Search Results (2,071)

Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality worldwide. This significant burden necessitates effective early identification of pregnancies at high-risk for preeclampsia. Accurate prediction is essential in order to develop and optimize preventive strategies. The evolution of preeclampsia screening has progressed from a traditional checklist-based approach to individualized, multivariable models. The first-trimester triple test, which was developed by the Fetal Medicine Foundation (FMF), represents this advancement. It utilizes Bayes’ theorem to calculate patient-specific risks by integrating maternal factors, mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor. This model, called “first trimester FMF triple test”, has undergone successful internal and external validation for the prediction of preterm preeclampsia. To ensure the reliability of biomarker measurements and achieve an optimal screening performance, it is essential to implement standardized measurement protocols and rigorous quality control processes in biomarker testing. The triple test could also be utilized in the 2nd and 3rd trimester, and the addition of biomarkers such as soluble fms-like tyrosine kinase-1 further improves risk stratification assessment and continued surveillance of high-risk pregnancies. Full article

Human norovirus (HuNoV) is the leading cause of foodborne viral gastroenteritis worldwide, yet its persistence in foods is still commonly interpreted through a simplified framework of contamination and residual survival. Accumulating evidence indicates that HuNoV persistence in food systems may be shaped by dynamic, genotype-dependent interactions with multiple classes of candidate ligands and retention mechanisms associated with hosts, food matrices, and microbiota. This review synthesizes current advances in the molecular basis and ecological consequences of these interactions, with emphasis on canonical and non-canonical glycans, HBGA-like substances, proteinaceous ligands, and bacterial surface or matrix-associated components. Structural, biophysical, and food-model studies collectively suggest that such factors may modulate capsid engagement, tissue retention, bioaccumulation, environmental stability, and, in some experimental systems, infectivity-related outcomes in representative matrices including leafy vegetables, bivalve mollusks, and bacteria-rich food environments. This multi-ligand perspective helps explain the matrix-dependent limitations of conventional washing, depuration, disinfection, and nucleic acid-based detection, as well as the frequent disconnect between measured viral signals and actual transmission risk. By linking molecular recognition to real food scenarios, this review highlights a shift from single-receptor and single-treatment perspectives toward mechanism-informed detection, risk assessment, and intervention strategies. A more integrated understanding of virus-ligand-matrix-microbiota interactions will be essential for improving the prediction and control of HuNoV foodborne transmission. Full article

Vibrio fluvialis is an important zoonotic pathogen that poses a growing threat to both public health and aquaculture, particularly to shrimp and fish farming. In this study, we report that a seafood-associated V. fluvialis strain, 10M-VF, possesses two genomic islands, SGI1-VfNDM1 and GIflu-1, in addition to hemolysins and type VI secretion systems (T6SSs). SGI1-VfNDM1 is a new member of the Salmonella genomic island 1 (SGI1) and harbors several antibiotic resistance genes. A potential transferable region, ISCR1-trpF-ble_MBL-bla_NDM-1, was observed in SGI1-VfNDM1, suggesting that ISCR1 may have mediated the integration of bla_NDM-1 into this island. Additionally, GIflu-1 represents a novel resistance island. Other GIflu variants carrying resistance genes in Vibrio all possess ISCR2, but their resistance regions vary. This indicates that ISCR2 may contribute to the integration of antibiotic resistance genes into GIflu islands. Notably, not every GIflu variant carries drug resistance genes. To the best of our knowledge, GIflu-1 is a previously unreported resistance island, and no previous report has documented the co-existence of two distinct resistance genomic islands in a single Vibrio isolate. The emergence of such resistance islands in a seafood-borne pathogen raises concerns for the maintenance and potential dissemination of clinically important resistance genes in aquatic food systems and underscores the need for ongoing surveillance of resistance determinants in seafood-borne Vibrio populations from a One Health perspective. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) arises through heterogeneous pathways involving chronic hepatitis B virus infection, hepatitis C virus infection, alcohol-related liver disease, metabolic dysfunction-associated steatotic liver disease, fibrosis, cirrhosis, and environmental exposures. Genome-wide association studies (GWASs) have identified host germline loci associated with HCC susceptibility, but interpretation is complicated by aetiology, ancestry, liver disease stage, and the definition of controls. This narrative review examines current GWAS evidence for HCC, with emphasis on aetiology-specific susceptibility, functional interpretation, cross-disorder genetic effects, and clinical translation. Methods: Studies were identified through iterative searches of PubMed/PMC, publisher pages, academic search tools, and citation tracking, supplemented by targeted searches for major HCC-associated loci. Sources were chosen based on relevance to GWAS discovery, replication, meta-analysis, functional interpretation, polygenic risk modelling, or HCC risk stratification, rather than by a formal systematic review protocol. Results: Viral HCC studies most often implicate immune regulation and antigen presentation, including MICA, HLA-DQ, HLA-DQB1, HLA class I, HCP5, STAT4, DEPDC5, and FAM114A1. Alcohol-related, metabolic, and non-viral HCC studies more often implicate hepatic lipid metabolism, telomere biology, iron metabolism, steatosis, and cirrhosis-related pathways, including PNPLA3, TM6SF2, TERT, HSD17B13, APOE, HFE, and MTARC1. Recent studies increasingly combine GWASs with fine-mapping, functional annotation, transcriptomic analyses, and risk modelling. Conclusions: HCC genetic susceptibility is highly aetiology-specific and overlaps with other liver and metabolic disorders, but discoveries from genetic studies have not yet been translated into routine clinical practice. Future work should prioritise multi-ancestry cohorts, disease-stage-aware controls, functional validation, and prospectively tested genetic risk models. Full article

Background: Antibiotics are commonly prescribed to patients with nasopharyngeal carcinoma (NPC) during chemoradiotherapy; however, peri-treatment antibiotic use may adversely affect patients’ outcomes. Methods: A retrospective cohort study was conducted. The association between antibiotic use and patients’ survival time was analyzed using Kaplan–Meier and Cox proportional hazards regression models. Results: Among 455 NPC patients, 42.0% received antibiotics around primary treatment. Patients who had an advanced tumor stage (p = 0.019) or had received neoadjuvant chemotherapy (p = 0.008) or concurrent chemoradiotherapy (p = 0.002) were more likely to be prescribed antibiotics. Univariate analysis showed that antibiotic use around primary treatment was associated with worse disease-specific survival (DSS) at both 5 years (p = 0.043) and 10 years (p = 0.019). Subgroup analysis showed that 5-year and 10-year DSS were significantly shortened in patients receiving RT only and Abx within 2 w or 1 w around RT (5-year: 2 w p = 0.001, 1 w p < 0.001; 10-year 2 w p < 0.001, 1 w p = 0.005). Conclusions: In NPC, antibiotic use around primary treatment was associated with poorer disease-specific survival. Further prospective studies are warranted to clarify the causality and underlying mechanisms. Full article

Background: Long-term care facility (LTCF) residents are highly susceptible to healthcare-associated infections, and prevention is challenging given frailty, dementia, communal living, and resource constraints. Environmental surface and air contamination contribute to transmission. Novel no-touch automated disinfection technologies have been studied in hospitals, but evidence specific to LTCFs is scarce. This scoping review summarizes recent LTCF-focused interventions, their effectiveness, and implementation considerations. Methods: This scoping review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist. We searched PubMed, Medline, Embase, CINAHL, and Scopus for observational or experimental studies evaluating environmental disinfection in LTCFs/nursing homes, excluding body decolonization, non-LTCF settings, and reviews/protocols. Two reviewers independently screened and extracted data via Covidence. This review has been registered on OSF (Open Science Framework). Results: Of 1491 records, 7 studies met the inclusion criteria (6 from the USA, 1 from Australia): one cluster randomized trial, one interrupted time series studies, three prospective observational studies, and two pre–post designs. Interventions included physical methods (HVAC-integrated UV/UVGI, continuous UVGI) and chemical approaches (dry hydrogen peroxide, room fogging plus chlorine dioxide wipes, hydrogen peroxide wipes). Outcomes were heterogeneous (surface SARS-CoV-2 RNA, COVID-19 attack/case rates, airborne/surface microbial loads, and one clinical endpoint—acute respiratory illness). Several studies reported reductions in environmental or airborne bioburden; however, UV-based studies did not demonstrate statistically significant reductions in clinical infections. Certainty was limited by small numbers, non-randomized designs, and diverse outcome measures. Conclusions: No-touch automated disinfection methods appear promising as supplements to standard infection prevention control bundles for reducing environmental contamination in LTCFs. Nevertheless, consistent clinical benefits are unproven. Rigorous, LTCF-tailored, adequately powered trials with standardized clinical and environmental outcomes, plus implementation and cost-effectiveness evaluations, are needed. Full article

Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are critical modulators of male reproductive health, influencing sperm function, hormonal regulation, and overall fertility. While physiological levels of ROS and RNS are essential for processes such as sperm capacitation and acrosome reaction, their overproduction leads to oxidative and nitrosative stress, contributing to male infertility. Excessive ROS and RNS can damage sperm DNA, proteins, and lipids, impairing motility, viability, and fertilizing capacity. Moreover, these reactive species disrupt the hypothalamic-pituitary-gonadal (HPG) axis, leading to hormonal imbalances that further compromise reproductive function. Environmental factors, lifestyle choices, and underlying health conditions exacerbate the production of ROS and RNS, highlighting the need for preventive and therapeutic strategies. Clinically, ROS- and RNS-mediated redox imbalance has been implicated in several male reproductive disorders, including varicocele, genital tract infection and inflammation, obesity, diabetes and other metabolic disorders, and toxicant-related reproductive dysfunction. Antioxidant supplementation has shown promise in mitigating oxidative stress; however, its efficacy varies, and further research is necessary to establish standardized treatment protocols. These findings underscore the clinical relevance of integrating oxidative stress assessment with conventional semen analysis to improve risk stratification and guide targeted interventions in male infertility. This review synthesizes current knowledge on the molecular mechanisms by which ROS and RNS affect male reproduction and discusses potential clinical interventions to address oxidative and nitrosative stress in male infertility. Full article

Tourism plays an increasingly important role in promoting economic growth and rural revitalization in ecologically fragile regions. However, tourism systems in Tibet–related areas of Sichuan, China, are highly vulnerable to natural disasters, ecological degradation, and regional development imbalances, posing challenges to sustainable tourism development. This study aims to evaluate tourism system resilience and identify its key influencing factors from a sustainability perspective. Based on the regional characteristics of Tibet-related areas in Sichuan, a comprehensive evaluation framework is constructed covering four subsystems: tourism infrastructure and scale, economy, society, and ecology. An integrated entropy weight–analytic hierarchy process (AHP) model, coupling coordination model, and obstacle degree model are employed to assess tourism system resilience and examine subsystem interactions using panel data from 2011 to 2020. The results indicate that: (1) the resilience levels of tourism subsystems show no clear spatial or temporal regularity across the study areas; (2) ecological resilience remains significantly lower than tourism, economic, and social resilience, representing the weakest component of the tourism system; (3) the coupling coordination among subsystems remains at a low level, suggesting insufficient synergy for sustainable regional development; and (4) ecological constraints are the primary limiting factors affecting overall tourism system resilience. This study contributes to sustainable tourism research by revealing the critical role of ecological governance and subsystem coordination in enhancing tourism resilience in ecologically sensitive regions. Policy implications include strengthening ecological protection, improving tourism infrastructure, promoting digital tourism marketing, and advancing rural revitalization to achieve long-term sustainable development. However, this study is limited by data availability and the spatial scope of the selected case-study areas, which may affect the generalizability of the findings. Full article

Problem sets are widely used in economics education, but the availability of generative artificial intelligence creates new challenges for assessment validity and academic integrity. This study conducts a rating-based benchmarking evaluation of GPT-4o on introductory economics problem-set items. Using 260 rated questions and three independent instructor ratings per item, we examine how GPT-4o performance varies across discussion, numerical, graphical and mixed-modality questions. The study is descriptive rather than causal: it benchmarks GPT-4o outputs under a specified prompting, input-modality and scoring protocol. All items were submitted through the ChatGPT web interface in fresh sessions, each item was answered once, graphical items were provided through uploaded original diagram images, no follow-up prompts were used, and outputs were saved without editing. Results show that GPT-4o performs comparatively well on text-based discussion and numerical-only items, but substantially less well on graphical items, especially those requiring numerical reasoning grounded in a graph. Inter-rater reliability is high according to intraclass correlation coefficients, and pooled rater–item analyses confirm the graphical and graphical–numerical performance gap as a descriptive benchmark pattern. To improve reproducibility while respecting copyright restrictions, the revised manuscript specifies the prompting protocol, coding procedure, rater procedure and supplementary replication files. The findings suggest that economics instructors should not simply add graphical questions as an “AI-proof” device, but should design constructively aligned, accessible, mixed-format assessments that validly sample intended economic reasoning skills. The conclusions are restricted to GPT-4o, the February–June 2025 testing window, the ChatGPT web-interface protocol and the item corpus used in this study. Full article

Analog in-memory computing (AIMC) has emerged as a promising approach to mitigate the Von Neumann bottleneck in matrix operations, which are common in deep learning applications. However, the practical implementation of resistive crossbar arrays is limited by challenges in signed weight representation, conductance quantization, and device nonlinearity. This paper presents a differential mixed-signal architecture for accurate signed matrix–vector multiplication (MVM), integrated with a RISC-V microcontroller for edge inference applications. A structured digital-to-analog mapping framework encodes quantized neural network weights into programmable conductance values while preserving arithmetic correctness. The design employs voltage-mode input encoding, differential current summation, and transimpedance-based readout followed by analog-to-digital conversion, enabling single-cycle signed accumulation without duplicating crossbar resources. A 32 × 16 dual-layer prototype crossbar was fabricated and experimentally characterized. Measurements demonstrate a mean absolute percentage error (MAPE) below 1% within the linear operating region and below 4% over the full-scale conductance range. These results validate the robustness of the proposed mapping methodology and confirm the feasibility of hybrid analog–digital acceleration for edge AI systems. Consequently, this discrete prototype serves as a physical verification platform for the AIMC approach, providing valuable insights for more efficient mixed-signal computing integrated circuit (IC) designs. Full article

Endothelial dysfunction (ED) is an early event in cardiovascular and metabolic diseases, including atherosclerosis, diabetes, and hypertension. Emerging evidence highlights the interplay between chronic inflammation and oxidative stress, collectively termed OxInflammation, as a major driver of vascular injury and impaired tissue repair. Among the key mediators of this response is the Nod like receptor family pyrin domain containing 3 (NLRP3) inflammasome, a multiprotein complex that promotes the release of inflammatory cytokines, including Interleukin 1β (IL-1β) and Interleukin-18 (IL-18), and induces gasdermin D-mediated pyroptotic cell death. Activation of NLRP3 disrupts endothelial function, reduces nitric oxide availability, and accelerates vascular inflammation and injury. This review discusses current evidence on pharmacological strategies targeting NLRP3 inflammasome signaling using both natural and synthetic inhibitors. Studies have shown that inhibiting NLRP3 can reduce inflammation and oxidative stress, preserve endothelial integrity, improve vascular function, and support tissue repair. Several NLRP3-targeting compounds have advanced into early-phase clinical trials, showing encouraging safety profiles and efficacy in individuals with cardiovascular risk factors. By integrating the emerging concept of OxInflammation with endothelial dysfunction, this review critically evaluates the therapeutic and translational potential of NLRP3 inflammasome inhibition in cardiovascular and metabolic disorders. Collectively, the available evidence supports NLRP3 as a promising therapeutic target for restoring endothelial homeostasis and promoting vascular repair. However, further clinical studies are needed to establish long-term efficacy, optimal dosing strategies, and appropriate patient selection criteria. Full article

Accurate multi-channel gas concentration prediction is very important for coal mine safety. However, the dynamic reconstruction of the sensor network often interferes with the input sequence. Existing models face a critical trade-off: channel-independent models are robust to sequence changes but ignore spatial coupling, while channel-dependent models overfit fixed sequences, leading to performance collapse during rearrangements. This paper presents a gas concentration prediction framework based on channel permutation-invariant interaction (CPiRi) to reconcile these limitations. CPiRi employs a spatio-temporal decoupling architecture where a frozen univariate pre-trained encoder independently extracts temporal features to ensure sequence robustness. Subsequently, a permutation-equivariant spatial module utilizes self-attention to model inter-channel gas emission relationships based on data content rather than positional indices. To achieve true permutation invariance, we introduce channel-shuffling regularization during training, forcing the model to learn content-driven relational reasoning. Evaluations on 15 real-world Chinese coal mine datasets demonstrate that CPiRi achieves highly competitive accuracy and consistently outperforms mainstream baselines in both prediction precision and structural adaptability. This study offers a robust technical pathway for gas monitoring in dynamic environments, substantially improving the reliability of intelligent mine safety systems. Full article

Background: Radiation dermatitis (ARD), particularly its most severe form, moist desquamation (MD), is a frequent and distressing complication of external beam radiotherapy (RT) in head and neck (H&N) cancer patients. Standard management often provides limited benefit for healing and symptom control. Silicone-based foam dressings, including Mepilex Lite and Mepilex Ag, may offer atraumatic adherence, moisture balance, and pain reduction. This study evaluated their real-world effectiveness for MD after conventional RT. Methods: Ten H&N cancer patients with clinically confirmed MD post-radiotherapy were prospectively followed until healing. Patients received Mepilex Lite or Mepilex Ag based on exudate level and infection risk, with dressings changed every three days. Patient- and healthcare provider-reported measures were collected throughout follow-up. The primary endpoint was time to MD resolution, defined as healing to grade 1 skin status. Secondary endpoints included changes in symptom burden, dressing tolerability and satisfaction, and adverse events. Results: Median age was 69 years (range 44–78). All wounds healed to grade 1, with a mean time of 8.6 days (SD 3.9). No infections or adverse events occurred. Pain, burning, and interference with daily activity decreased, and most patients reported improved comfort. Conclusions: In this small prospective cohort study, use of Mepilex dressings was associated with rapid healing, good tolerability, and improvement in patient-reported symptoms of acute radiation dermatitis. These findings suggest that Mepilex dressings may be a promising management option and warrant evaluation in larger comparative studies. Full article

Introduction: Skates (Rajidae) are cornerstone elasmobranchs, yet their intrinsic biological constraints, like slow growth, late maturation, and low fecundity, render them exceptionally susceptible to anthropogenic pressure. Despite their ecological and economic importance, tracking their population trajectories is historically hindered by “taxonomic blurring” and aggregated reporting in commercial fisheries. Objective: This study evaluates long-term conservation trends and exploitation dynamics of Rajidae species in the Northeast Atlantic and the Mediterranean Sea. Methodology: We analyzed 31 Rajidae species across the Northeast Atlantic and the Mediterranean Sea (FAO Areas 27 and 37) by integrating IUCN Red List assessments, species-specific life-history traits (maximum body size and depth distribution), and FAO fisheries landing data from 1992 to 2023. Descriptive analyses and Spearman correlations were used to assess temporal trends in conservation status and exploitation patterns. Results: Our synthesis reveals that some species show improvements in IUCN Red List category assessments, likely driven by recent management interventions such as species-specific reporting, catch quotas, and targeted retention bans. However, we also identify a critical mismatch between policy and biology: current Total Allowable Catches (TACs) and minimum landing sizes often do not explicitly incorporate species-specific life-history traits, inadvertently favoring smaller, less-marketable taxa while leaving larger, vulnerable species at risk. While FAO landings offer a valuable broad-scale overview of exploitation, the results highlight the limitations of aggregated fisheries statistics for species-level conservation assessments. Conclusions: These findings underline the need to adopt more precise and species-specific fisheries management approaches for Rajidae, including expanded regional monitoring programs, the use of data collected by on-board observers or electronic monitoring tools, and improved control of data reporting procedures, to prevent continued aggregation of species-level data. Full article

Accurate assessment of carbon storage dynamics and their driving factors is important for ecological sustainability and land management on the Loess Plateau under China’s dual carbon goals. In this study, the InVEST and PLUS models were integrated to evaluate carbon storage changes from 2000 to 2020 and simulate future carbon storage patterns for 2030 under four development scenarios, including natural development (ND), rapid development (RD), cropland protection (CP), and ecological protection (EP). In addition, the XGBoost-SHAP framework was employed to identify the dominant drivers and nonlinear response relationships controlling spatial variation in carbon storage. During 2000–2020, ecosystem carbon storage across the Loess Plateau generally increased, rising from 5.780 Pg to 5.893 Pg. Spatially, carbon storage displayed a pronounced pattern characterized by higher levels in the southeast and lower levels in the northwest, aligning with forest–grassland restoration belts. Scenario simulations showed that EP produced the largest carbon storage gain, with total carbon storage projected to reach 5.962 Pg in 2030. In contrast, RD reduced carbon storage to 5.858 Pg because of intensive construction land expansion. XGBoost-SHAP results identified net primary productivity (NPP) as the most influential factor controlling spatial variation in carbon storage, accounting for 57.3% of the total explanatory importance, whereas soil erosion (SE) exhibited a strong negative effect on carbon storage. Population density (POPD) also exerted a negative effect, whereas gross domestic product (GDP) showed positive contributions in economically developed counties. These findings enhance understanding of the spatial response characteristics of carbon storage under environmental gradients and human disturbance across the Loess Plateau. They further provide scientific support for differentiated ecological management and regionally adapted carbon mitigation planning. Full article