance was positively associated with depressive symptoms (r = 0.38, p < 0.001) and self-management behaviors (r = 0.36, p < 0.001). Depressive symptoms were also positively associated with self-management (r = 0.67, p < 0.001). Mediation analysis demonstrated that depression partially mediated the relationship between illness acceptance and self-management, accounting for approximately 68.57% of the total effect. The indirect effect was statistically significant based on bootstrap confidence intervals. Structural equation modeling indicated acceptable model fit. Illness acceptance was positively associated with early self-management among older adults with prediabetes, both directly and indirectly through emotional pathways. The findings suggest that emotional responses accompanying early disease awareness may influence behavioral engagement during disease adaptation. Integrating acceptance-based education with emotional support strategies may enhance early self-management interventions for older adults with prediabetes.
Geographic knowledge graph (GeoKG) organizes the geographical entities and their relationships, which provides rich spatial semantic to serve various geographic artificial intelligence tasks by knowledge graph representation learning (KGRL). As a bridge between the knowledge graph and downstream tasks, KGRL results in a speedup of inference by embedding the entities and relationships of KG into a low-dimensional vector space. However, the existing KGRLs treated subgraphs in different regions uniformly, ignoring the spatial heterogeneity of GeoKG. It may result in significant performance differences across regions. To address this problem, this study proposes a region adaptive KGRL (RA-KGRL) method to mitigate the impact of spatial heterogeneity on performance. Specifically, RA-KGRL first splits the original GeoKG into subgraphs by introducing regional priors. Then, RA-KGRL learns local models for the subgraphs and performs local-to-global optimization to learn accurate global model. Extensive experiments on thirteen datasets indicate that RA-KGRL is comparable or even better than baselines on the traditional metrics, and outperforms all baselines on the new region adaptive metrics. This study provides a methodological reference for improving the performance of KGRLs on spatial heterogeneity scenarios.
Motivation to quit smoking and decisions to smoke or forgo smoking vary throughout the day. However, little is known about how within-day patterns of psychological states such as self-efficacy and attitudes toward smoking relate to these determinants of smoking cessation attempts. Identifying these dynamic processes can inform the development of more precisely timed and tailored digital interventions. This study aimed to identify distinct within-day trajectories of self-efficacy for cutting down on cigarettes smoked and attitudes toward smoking, and to examine how these trajectories predicted end-of-day motivation to quit and same-day cigarette forgoing (ie, choosing not to smoke cigarettes that one would normally smoke). People who smoked at least 10 cigarettes a day at baseline (N=348, mean age 44.6, SD 12.1 years; n=212, 60.9% female) received smartphone surveys about 4-5 times a day after logging each cigarette, producing 15,614 surveys over 2561 days. Trajectories of self-efficacy and smoking attitudes were modeled at the person-day level using smooth functions, and 6 daily parameters of change (overall level, range of change, volatility, overall trend, acceleration of change, and trajectory shape [trend×acceleration]) were extracted. These parameters were then entered as predictors of (1) end-of-day motivation to quit (linear mixed models) and (2) whether participants forwent cigarettes that day (binomial generalized linear mixed models). Higher overall self-efficacy consistently predicted both greater end-of-day motivation and greater odds of forgoing. Upward trends and acceleration in self-efficacy further predicted greater odds of forgoing, indicating that days when confidence not only increased but did so quicker were most strongly associated with forgoing cigarettes that day. Less favorable attitudes toward smoking predicted greater motivation to quit and increased likelihood of forgoing cigarettes. Broader ranges of daily change in attitudes were linked with stronger motivation to quit and greater odds of forgoing, while more moment-to-moment volatility was associated with reduced odds of forgoing cigarettes that day. Dynamic features of self-efficacy and smoking attitudes, such as overall level, trend, and acceleration, were robust predictors of daily motivation to quit and cigarette forgoing. These findings highlight that the way self-efficacy and attitudes shift across the day is meaningful beyond their overall levels. Just-in-time adaptive interventions may be more effective if they monitor and respond to varying trajectory features rather than focusing on static states, supporting a shift toward dynamically aware intervention strategies in digital health.
This study presents a dual-stream spatiotemporal attention network (DSTA-Net) for robust driver behavior recognition under complex illumination conditions. Based on the SlowFast backbone, DSTA-Net incorporates the Temporal-Channel Attention Module (TCAM), Temporal Attention Focusing Algorithm (TAFA), Adaptive Rank Pooling Dynamic Image Generation (ARPDIG), and Coordinate Attention (CA) mechanism to enhance temporal sensitivity and illumination adaptability. A computationally efficient (2+1)D convolutional structure is adopted to reduce computational cost while maintaining spatiotemporal representation capability. Evaluated on the proposed MAID-Behav dataset with multi-view and multi-illumination scenarios, DSTA-Net achieves 98.76% accuracy under normal lighting and shows improved performance under low-light environments, outperforming state-of-the-art models by over 7%. The proposed model provides a spatiotemporal modeling framework that may be applicable to intelligent driving scenarios under the evaluated experimental settings.
In preclinical research, agar-based tissue-mimicking phantoms have proven to be valuable tools for magnetic resonance imaging (MRI)-guided focused ultrasound (MRgFUS) evaluations. This study evaluates an agar-based silica-doped phantom for MRgFUS, examining main properties, MRI appearance, and thermal lesion formation in comparison with excised porcine tissue. The proposed agar/silica phantom was subjected to various single and grid sonication protocols in a 3T MRI scanner, with thermal effects monitored intraprocedurally through magnetic resonance thermometry and postsonication through T2-Weighted (T2-W) Turbo Spin Echo (TSE) imaging. The accuracy of lesion formation according to planned patterns and lesion visibility on T2-W TSE images were assessed. To establish the lesion detection threshold, phantom exposure was gradually increased, with identical sonication protocols repeated to assess repeatability. Grid sonications were also conducted on excised porcine tissue for comparison. The phantom facilitated lesion formation across various patterns and depths without significant shifting effects, exhibiting lesions with excellent contrast on T2-W images and adaptability to variations in power and pulse duration settings. In contrast, excised tissue exhibited abnormal temperature fluctuations during grid sonications and lesion shifting. The minimum focal temperature required to generate a measurable lesion on T2-W images was 39°C (thermal dose threshold of 1.49 × 10-4 CEM43°C), with lesion sizes increasing proportionally to energy levels. A comparison of thermal profiling in repeated sonications demonstrated good repeatability. This study confirms that the agar/silica phantom provides a reliable, reproducible platform for MRgFUS assessment, improving lesion visualization, and calibration for preclinical studies.
Heart disease remains one of the leading causes of mortality worldwide, highlighting the need for accurate and early risk prediction systems. Traditional machine learning approaches for cardiovascular disease prediction primarily rely on structured clinical attributes and may not fully capture contextual relationships among patient features. To address this limitation, this study proposes a structured-to-text ClinicalBERT framework that transforms structured cardiovascular records into contextual clinical text representations and utilizes transformer-based embeddings for heart disease prediction. The study employs a publicly available UCI Statlog/Kaggle heart disease dataset containing 270 complete patient records. Structured cardiovascular attributes, including age, sex, chest pain type, blood pressure, cholesterol level, electrocardiogram results, and heart rate measurements, are converted into clinically meaningful textual descriptions. These text representations are processed using ClinicalBERT to generate contextual embeddings, which are subsequently used as input features for a Random Forest classifier. Model performance was evaluated using an 80:20 train-test split and assessed through Accuracy, Precision, Recall, F1-score, and ROC-AUC metrics. Experimental results demonstrate that the proposed ClinicalBERT + Random Forest framework achieved an accuracy of 95.6%, precision of 88.89%, recall of 95.30%, F1-score of 91.30%, and a ROC-AUC of 0.71 on the held-out test set. Comparative analysis with conventional machine learning models indicates that contextual embeddings generated by ClinicalBERT provide improved feature representation for cardiovascular risk prediction. The findings demonstrate the feasibility of adapting ClinicalBERT to structured cardiovascular data through contextual text generation. Although the proposed framework shows promising predictive performance, the study should be considered a proof-of-concept due to the limited dataset size and absence of external validation. Future work will focus on multicenter evaluation, explainable AI techniques, and broader clinical validation to enhance generalizability and real-world applicability.
Rheumatoid arthritis affects ∼1% of adult population, results in joint inflammation and systemic comorbidities, and is driven by pathogenic hyperactivation of both innate and adaptive immune systems. We demonstrate that emergency myelopoiesis is induced in rheumatoid arthritis, enhancing innate immune cell production and generating functionally altered innate immune cells. Importantly, these mechanisms impact dendritic cells-antigen-presenting cells that bridge innate and adaptive immune responses. Such effects are intrinsic to hematopoietic stem and progenitor cells (HSPCs) and persist ex vivo independently of inflammatory disease milieu. Dendritic cells derived from HSPCs of arthritis afflicted mice show global changes in gene expression, cytokine production, and induction of activation and checkpoint markers. Furthermore, such dendritic cells have altered capacity for T cell activation. Overall, this characterizes how chronic inflammation and induction of emergency myelopoiesis affect dendritic cell development and function in models of rheumatoid arthritis, with implications for other disorders of chronic inflammation.
Endometriosis (EMs) is an estrogen-dependent chronic inflammatory gynecological disease characterized by ectopic growth of endometrial tissues, leading to dysmenorrhea, pelvic pain, and infertility. Although the retrograde menstruation theory clarifies the dissemination of endometrial fragments to ectopic sites, the mechanisms behind the survival of ectopic lesions and their immune evasion in hostile microenvironments remain unclear. Endometrial stromal cells (ESCs) are chronically exposed to a microenvironment of hypoxia, nutrient deprivation and oxidative stress, and this energy stress state drives the ESCs to develop adaptive metabolic reprogramming. Through remodeling glucose, lipid, and amino acid metabolic pathways, ESCs not only fulfill their own proliferative requirements but also utilize metabolites as signaling mediators to modulate immune cell functions. This review elaborates on the characteristics of energy stress-driven metabolic reprogramming in EMs, deciphers its mechanisms underlying immune evasion, and discusses the therapeutic potential of combined metabolic-immune intervention strategies.