Search Results (2,369)

Background: This study examined age-related differences and interrelationships among psychological symptoms, personality traits, and emotional expression styles in a community sample of 151 participants aged 10–77 years, spanning four age groups: adolescents, young adults, middle-aged adults, and older adults. Methods: Psychological symptoms were assessed using the SCL-90, personality traits using the Big Five Inventory-2 (BFI-2), and emotional expression patterns were derived from facial expression recognition via a convolutional neural network (CNN) model. Kruskal–Wallis H tests were used to examine age-related differences. K-means cluster analysis was applied to identify emotional expression patterns, and logistic regression was used to construct a mental health risk screening model. Results: The young adult group (19–35 years) achieved the highest scores on the depression (M = 1.73) and anxiety (M = 1.61) dimensions, indicating a higher level of psychological distress during this life stage. Personality traits showed a significant developmental trajectory: neuroticism decreased with age (H(3) = 17.09, p < 0.001, η² = 0.11), declining from 2.69 in the young adult group to 2.17 in the older adult group; conscientiousness increased with age (H(3) = 37.39, p < 0.001, η² = 0.24), representing the most substantial age-related effect. K-means clustering identified three distinct emotional expression patterns: Cluster 1 was characterised by happiness, Cluster 2 by anger, disgust, and fear, and Cluster 3 by neutrality, sadness, and surprise. Cluster 2 exhibited the highest scores on neuroticism, anxiety, depression, and mood swings, and scored significantly higher than the other two clusters on interpersonal sensitivity, depression, anxiety, and hostility (p < 0.05). Mental health risk screening indicated that 26.5% of participants were classified as high-risk. Logistic regression analysis (AUC = 0.742) showed that neuroticism was the strongest predictor of elevated mental health risk (OR = 4.58), while extraversion (OR = 0.41) and conscientiousness (OR = 0.57) were significant protective factors. Conclusions: These findings provide exploratory evidence regarding age-related patterns of psychological symptoms and personality traits in a convenience sample and offer preliminary support for personality-based mental health risk screening. Notably, the SCL-90 was employed as a screening tool rather than for clinical diagnosis. Given the unequal age group sizes, particularly the small young adult subgroup, generalisability across the lifespan should not be assumed. Full article

The advancement of sustainable energy is a key component of the achievement of the Sustainable Development Goals. Technology advancements have made tidal current energy (TCE) a promising renewable energy source. China possesses abundant TCE resources and has gradually incorporated TCE into its energy and marine development policies. In China, TCE projects are currently being implemented on a large scale. However, despite policy-level recognition, TCE development in China has received limited regulatory attention, particularly with respect to environmental protection and ecological risk governance. Existing governance frameworks largely rely on general marine environmental and ecological policies, which are insufficient to address the three-dimensional, underwater characteristics and cumulative ecological risks. This study analyzes the evolution of China’s TCE-related laws and policies and identifies key deficiencies in current environmental regulation. To promote the sustainable TCE projects, the paper proposes tentative recommendations to promote the sustainable development of TCE in China, including the formulation of specialized environmental impact assessment guidelines grounded in the precautionary principle, future policies for addressing the cumulative environmental impact of large-scale TCE deployment, and the establishment of an environmental risk assessment system tailored to the data limitations and ecological characteristics of TCE exploitation. Full article

Introduction: Artificial intelligence (AI) and robot-assisted platforms are increasingly influencing cardiothoracic surgery. AI enhances risk prediction, imaging interpretation, and early complication detection, while robotics improves visualization, dexterity, and minimally invasive access. This systematic review evaluates the current evidence supporting these technologies and their implications for clinical practice. Methods: A systematic literature search was conducted across PubMed, Embase, Scopus, Web of Science, and Google Scholar (January 2000–May 2025) following PRISMA 2020 guidelines. After screening and eligibility assessment, 67 studies met predefined inclusion criteria and were incorporated into the qualitative synthesis. Additional high-impact reviews and consensus documents were consulted for contextual interpretation. Results: Machine learning models demonstrated modest but consistent improvements in predictive performance compared with EuroSCORE II and STS scores, particularly in high-risk cohorts. Robot-assisted mitral and coronary procedures showed reduced postoperative pain, blood loss, ICU stay, and recovery time in experienced centers, though early learning phases were associated with longer operative, cross-clamp, and bypass times. AI-enabled intraoperative tools, such as video analysis, workflow recognition, and real-time anatomical segmentation, emerged as promising adjuncts for surgical precision. Structured robotic training programs, especially simulation-based and dual-console pathways, accelerated proficiency acquisition. Conclusions: AI and robotic systems act as augmentative technologies that enhance rather than replace the surgeon’s role. Their safe and effective adoption requires standardized training, transparent AI decision pathways, and clear ethical and medico-legal governance. Full article

Wearable device-based Human Activity Recognition (HAR) is widely used in health management, rehabilitation, and personal safety. While contemporary HAR research effectively classifies a wide range of discrete activities, there remains a significant gap in organizing these heterogeneous motions into a structured intensity framework suitable for continuous risk assessment. Furthermore, many high-performing models rely on computationally intensive architectures that hinder real-time deployment on resource-constrained wearables. We propose an on-device method for estimating five-level activity intensity in real time using only accelerometer signals from a commercial smartwatch. To bridge the gap between simple identification and intensity modeling, 13 dynamic and emergency-like wrist motions were integrated with 11 daily activities from the PAMAP2 dataset, yielding 21 activities mapped onto an ordinal five-level intensity scale. A finetuned Multi-Layer Perceptron (MLP) classifier trained on this integrated dataset achieved 0.939 accuracy and a quadratic weighted kappa (QWK) of 0.971. The model was deployed on a Galaxy Watch 7, achieving $<1$ ms inference latency and a size $<0.1$ MB, confirming real-time feasibility. This approach demonstrates that organizing diverse activities into a lightweight, intensity-aware framework provides a robust foundation for safety-aware monitoring systems under real-world, on-device constraints. Full article

Caffeine is widely consumed and generally considered safe at customary doses. How-ever, high-dose preparations available online pose a risk of severe and potentially fatal intoxication. Although uncommon, lethal caffeine poisoning is associated with profound cardiovascular and neurological toxicity. A rare case of intentional acute caffeine intoxication with fatal outcome is presented. A 25-year-old woman ingested an estimated 60 tablets containing 200 mg of caffeine each, purchased online. She was admitted to hospital shortly after ingestion of the caffeine tablets with palpitations, agitation, dizziness, and repeated vomiting. On examination, she presented with arterial hypotension (90/60 mmHg) and marked sinus tachycardia (150 beats/min), accompanied by psychomotor agitation. Her blood caffeine concentration measured by means of high-performance liquid chromatography (HPLC) was 177 µg/mL. The patient’s condition rapidly deteriorated, with the development of convulsive syndrome progressing to coma, extreme ventricular tachycardia, exotoxic shock, and toxic cardiomyopathy. Despite intensive care management, including mechanical ventilation and advanced cardiopulmonary resuscitation, the patient died several hours after admission. In conclusion, this case underscores the life-threatening potential of acute high-dose caffeine ingestion and highlights the risk associated with unrestricted access to concentrated caffeine products. Early recognition and aggressive management are crucial, yet may be insufficient in cases of massive overdose. Full article

Background/Objectives: Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most consumed drugs worldwide and the main cause of drug hypersensitivity reactions (HSRs). The most common NSAID-HSR class is cross-hypersensitivity (CR), with patients reacting to NSAIDs from different chemical groups without specific immunological recognition, with NSAID-induced acute urticaria/angioedema (NIUA) being the most frequent clinical phenotype. Although CR-HSRs are triggered by arachidonic acid (AA) alterations following cyclooxygenase (COX)-1 inhibition and cysteinyl-leukotrienes synthesis by 5-lypoxygenase (5-LO), current evidence supports the participation of additional mechanisms. As COX-1 and 5-LO head oxidative pathways, it is conceivable that enzymes participating in antioxidant control are involved in these mechanisms. In addition, as the CR-HSR susceptibility seems to be influenced by genetic factors, the possibility of genetic variants playing a role in such enzymes should not be excluded. Methods: In this observational case–control study, we analysed for the first time in NIUA the overall genetic variability in key antioxidant defence enzymes genes, including catalase (CAT), glutathione peroxidase (GPX)-1 and 3, and superoxide dismutase (SOD)-1. We selected a set of tagging single nucleotide polymorphisms (tSNPs) in these genes using data from Europeans in the 1000 Genomes Project. Two independent Spanish populations (discovery and replication) of NIUA patients and NSAID-tolerant individuals were included. Results: Twenty-six tSNPs were genotyped in the discovery population, with three that were significantly associated with NIUA: rs3448 (GPX-1), rs3792798 (GPX-3), and rs10432782 (SOD-1). They were then genotyped in the replication group, with rs3792798 being protective and rs10432782 being associated with an increased NIUA risk. Conclusions: Our results suggest that a role for antioxidant enzyme polymorphisms in NIUA is required. Nevertheless, further research is needed to replicate our findings in other populations and their meaning at the molecular level and to investigate the role of such variants in other CR-HSR-induced phenotypes. Full article

Background/Objectives: Acute severe ulcerative colitis (ASUC) affects up to one quarter of patients with ulcerative colitis and carries a substantial risk of colectomy. Early recognition of the need for escalation beyond intravenous (IV) corticosteroids is essential, yet most indices—such as the Oxford criteria—require reassessment on day 3, delaying rescue therapy. The ASUC score, based on admission albumin, C-reactive protein (CRP), endoscopic severity (Ulcerative Colitis Endoscopic Index of Severity, UCEIS), and pre-admission steroid use, was recently proposed to predict early escalation at admission. This study aimed to externally validate the ASUC score and compare its performance with established indices. Methods: We performed a single-center retrospective validation study including consecutive ASUC admissions (2015–2024). The primary outcome was escalation beyond IV steroids, defined as medical rescue therapy with infliximab or ciclosporin and/or colectomy during the index hospitalization. As a sensitivity analysis providing a more specific estimate of IV corticosteroid non-response, we repeated analyses restricting the outcome to medical rescue therapy alone. The model performance was assessed for discrimination (AUC and bootstrap-corrected 2000 resamples), calibration (intercept, slope, and Brier score), and clinical utility (decision-curve analysis). Comparator indices included Albumin-CRP-Endoscopy score (ACE), Admission Model for Acute Severe Colitis (ADMIT-ASC), Oxford Day 3, Lindgren, and Edinburgh. Predefined subgroup analyses (exploratory and underpowered) evaluated infection and biologic exposure. Results: Ninety-one admissions were included overall. The primary validation was performed in the infection-free cohort (n = 77), and infected cases (n = 14) were analyzed separately. In the infection-free cohort, 17/77 (22.1%) required escalation beyond IV steroids during the index hospitalization (medical rescue therapy and/or colectomy), and 5/91 (5.5%) underwent colectomy within 90 days. The ASUC score showed excellent discrimination (Area under the receiver-operating characteristic curve [AUC] 0.89, 95% Confidence Interval [CI] 0.81–0.95), good calibration (intercept 0.26, slope 1.29), and net clinical benefit across 30–50% thresholds. In the rescue-only sensitivity analysis, discrimination remained high (AUC 0.86, 95% CI 0.77–0.94). At a cut-off of ≥2, sensitivity 94% and specificity 78% outperformed other indices (AUC 0.62–0.83). Exploratory subgroup analyses were imprecise due to small sample sizes; discrimination was lower in the infected-only subgroup (AUC 0.71), and estimates in biologic-experienced patients were unstable because of severe imbalance. Conclusions: The ASUC score accurately identified patients likely to require escalation beyond IV steroids on the day of admission, outperforming or matching established day-3 indices. Its simplicity and reliability support its integration into early ASUC management to expedite rescue therapy and potentially improve outcomes. Full article

International travel has increased significantly in recent years. Many travellers are immunocompromised, making them more susceptible to infectious diseases due to their weakened immune systems. This narrative review provides an overview of infection epidemiology, prevention strategies, and clinical management for immunocompromised travellers. We demonstrate the role of pre-travel consultation, emphasizing individualized risk assessment informed by destination-specific epidemiology, immune status, and underlying conditions. Key preventive interventions, including vaccination strategies, antimicrobial prophylaxis, and detailed health counseling, in addition to practical measures that can be taken to minimize infection risk during travel, are addressed. Post-travel surveillance and early recognition of travel-related infections are analyzed, highlighting the importance of prompt symptom evaluation. Effective care for immunocompromised travellers requires a multidisciplinary framework that integrates patients, primary care physicians, infectious disease specialists, and travel medicine experts. Full article

Background: Exacerbations of chronic obstructive pulmonary disease (COPD) are a leading cause of morbidity, mortality, and healthcare burden worldwide. Early detection and timely intervention remain important challenges in COPD management, given the unpredictable nature of acute deterioration and limitations of traditional spirometry-based risk assessment. Methods: This narrative review synthesizes artificial intelligence (AI)-driven approaches for predicting and detecting chronic obstructive pulmonary disease (COPD) exacerbations across electronic health records, wearable sensors, imaging, environmental data, and patient-reported outcomes, emphasizing novel discoveries and emerging relationships rather than predictive performance. Results: Three major discoveries have been made. First, measurable physiological and behavioral deterioration may precede symptom recognition by approximately 7–14 days, thereby establishing a potential intervention window for anticipatory care. Second, machine learning (ML) models integrating pollutant exposure, medication adherence, and clinical characteristics have identified phenotypes with differential environmental sensitivity, including unexpected exposure–adherence interactions. Third, deep neural network analysis of full spirometry curves has revealed structural phenotypes beyond traditional Forced Expiratory Volume (FEV₁)-based measures and novel imaging biomarkers. The predictive performance ranges from the Area Under the Curve (AUC) 0.72–0.95, with a pooled meta-analytic AUC of approximately 0.77. Conclusions: AI has uncovered hidden patterns in the progression of COPD, supporting a shift from reactive to anticipatory management. Translation to routine care requires prospective validation, improved interpretability, workflow integration, and generalizability and equity. Full article

Background: Liquid biopsy using circulating tumor DNA (ctDNA) is rapidly reshaping gastrointestinal (GI) oncology. The highest-impact applications are molecular residual disease (mRD) detection after curative-intent therapy and early recognition of progression or resistance during systemic treatment. Methods: We performed a structured, clinically oriented narrative synthesis by using explicit search, eligibility, evidence prioritization, and clinical interpretation rules, integrating landmark prospective cohorts, randomized ctDNA-guided strategy trials where available, meta-analyses, key methodological research (e.g., pre-analytics, assay design, and clonal hematopoiesis (CH)/clonal hematopoiesis of indeterminate potential (CHIP)), and selected trial registries. Results: In resected colorectal cancer (CRC), postoperative ctDNA positivity is among the strongest known biomarkers of recurrence risk; large prospective studies demonstrate clear separation of disease-free survival (DFS)/overall survival (OS) between mRD+ and mRD− patients. In stage II colon cancer, randomized data (DYNAMIC) show that a ctDNA-guided strategy reduces adjuvant chemotherapy exposure without compromising long-term outcomes. In metastatic CRC, ctDNA supports early response monitoring and resistance tracking; ctDNA-selected anti-EGFR rechallenge provides a model of biomarker-driven actionability (CHRONOS). In gastroesophageal cancers, longitudinal ctDNA dynamics correlate with relapse risk and treatment efficacy, and in esophageal squamous cell carcinoma, ctDNA after neoadjuvant chemoradiotherapy informs residual disease risk and adjuvant stratification. In pancreatic ductal adenocarcinoma and hepatobiliary malignancies, sensitivity is constrained by low shedding and background cell-free DNA (cfDNA), yet ctDNA positivity remains clinically meaningful, and emerging data in resected extrahepatic cholangiocarcinoma (STAMP-linked analyses) show that ctDNA dynamics during adjuvant therapy predict recurrence. Conclusions: ctDNA is a clinically validated biomarker for mRD in CRC, whereas in other GI cancers, it remains a promising but methodologically heterogeneous tool whose clinical utility is tumor- and context-dependent. The next phase requires interventional trials demonstrating outcome improvement, harmonized sampling and reporting standards, and rigorous control of confounders (notably CH/CHIP). Full article

The immunosuppressive nature of porcine reproductive and respiratory syndrome virus (PRRSV) remains the central obstacle to its effective control. Conventional microRNA (miRNA)-based antiviral approaches are limited by their modest potency and the high risk of viral escape. Here, we rationally designed an engineered miRNA carrying a 5′-triphosphate (5′-PPP) terminus that integrates RIG-I-driven innate immune activation and sequence-specific gene silencing within a single molecule. In vitro-transcribed 5′-PPP miRNAs are efficiently recognized by the pattern-recognition receptor RIG-I, triggering a robust type I interferon response that counteracts PRRSV-induced immunosuppression. In MARC-145 cells, one such construct, 5′-PPP BZL-sRNA-20, potently inhibited PRRSV replication through the synergistic action of immune activation and gene silencing. However, in porcine alveolar macrophages (PAMs)—the natural host cells for PRRSV—the antiviral effect depended primarily on 5′-PPP-induced interferon responses, with the targeting sequence providing limited or context-dependent benefits. Dual-luciferase assays confirmed that the gene-silencing activity depends on 5′-PPP modification, which enhances the stability of BZL-sRNA-20. This bifunctional strategy establishes an “immune activation plus targeting” paradigm by simultaneously acting as a RIG-I ligand that triggers broad antiviral responses and specifically cleaves viral RNA via direct base-pairing to conserved regions of the PRRSV genome. These findings reveal the potential of engineered 5′-PPP miRNAs as immunomodulatory antiviral agents, while highlighting that the contribution of RNAi targeting varies depending on the cellular context. Full article

Pregnancy loss affects ~15% of couples and often results from embryonic chromosomal abnormalities. Early peripheral biomarkers that signal abnormal development could improve counseling and clinical decision-making. Here, we analyzed early-pregnancy peripheral blood from patients who conceived via assisted reproduction without preimplantation aneuploidy testing. Samples were collected ≤12 weeks’ gestation for complete blood counts with differentials and multiparameter flow cytometry to quantify major lymphocyte subsets (total T, B, cytotoxic T cells, T helpers (Th), Th1, Th2, Th9, Th17, and regulatory T cells (Treg)). Participants were followed until pregnancy resolution (live birth, euploid or aneuploid miscarriage), and immune profiles were compared by outcome using the Kruskal–Wallis test. Exploratory discriminative analyses were performed with significantly different immune cell quantities. Basophils were highest in the aneuploid miscarriage group (n = 26), distinguishing them from both euploid miscarriage (n = 27) and live birth (n = 91). Th9 cells were lower in aneuploid miscarriages compared to euploid miscarriages. Th17 levels were higher in live births compared with both miscarriage groups. Additional aneuploidy-type-specific immune differences were observed. These alterations may reflect maternal immune recognition of a non-viable conceptus and localized immune activation at the fetal–maternal interface. If validated in larger cohorts, these early peripheral markers may help identify pregnancies at risk for miscarriage, particularly those involving chromosomal abnormalities. Full article

Background: Depression in men often goes unrecognized, even though it leads to high rates of suicide. Men may show symptoms that are external, behavioral, or physical, which traditional assessment tools focused on internal symptoms do not adequately reflect. Methods: A narrative review was carried out to gather evidence on depression scales tailored for men. We searched PubMed up to November 2025 for studies discussing the development, validation, and clinical use of the Gotland Male Depression Scale (GMDS), the Male Depression Risk Scale (MDRS-22 and MDRS-7), and the Gender-Sensitive Depression Screening scale (GSDS-26). We organized the findings by instrument. Results: The studies indicate that male-sensitive scales capture symptom domains such as emotional suppression, anger, risk-taking behaviors, substance misuse, and somatic complaints. The GMDS has demonstrated applicability across psychiatric, somatic, and paternal perinatal populations. The MDRS-22 and MDRS-7 were particularly sensitive to externalizing symptom patterns associated with male presentations of depression and behavioral profiles linked to elevated suicide risk. The GSDS-26 integrates both prototypical and externalizing symptoms, enabling the identification of diverse depressive profiles. However, the current evidence base remains limited due to a reliance on non-clinical samples and the scarcity of long-term and cross-cultural validation studies. Conclusions: Male-sensitive depression scales may serve as useful complementary screening tools that improve recognition of male-typical depressive presentations and behavioral patterns associated with increased suicide risk. Further clinical and longitudinal research is needed to confirm their diagnostic accuracy and clinical utility. Full article

The risks associated with hazardous materials (HazMat) transportation exhibit typical characteristics of chain-like distribution, spatiotemporal regularity, and individual heterogeneity. A personalized trip-chain feature spectra recognition framework for HazMat vehicles is proposed to enhance the capability to assess and analyze individual risks using vehicle positioning data. The proposed framework addresses the challenges of deriving personalized risk feature maps arising from missing real-time trajectory data, complex sub-trip-chain segmentation, and the extraction of personalized risk feature representations. An improved conditional Wasserstein Generative Adversarial Network (WGAN) model is initially developed to impute trajectories with missing positional data, and it can robustly reconstruct trajectories with large-scale missing segments by integrating a multi-head self-attention mechanism and a gradient penalty. A two-layer clustering algorithm, K-Means-multiplE-THreshOlds-adaptive-DBSCAN (KMETHOD), which combines an adaptive mechanism with threshold rules, is subsequently designed to identify the dwell time and related spatial attributes of dwell points along vehicle trips. A BERT-based model is incorporated to filter Points of Interest (POIs) around dwell points, which enables the extraction of their detailed location semantics and trip characteristics and thus supports trip chain identification and segmentation. A threshold-activated multilayer trajectory feature-map method (TAFEM) is constructed to generate feature maps for each trip chain. The Liquefied Natural Gas (LNG) transportation trajectory data from Guangdong Province is selected to evaluate the effectiveness of the proposed methods. The experimental results demonstrate that the proposed framework can effectively identify trip chains and generate their corresponding feature maps. The trajectory imputation model achieved the Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Dynamic Time Warping (DTW) of 2.34–3.33, 6.05–7.74, and 0.74–1.21, respectively, across different missing-rate scenarios, outperforming other benchmark models. The identification accuracy of dwell-point duration and location reaches 98.35%. The BERT-based method achieves a maximum accuracy of 92.83% in origin–destination (OD) point recognition, effectively capturing comprehensive trip-chain information. TAFEM accurately characterizes the spatiotemporal distribution and potential causal factors of personalized HazMat transportation safety risks, providing a reliable foundation for risk identification and safety management strategies. Full article

Background/Objectives: Pelvic injuries are frequently associated with severe hemorrhage and may contribute to early trauma-induced coagulopathy (TIC). Whether pelvic injury is independently associated with TIC beyond overall injury severity remains unclear. The objective of this study was to evaluate the association between pelvic injury and TIC in severe trauma patients. Methods: We conducted a retrospective single-center study including adult severe trauma patients (injury severity score > 15) admitted between January 2012 and July 2020. Patients with moderate to severe traumatic brain injury (because of its specific coagulopathy and mortality), inter-hospital transfer, pregnancy, or long-term anticoagulant or antiplatelet therapy were excluded. Pelvic injury was defined as any traumatic lesion involving the pelvic girdle identified on admission computed tomography. TIC was defined by an international normalized ratio (INR) > 1.2 and/or fibrinogen < 1.5 g/L and/or platelet count < 100 G/L. Multivariable logistic regression was performed to identify factors associated with TIC. Results: Among 388 included patients (79.6% male, median age 39 years), 114 (29.4%) had a pelvic injury. TIC was present in 160 patients (41.3%), and TIC prevalence was significantly higher in patients with pelvic injury (n = 73–64.0%) compared to those without (n = 87–31.8%) (p < 0.001). After multivariate analysis, TIC was independently associated with pelvic injury (OR 2.81, 95% CI 1.63–4.89), shock index > 0.9 (OR 1.94, 95% CI 1.12–3.37), hemoglobin < 10 g/dL (OR 4.27, 95% CI 1.77–11.49), and lower base excess values on admission (OR per unit increase 0.92, 95% CI 0.87–0.97). Injury severity score and number of lesions (AIS ≥ 3) were not independently associated with TIC. Conclusions: Pelvic injury was independently associated with TIC after adjustment for injury severity, number of severe injuries, and markers of hemodynamic and metabolic shock, including shock index, hemoglobin level, and base excess. These findings suggest that patients with pelvic injury may represent a high-risk subgroup for early coagulopathy, supporting the need for early recognition and adapted resuscitation strategies. Further prospective studies are required to explore underlying mechanisms. Full article