Search Results (20,627)

Background: The rapid aging of China’s population poses significant challenges, particularly in public health and medical services. Frailty, a reversible geriatric syndrome, is a critical intervention target for disability prevention among older adults. Objective: We hypothesize that both intervention groups will demonstrate significant improvements in Short Physical Performance Battery (SPPB) scores compared to the control group, and that these improvements will be accompanied by parallel reductions in inflammatory markers and beneficial alterations in the gut microbiota. Methods: The MultIfaceted NUtrition inTervention for frail Elderly (MINUTE) trial is a randomized, parallel-group controlled trial. In Beijing, China, 315 frail older adults were recruited and randomly assigned to 3 groups: a control group receiving routine community health management only, multifaceted nutrition intervention group, and a multifaceted nutrition and exercise combined intervention group, each comprising 105 participants. The study consists of a three-month intervention period followed by a nine-month follow-up. During the three-month intervention period, the control group receives routine community health management, while the multifaceted nutrition intervention group receives daily dietary guidance, personalized nutrition consultations, and health education. Additionally, the combined intervention group receives exercise interventions in addition to the nutritional components. After the three-month intervention, all three groups will be followed up for nine months to assess the sustainability of the study. Results: The primary outcomes are the changes in the SPPB scores. The secondary outcomes include frailty scores, intrinsic capacity, malnutrition risk, frailty recovery rates, serum differential metabolites, inflammatory factors, and gut microbiota changes. This study aims to establish a scalable and sustainable pathway for frailty prevention among community-dwelling older adults in China and provide valuable insights to inform strategies for healthy aging. Trial registration: This study is conducted in accordance with the Declaration of Helsinki and approved by the Peking University Institutional Review Board (IRB00001052-23178), with all amendments subject to prior review and approval. Informed consent is obtained from participants, and findings will be disseminated through peer-reviewed publications, conference presentations, and summaries for school staff and participants. ClinicalTrials.gov (NCT06547593) registered 30 July 2024. Full article

Lassa fever (LF), a severe hemorrhagic disease endemic to West Africa, is primarily transmitted by rodents of the genus Mastomys, particularly Mastomys natalensis, which serve as the main reservoirs of Lassa virus (LASV). There have been reports of high prevalence of LF in Nigeria, and outbreaks tend to be recurrent yet geographically restricted, implying that additional ecological or epidemiological factors influence the distribution of the disease beyond the mere presence of M. natalensis. However, national-scale data on LASV prevalence in rodent populations remain scarce. To address this gap, a targeted small mammal survey was conducted over a four-month period (May to August 2024) in Otukpo Local Government Area (LGA) of Benue State, north-central Nigeria. Rodents and other small mammals were trapped across three purposively selected wards identified as high-risk areas based on prior reports of occurrence of such small mammals in the areas and the informal settlements in which the selected wards were located in in Otukpo LGA. Analysis of the samples revealed no statistically significant variation in LASV prevalence among the study sites, indicating a relatively uniform, low-level exposure risk across the LGA and region. However, a marginally significant difference in LASV detection between plasma and serum samples suggests that sample type and storage conditions may influence serological sensitivity. These findings highlight the importance of refining diagnostic protocols, broadening surveillance to include additional rodent hosts, and integrating ecological data with public health strategies to improve early warning systems and strengthen Lassa fever control efforts. Full article

A reassessment of the risk-benefit balance of the two lipid nanoparticle (LNP)-based vaccines, Pfizer’s Comirnaty and Moderna’s Spikevax, is currently underway. While the FDA has approved updated products, their administration is recommended only for individuals aged 65 years or older and for those aged 6 months or older who have at least one underlying medical condition associated with an increased risk of severe COVID-19. Among other factors, this change in guidelines reflect an expanded spectrum and increased incidence of adverse events (AEs) and complications relative to other vaccines. Although severe AEs are relatively rare (occurring in < 0.5%) in vaccinated individuals, the sheer scale of global vaccination has resulted in millions of vaccine injuries, rendering post-vaccination syndrome (PVS) both clinically significant and scientifically intriguing. Nevertheless, the cellular and molecular mechanisms of these AEs are poorly understood. To better understand the phenomenon and to identify research needs, this review aims to highlight some theoretically plausible connections between the manifestations of PVS and some unique structural properties of mRNA-LNPs. The latter include (i) ribosomal synthesis of the antigenic spike protein (SP) without natural control over mRNA translation, diversifying antigen processing and presentation; (ii) stabilization of the mRNA by multiple chemical modification, abnormally increasing translation efficiency and frameshift mutation risk; (iii) encoding for SP, a protein with multiple toxic effects; (iv) promotion of innate immune activation and mRNA transfection in off-target tissues by the LNP, leading to systemic inflammation with autoimmune phenomena; (v) short post-reconstitution stability of vaccine nanoparticles contributing to whole-body distribution and mRNA transfection; (vi) immune reactivity and immunogenicity of PEG on the LNP surface increasing the risk of complement activation with LNP disintegration and anaphylaxis; (vii) GC enrichment and double proline modifications stabilize SP mRNA and prefusion SP, respectively; and (viii) contaminations with plasmid DNA and other organic and inorganic elements entailing toxicity with cancer risk. The collateral immune anomalies considered are innate immune activation, T-cell- and antibody-mediated cytotoxicities, dissemination of pseudo virus-like hybrid exosomes, somatic hypermutation, insertion mutagenesis, frameshift mutation, and reverse transcription. Lessons from mRNA-LNP vaccine-associated AEs may guide strategies for the prediction, prevention, and treatment of AEs, while informing the design of safer next-generation mRNA vaccines and therapeutics. Full article

Accurate detection of fetal distress from cardiotocography (CTG) is clinically critical but remains subjective and error-prone. In this research, we present a leakage-safe Calibrated Global Logit Fusion (CGLF) framework that couples TabNet’s sparse, attention-based feature selection with XGBoost’s gradient-boosted rules and fuses their class probabilities through global logit blending followed by per-class vector temperature calibration. Class imbalance is addressed with SMOTE–Tomek for TabNet and one XGBoost stream (XGB–A), and class-weighted training for a second stream (XGB–B). To prevent information leakage, all preprocessing, resampling, and weighting are fitted only on the training split within each outer fold. Out-of-fold (OOF) predictions from the outer-train split are then used to optimize blend weights and fit calibration parameters, which are subsequently applied once to the corresponding held-out outer-test fold. Our calibration-guided logit fusion (CGLF) matches top-tier discrimination on the public Fetal Health dataset while producing more reliable probability estimates than strong standalone baselines. Under nested cross-validation, CGLF delivers comparable AUROC and overall accuracy to the best tree-based model, with visibly improved calibration and slightly lower balanced accuracy in some splits. We also provide interpretability and overfitting checks via TabNet sparsity, feature stability analysis, and sufficiency (k95) curves. Finally, threshold tuning under a balanced-accuracy floor preserves sensitivity to pathological cases, aligning operating points with risk-aware obstetric decision support. Overall, CGLF is a calibration-centric, leakage-controlled CTG pipeline that is interpretable and suited to threshold-based clinical deployment. Full article

Background: Artificial Intelligence (AI) is increasingly applied in endurance sports to optimize performance, enhance recovery, and personalize nutrition and supplementation. This review synthesizes current knowledge on AI applications in endurance sports, emphasizing implications for metabolic health, nutritional strategies, and recovery optimization, while also addressing ethical considerations and future directions. Methods: A narrative review was conducted using targeted searches of PubMed, Scopus, and Web of Science with cross-referencing. Extracted items included sport/context, data sources, AI methods including machine learning (ML), validation type (internal vs. external/field), performance metrics, comparators, and key limitations to support a structured synthesis; no formal risk-of-bias assessment or meta-analysis was undertaken due to heterogeneity. Results: AI systems effectively integrate multimodal physiological, environmental, and behavioral data to enhance metabolic health monitoring, predict recovery states, and personalize nutrition. Continuous glucose monitoring combined with AI algorithms allows precise carbohydrate management during prolonged events, improving performance outcomes. AI-driven supplementation strategies, informed by genetic polymorphisms and individual metabolic responses, have demonstrated enhanced ergogenic effectiveness. However, significant challenges persist, including measurement validity and reliability of sensor-derived signals and overall dataset quality (e.g., noise, missingness, labeling error), model performance and generalizability, algorithmic transparency, and equitable access. Furthermore, limited generalizability due to homogenous training datasets restricts widespread applicability across diverse athletic populations. Conclusions: The integration of AI in endurance sports offers substantial promise for improving performance, recovery, and nutritional strategies through personalized approaches. Realizing this potential requires addressing existing limitations in model performance and generalizability, ethical transparency, and equitable accessibility. Future research should prioritize diverse, representative, multi-site data collection across sex/gender, age, and race/ethnicity. Coverage should include performance level (elite to recreational), sport discipline, environmental conditions (e.g., heat, altitude), and device platforms (multi-vendor/multi-sensor). Equally important are rigorous external and field validation, transparent and explainable deployment with appropriate governance, and equitable access to ensure scientifically robust, ethically sound, and practically relevant AI solutions. Full article

Understanding the variability of turbulence intensity (TI) under different wind regimes is essential for the design and safety of offshore wind turbines. The IEC Normal Turbulence Model (NTM), though widely adopted in industry, does not incorporate directional dependence or account for extreme wind events such as typhoons, which can lead to substantial underestimation of turbulence in complex offshore environments. In this study, field measurements from two coastal sites in China, Huilai and Pingtan, were analyzed. At Pingtan, two months of observations captured both normal and typhoon-affected winds, providing a unique dataset for assessing turbulence under typhoon-affected conditions. The results show that wind speeds during the typhoon-affected period were approximately 14% higher than those during normal periods. At Huilai, TI was evaluated under northeasterly and southeasterly sea breezes, revealing that the IEC NTM underestimated TI by 15–42%, with more pronounced discrepancies under northeasterly winds. Based on these findings, revised NTM parameters and correction factors are proposed for different wind conditions, enhancing the applicability of the model to offshore wind turbine design. This work underscores the importance of incorporating directional and event-specific modifications into IEC turbulence standards to ensure reliable structural assessment across diverse wind regimes. Full article

Artificial intelligence (AI) is transforming cardiac electrophysiology across the entire care pathway, from arrhythmia detection on 12-lead electrocardiograms (ECGs) and wearables to the guidance of catheter ablation procedures, through to outcome prediction and therapeutic personalization. End-to-end deep learning (DL) models have achieved cardiologist-level performance in rhythm classification and prognostic estimation on standard ECGs, with a reported arrhythmia classification accuracy of ≥95% and an atrial fibrillation detection sensitivity/specificity of ≥96%. The application of AI to wearable devices enables population-scale screening and digital triage pathways. In the electrophysiology (EP) laboratory, AI standardizes the interpretation of intracardiac electrograms (EGMs) and supports target selection, and machine learning (ML)-guided strategies have improved ablation outcomes. In patients with cardiac implantable electronic devices (CIEDs), remote monitoring feeds multiparametric models capable of anticipating heart-failure decompensation and arrhythmic risk. This review outlines the principal modeling paradigms of supervised learning (regression models, support vector machines, neural networks, and random forests) and unsupervised learning (clustering, dimensionality reduction, association rule learning) and examines emerging technologies in electrophysiology (digital twins, physics-informed neural networks, DL for imaging, graph neural networks, and on-device AI). However, major challenges remain for clinical translation, including an external validation rate below 30% and workflow integration below 20%, which represent core obstacles to real-world adoption. A joint clinical engineering roadmap is essential to translate prototypes into reliable, bedside tools. Full article

Objectives: This study evaluated the utility of complex morphometric analyses for predicting radiation pneumonitis (RP) and proposed a quantitative prognostic framework for patients with non-small cell lung cancer (NSCLC) undergoing curative-intent radiotherapy (RT). Imaging biomarkers, including box-counting fractal dimension (BoxFD), lacunarity, and minimum spanning tree fractal dimension (MSTFD), were assessed for their prognostic significance. Materials and Methods: We retrospectively analyzed 166 NSCLC patients who received curative-intent RT and had both pre-treatment and follow-up chest CT scans. Among them, 85 received RT alone and 81 underwent concurrent chemoradiotherapy (CCRT). Fractal features were measured to build a Random Forest model (RFM) predicting RP of grade ≥ 2, and the most important features were used to construct a decision tree model. Results: RP of grade ≥ 2 occurred in 19 patients (22.3%) in the RT alone group and 44 patients (54.3%) in the CCRT group. Lacunarity increased significantly post-RT in both groups, while BoxFD and MSTFD showed no significant changes. In the RFM, pre-RT MSTFD and lung dose parameters (V10 in RT alone; V5–V20 in CCRT) were identified as key predictors. Decision tree models based on these features achieved high predictive performance, with AUROC of 0.83 and 0.85, and F1 scores of 0.92 and 0.76 for RT alone and CCRT groups, respectively. Conclusions: Fractal imaging biomarkers demonstrated promising prognostic value for predicting grade ≥ 2 RP in NSCLC patients. The proposed decision tree model may serve as a practical tool for early identification of high-risk patients, facilitating personalized treatment strategies and informing future research. Full article

Hardware systems are foundational to critical infrastructure, embedded devices, and consumer products, making robust security assurance essential. However, existing hardware security standards remain fragmented, inconsistent in scope, and difficult to integrate, creating gaps in protection and inefficiencies in assurance planning. This paper proposes a unified, standard-aligned, and threat-validated taxonomy of Security Objective Domains (SODs) for hardware security assurance. The taxonomy was inductively derived from 1287 requirements across ten internationally recognized standards using AI-assisted clustering and expert validation, resulting in 22 domains structured by the Boundary-Driven System of Interest model. Each domain was then validated against 167 documented hardware-related threats from CWE/CVE databases, regulatory advisories, and incident reports. This threat-informed mapping enables quantitative analysis of assurance coverage, prioritization of high-risk areas, and identification of cross-domain dependencies. The framework harmonizes terminology, reduces redundancy, and addresses assurance gaps, offering a scalable basis for sector-specific profiles, automated compliance tooling, and evidence-driven risk management. Looking forward, the taxonomy can be extended with sector-specific standards, expanded threat datasets, and integration of weighted severity metrics such as CVSS to further enhance risk-based assurance. Full article

The study represents the results of a long-term (2016 to 2021) survey on the herpetofauna inhabiting the vicinity of a heavily loaded section of the road E 87. The investigated road splits a Protected site from the net NATURA 2000 BG0000271 “Mandra-Poda”. The Protected site is known for its high biodiversity and its dense populations of vertebrates, which thrive in the area. Directly near the inspected road and on the pavement, we were able to detect five species of snakes, three species of turtles and two species of lizards. Among the squamates, rare observations were made of the European nose-horned viper (Vipera ammodytes), detected twice, and the European glass lizard (Pseudopus apodus), detected three times. Three other species—the Bloched snake (Elaphe sauromates), the Caspian whipsnake (Dolichophis caspius) and the Rhodos green lizard (Lacerta dyplochondrodes)—were found in larger numbers during some of the field surveys and here we provide information concerning the hot moments of their activity in the vicinity of the road. The Grass snakes (Natrix natrix) and the Dice snakes (N. tessellata) formed dense groups in the direct vicinity (closer than one and half meters) of the investigated road section. Despite the high number of recorded snakes and lizards, only isolated cases of vehicle collisions were observed. We suggest that the local squamate population had developed a complex of ethological specifics related to feeding, basking, shading, and copulation, which helped them to benefit from the road and avoid the risks related to the heavy traffic. Full article

Introduction: Testicular cancer is the most common cancer in young men. Studies show that general awareness among the risk group is low, and anticipatory guidance is of paramount importance for early detection. We queried pediatricians and pediatric surgeons on their perceived role and their interaction with patients regarding education on this issue. Materials and Methods: A survey was sent to pediatricians and pediatric surgeons in Germany to assess the extent of genitourinary examinations, health education about testicular cancer, and instructions for testicular self-examination during well-child visits and clinic contacts. Statistics were processed using R software (Version 4.5.1). Results: Data from 150 participating pediatricians and 21 pediatric surgeons were analyzed. Genitourinary examinations were performed routinely by the majority of participants, especially those in solo or group practices (p < 0.05). In particular, physicians who provide health education about testicular cancer perform testicular examinations significantly more often than those who do not provide such education (p < 0.05). Four percent of the participants offered a special consultation for male adolescents to provide information about male sexual diseases. There was a significant correlation between the length of experience of physicians and the level of health education (p < 0.01). Discussion: Although the majority of participants perform regular genitourinary examinations, only a minority provide special health education about testicular cancer or provide instructions for testicular self-examination. Most participating pediatricians and pediatric surgeons asked for more support regarding testicular cancer screening and health education. Full article

Corporate carbon information disclosure (CID) is gradually transitioning from being voluntary to mandatory, consistent with the global consensus on addressing climate change and achieving sustainable development. CID reflects corporate environmental performance and is a crucial source for the market to comprehend corporate environmental risks and assess their long-term value. However, corporate operations are often influenced by managers’ behavioral preferences when formulating disclosure strategies, as managerial cognitive vision and values directly affect strategic decisions. This study used a sample of Chinese A-share-listed companies for 2010 to 2023 to investigate the relationship between managerial myopia and CID. The findings indicate that managerial myopia significantly inhibits CID by reducing executive environmental awareness and corporate green innovation capabilities. A heterogeneity analysis shows that managerial myopia has a stronger inhibitory effect on CID in companies with weak governance structures and those that are not technology-intensive, providing valuable references for environmental performance and CID practice in emerging countries. Full article

Background/Objectives: To assess overall and type-specific HPV vaccine effectiveness in central and eastern Europe (CEE), the age-stratified prevalence of cervical HPV infection was determined among Slovenian women aged 20 to 64 attending a cervical cancer screening program 14 years after implementation of a national HPV vaccination program, which was then compared with 2009–2010 pre-vaccination data using the same methodological approach. Methods: Cervical samples of 4419 women were tested in 2023–2025 using the clinically validated Alinity m HR HPV Assay, and individual HPV types were determined by the Allplex HPV HR Detection assay. Results were compared with 2009–2010 pre-vaccination data generated using the same assay on an age-range matched cohort of women. Results: The overall prevalence of the 14 Alinity-targeted HPV types was 10.0% in 2023–2025 versus 13.3% in 2009–2010 (p < 0.001). HPV16 prevalence declined from 3.5% to 1.5% (p < 0.001), and HPV18 prevalence from 1.1% to 0.5% (p = 0.005). In women aged 20 to 24 with 40% uptake of quadrivalent HPV vaccine, overall HPV prevalence dropped from 25.3% to 12.8% (p < 0.001). No single case of HPV16/HPV18 infection was detected among vaccinated women. Conclusions: The first large-scale, systematic, and methodologically consistent study of HPV vaccine effectiveness in CEE showed a substantial reduction in high-risk HPV prevalence after implementation of the national program, with the greatest decline among women aged 20 to 24, who harbored the highest HPV burden in the pre-vaccination era. These locally acquired data will considerably inform public health strategies on cervical cancer elimination in CEE. Full article

Candida krusei empyema is a rare but serious manifestation of invasive candidiasis, characterized by intrinsic resistance to fluconazole, biofilm formation, and high mortality, with limited case-level data to inform management. This review aims to systematically identify and synthesize all reported English-language cases of Candida krusei empyema from January 2005 to June 2025 using PubMed, ScienceDirect, OVID MEDLINE, and Gale OneFile and perform descriptive analysis on them. Screening, data extraction, and eligibility assessment were performed, and those articles not clearly meeting eligibility criteria were reviewed by additional reviewers with consensus resolution. Seven publications (six individual cases and two cohorts) were included. We additionally describe the clinical course, management, and outcome of a 70-year-old bilateral lung transplant patient who developed persistent C. krusei empyema despite optimized antifungal therapy. Patients ranged from 11 to 74 years of age (median 62.5 years). Predisposing factors included esophageal perforation (n = 4), post-transplant hemorrhage (n = 1), community-acquired empyema (n = 1), and thoracic surgery (n = 1). Empiric fluconazole was switched to caspofungin (3/4), with others receiving amphotericin B, voriconazole, or combination therapy. Source control varied: chest tube drainage (n = 3), percutaneous catheter (n = 3), and surgical decortication (n = 2). Mortality was 14.3% (1/7). In the absence of clear guidelines and robust literature, the management approach remains heterogeneous. Optimal care requires early recognition, aggressive multimodal antifungal therapy, and effective source control tailored to patient risk. Standardized antifungal protocols and larger case series are needed to guide clinicians in managing this challenging infection. Full article

 Asbestos, consisting of six natural mineral fibrous silicate phases, was widely utilized in industrial development during the 20th century and has left a global legacy of health, environmental, and regulatory challenges. Its remarkable properties (e.g., heat resistance, sound absorption, and tensile strength) made it a useful material in numerous applications. However, scientific research revealed its serious health risks in the early 1900s, with growing evidence during the 1960s, and nowadays its role in the development of different diseases (e.g., respiratory diseases, such as lung cancer, mesothelioma, and asbestosis) is well defined. Mapping this complex history requires integrating heterogeneous and often inconsistent information from nearly 200 countries. In this study, we tested the use of generative artificial intelligence (AI) tools as exploratory and comparative instruments to support the collection of asbestos-related data worldwide. Using Google Gemini (version 2.5 flash) and OpenAI ChatGPT (GPT-4-turbo variant), we gathered historical, medical, and regulatory information and then systematically verified and contextualized it with expert analysis. This dual approach allowed us to assess both the global asbestos situation and the reliability, advantages, and limitations of AI-assisted research. Our results highlight how AI can accelerate data collection and provide useful first drafts while underscoring the necessity of human expertise for validation, interpretation, and critical integration. This study, therefore, contributes a dual perspective: a comprehensive overview of the asbestos legacy across countries and a methodological reflection on the opportunities and pitfalls of employing AI in geoscientific and environmental research.  Full article