Search Results (14,122)

Understanding the circulation of influenza A viruses and other respiratory pathogens in Antarctic wildlife is essential for anticipating outbreaks and evaluating potential impacts on vulnerable populations. During the austral summer of December 2024 and January 2025, we conducted viral surveillance in six bird species breeding at Lions Rump, King George Island, South Shetland Islands, Antarctica. A total of 199 individuals were sampled, including Pygoscelis papua (gentoo penguin; n = 81), Pygoscelis adeliae (Adélie penguin; n = 79), Pygoscelis antarcticus (chinstrap penguin; n = 34), Stercorarius antarcticus (brown skua; n = 2), Chionis albus (snowy sheathbill; n = 2), and Eudyptes chrysolophus (macaroni penguin; n = 1). All cloacal and oropharyngeal swabs tested negative for influenza A viruses and coronaviruses by RT-PCR. Blood samples from 177 birds were screened by enzyme-linked immunosorbent assay, which detected influenza A virus antibodies in 20 individuals (11.3%). Hemagglutination inhibition assays identified subtypes H6 and H11 in two penguins and H1, H5, H6, and H9 in one skua. These findings reveal no evidence of active viral infection during the sampling period but provide serological evidence of past exposure in seabird populations at Lions Rump. Continued surveillance is essential to characterize viral dynamics in Antarctic ecosystems and to support early detection and preparedness for potential incursions of emerging high-pathogenicity influenza A viruses. Full article

Respiratory infections are a leading cause of hospitalization and mortality in children, and the pediatric intensive care unit (PICU) is a critical setting for managing severe cases. However, the epidemiological patterns of respiratory pathogens in the PICU remain insufficiently characterized. In this retrospective study, we analyzed respiratory pathogen testing results from 2126 pediatric patients admitted to the PICU of Wuhan Children’s Hospital between 2019 and 2024. The pathogen spectrum and epidemiological characteristics were evaluated across age groups and seasons. Respiratory syncytial virus (RSV, 18.06%) was the most frequently detected viral pathogen, while Streptococcus pneumoniae (6.96%) was the predominant non-viral pathogen. The overall infection burden was highest in children aged ≤ 1 year (53.75%) and 3 < age ≤ 6 years (54.70%), indicating that early childhood represents a high-risk period for severe respiratory infections requiring intensive care. Pathogen distribution varied significantly across age groups. Distinct seasonal patterns were observed for several respiratory pathogens, particularly among viral pathogens, whereas non-viral pathogens showed more variable seasonal distributions. Furthermore, screening for 10 common pathogens accounted for 75% of PICU respiratory infections, highlighting the clinical utility of multiplex molecular detection. This study delineates the pathogen spectrum of respiratory tract infections in the PICU and characterizes their age- and season-specific epidemiological patterns. This study defines the pathogen spectrum and age- and season-specific patterns of respiratory infections in the PICU, providing evidence to support targeted pathogen surveillance, optimized multiplex diagnostics, and risk-informed infection control strategies in pediatric critical care. Full article

Steep slope failures adjacent to residential areas are becoming an increasingly serious hazard. However, satellite-based monitoring is often limited by revisit time and spatial resolution, which can impede the timely identification of small, precursory deformations. To support dense in situ surveillance, embedded glass fiber-reinforced polymer (GFRP) sensor rods were installed in a susceptible slope, and ground-displacement data were recorded at 5 min intervals for five months. Based on these multivariate time series, we propose PRISM-TAD, a masked Transformer-based anomaly detection approach that integrates kinematic priors computed from displacement and velocity to model normal slope dynamics and detect departures from typical behavior. The proposed method was benchmarked against six baselines: robust velocity threshold screening, PCA-based reconstruction, Isolation Forest, one-class SVM, a 1D convolutional autoencoder, and a standard Transformer reconstructor. In a field test using a documented slope failure case in Seocheon, PRISM-TAD generated an alert approximately 22 h before collapse while yielding the lowest false alarm rate. Although some baseline methods showed longer nominal lead times, they produced substantially more false positives. Overall, the results suggest that coupling high-frequency IoT displacement sensing with domain-informed deep learning can enhance the operational reliability of early warning for slope failures. Full article

Background: Obstructive Sleep Apnea (OSA) is highly prevalent yet underdiagnosed due to the scarcity of Polysomnography (PSG) resources. Audio-based screening offers a scalable solution, but often lacks the granularity to precisely localize respiratory events or accurately estimate the Apnea-Hypopnea Index (AHI). This study aims to develop a fine-grained and lightweight detection framework for OSA screening, enabling precise respiratory event localization and AHI estimation using non-contact audio signals. Methods: A Dual-Stream Convolutional Recurrent Neural Network (CRNN), integrating Log Mel-spectrograms and energy profiles with BiLSTM, was proposed. The model was trained on the PSG-Audio dataset (Sismanoglio Hospital cohort, 286 subjects) and subjected to a comprehensive three-level evaluation: (1) frame-level classification performance; (2) event-level temporal localization precision, quantified by Intersection over Union (IoU) and onset/offset boundary errors; and (3) patient-level clinical utility, assessing AHI correlation, error margins, and screening performance across different severity thresholds. Generalization was rigorously validated on an independent external cohort from Beijing Tongren Hospital (60 subjects), which was specifically curated to ensure a relatively balanced distribution of disease severity. Results: On the internal test set, the model achieved a frame level macro F1 score of 0.64 and demonstrated accurate event localization, with an IoU of 0.82. In the external validation, the audio derived AHI showed a strong correlation with PSG-AHI (r = 0.96, MAE = 6.03 events/h). For screening, the model achieved sensitivities of 98.0%, 89.5%, and 89.3%, and specificities of 88.9%, 90.9%, and 100.0% at AHI thresholds of 5, 15, and 30 events per hour, respectively. Conclusions: The Fine-Grained and Lightweight Dual-Stream CRNN provides a robust, clinically interpretable solution for non-contact OSA screening. The favorable screening performance observed in the external cohort, characterized by high sensitivity for mild cases and high specificity for severe disease, highlights its potential as a reliable tool for accessible home-based screening. Full article

Aboveground storage tanks are used to store various fluids and chemicals for many industrial purposes. According to API standard 653, the structural integrity of these tanks must be regularly assessed. The U.S. EPA requires each operator to have a Spill Prevention, Control and Countermeasure Plan (SPCC) for aboveground storage containers. The accepted practice for inspection of these tanks, particularly the tank bottoms, requires removing the tank from service, emptying the tank, and interior entry for direct inspection of the structure. The required inspection operations are hazardous due to the chemicals themselves as well as the requirement to operate within confined spaces. An inspection from outside the tank would have significant cost and time benefits and would provide a large reduction in the risks faced by inspection personnel. Guided wave (GW) testing is a promising candidate for screening of storage tank walls and bottoms from the tank exterior due to the ability of GWs to propagate over long distances from a fixed probe location. The lowest-order transverse-motion guided wave modes (e.g., torsional vibrations in pipes) are a good choice for long-range inspection because this mode is not dispersive; therefore, the wave packets do not spread out in time. A common weakness of guided wave inspection is the complexity of report generation in the presence of multiple geometry features in the structure, such as welds, welded plate corners, attachments and so on. In some cases, these features cause generation of non-relevant indications caused by mode conversion. Another significant challenge in applying GW testing is development of probes with high-enough signal amplitudes and relatively small footprints to allow them to be mounted on short tank bottom extensions. In this paper, a new generation of magnetostrictive transducers will be presented. The transducers are based on the reversed Wiedemann effect and can generate shear horizontal mode guided waves over a wide frequency range (20–150 kHz) with SNRs in excess of 50 dB. The recently developed SwRI MST 8 × 8 probe contains an array of eight pairs of individual magnetostrictive transducers (MsTs). The data acquisition hardware allows acquisition using Full Matrix Capture (FMC) and analysis software reporting of anomalies based on Total Focusing Method (TFM) image reconstruction. This novel inspection package allows generation of reports that map out corrosion locations and provide estimates of defect widths. Case studies of this technology on actual storage tank walls and bottoms will be presented together with validation of processing methods on mockups with known anomalies and geometry features. Full article

Background: Immunoglobulin A (IgA) vasculitis is the most common vasculitis of childhood. This study aimed to evaluate the demographic characteristics, clinical manifestations, laboratory findings, prognostic features, differential diagnoses, and treatment approaches of children diagnosed with IgA vasculitis in our clinic. Methods: This retrospective study included children diagnosed with IgA vasculitis between February 2020 and November 2025. Demographic, clinical, laboratory, imaging, biopsy, and treatment data were obtained from medical records. Results: Seventy-four patients were included (mean age: 7.7 ± 3.3 years; 60.8% female), with admissions occurring most frequently in autumn and winter. A preceding infection within the last two weeks was present in 78% of patients. Epstein–Barr virus IgM positivity was detected in three patients and Cytomegalovirus IgM positivity in three patients. Joint, gastrointestinal, and renal involvement were observed in 35, 46, and 30 patients, respectively; testicular involvement was detected in two patients and pneumonic infiltration in one patient. Severe gastrointestinal involvement was observed in six patients (melena in four and intussusception in two). Extensive rheumatologic testing revealed no additional pathology, and skin punch biopsy demonstrated findings consistent with IgA vasculitis in all cases. Corticosteroids were required in 44 patients due to gastrointestinal or renal involvement, or persistent disease. Conclusions: Although IgA vasculitis is generally self-limiting, careful clinical monitoring is essential due to the risk of acute gastrointestinal, testicular, and renal complications, and its potential to mimic other causes of acute abdomen before purpura onset. Extensive rheumatologic testing, broad infectious screening and skin biopsy did not provide additional diagnostic or follow-up value beyond clinical assessment. Full article

In recent years, xylazine has emerged as a cutting agent combined with illicit drugs to extend their effects. The present study aimed to discover drug use patterns associated with xylazine-positive and -negative urine toxicology drug screens and to assess whether xylazine can be used as a marker for exposure to designer drugs/new psychoactive substances in our study population. This is a retrospective analysis of urine toxicology results from two different analytical platforms: a targeted, structurally confirmatory, high-performance liquid chromatography–tandem mass spectrometry (LC-MS/MS) assay that quantifies 136 drugs and metabolites including xylazine; and a non-targeted ThermoFisher Orbitrap Tribrid mass spectrometry system (Thermo Scientific^TM, Bremen, Germany) in combination with database searches for the identification of drugs not captured by the targeted assay. All participants were patients receiving care through the Addiction Research and Treatment Services (ARTS), with documented substance misuse, undergoing routine urine drug toxicology testing at the iC42 Clinical Toxicology. Data analysis was performed using Sciex OS version 2.2.0.5738 after extraction using the targeted, structurally confirmatory and quantitative LC-MS/MS platform (SCIEX, Framingham, MA, USA). The drug patterns found in xylazine-positive and -negative urine samples were statistically significantly different (p < 0.001), indicating different consumption patterns associated with xylazine. Moreover, the overall concentrations of drugs (normalized to creatinine) were also statistically significantly different with higher concentrations in the urine samples that tested negative for xylazine. In contrast, samples that were positive for xylazine contained significantly higher concentrations of various designer drugs/new psychoactive substances as detected by the untargeted platform (p < 0.0001). The results indicated that xylazine has become increasingly common in Denver’s drug circulation and that xylazine may be used as a marker to prompt reflex testing with non-targeted high-resolution mass spectrometry assays in combination with database searches to test for the exposure to designer drugs/new psychoactive substances in our patient population. Full article

Background: Endometrial cancer (EC) represents one of the most prevalent gynecological malignancies worldwide, with increasing incidence rates attributed to rising obesity, metabolic syndrome, and demographic aging. Recent evidence suggests that dyslipidemia, including elevated triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and reduced high-density lipoprotein cholesterol (HDL-C), may have a significant role in the pathogenesis of EC through inflammatory, oxidative stress, and hormonal mechanisms. Objective: This meta-analysis aims to systematically evaluate the association between serum lipid biomarkers and endometrial cancer risk by synthesizing quantitative data from observational studies. Methods: We conducted a comprehensive search of five electronic databases (PubMed, Web of Science, Scopus, EMBASE, and Cochrane) to identify studies examining lipid biomarkers in patients with EC compared to healthy controls. After screening 639 articles and applying rigorous inclusion/exclusion criteria, six studies were selected for final analysis. The standardized mean differences (SMD) were calculated with 95% confidence intervals using random-effects and fixed-effects models, considering heterogeneity assessed by the I² statistic. Publication bias was evaluated using funnel plots and Egger’s regression test. Results: The meta-analysis revealed significantly elevated TG levels in EC patients compared to controls (SMD +0.87, 95% CI [+0.65, +1.10]), markedly reduced HDL-C levels (SMD −0.92, 95% CI [−1.15, −0.69]), and increased LDL-C levels (SMD +0.74, 95% CI [+0.50, +0.98]). The heterogeneity was moderate to substantial, with an I² ranging from 49% to 62%. Subgroup analyses demonstrated stronger associations in Type I EC and obese patients (BMI > 30 kg/m²). Conclusions: This meta-analysis establishes a significant association between dyslipidemia and endometrial cancer risk, with elevated triglycerides and LDL-C conferring increased risk while HDL-C appears protective. These findings support the integration of lipid profiling into EC risk assessment protocols and suggest the potential preventive value of lipid-modulating interventions. Further studies are needed to establish causality and evaluate therapeutic applications. Full article

Mass M (kg) and peak intrusion L (mm) are jointly minimized for a CFRP-enabled battery pack enclosure under the GB 38031-2025 −40° side-pole extrusion condition. A 50-run explicit FE design of experiments is conducted and deterministically partitioned into 37/5/5/3 for initial training, two sequential enrichment batches, and an independent hold-out test. Bayesian additive regression trees are trained as the primary surrogates for M, L, and Stress, and stress acceptability is enforced through a probability-of-feasibility (PoF) gate anchored to a baseline-scaled cap, σ_lim = 1.2 σ_base = 410.4 MPa. NSGA-II performed on the feasible surrogate landscape yields a bimodal feasible non-dominated set. The two branches correspond to two discrete levels of a key thickness variable x₄: a low-mass regime (n = 106) with M = 100.61–104.81 kg and L = 5.430–5.516 mm at x₄ ≈ 5.60 mm, and a stiffer regime (n = 94) with M = 110.69–115.08 kg and L = 5.362–5.430 mm at x₄ ≈ 8.00 mm. PoF screening eliminates part of the intermediate region where feasibility confidence is insufficient. Independent FE reruns further indicate that the PoF gate reduces deterministic misclassification near the stress boundary (e.g., one near-threshold candidate exceeds σ_lim, whereas others satisfy the cap with margin). Overall, the proposed workflow offers a traceable lightweighting route under extreme-cold uncertainty within a constrained FE budget. Full article

The western region of the Tarim Basin is a typical deep and ultra-deep oil and gas reservoir with complex geological conditions in China. This area includes a thick salt–gypsum layer, high-pressure brine layers, and other formations with high pressures and a complex pressure system. These geological features present challenges such as a high risk of drilling fluid contamination by formation fluids, the deep burial of subsalt reservoirs, high temperatures, and difficulty in designing drilling fluids. In this paper, by systematically screening and optimizing key additives, a diesel oil-based drilling and completion fluid system resistant to 220 °C ultra-high temperatures with a density of 2.60 g/cm³ was developed. The overall performance was evaluated. Utilizing an independently developed high-temperature emulsifier (BZ-PSE), an organically modified lithium silicate viscosity modifier (BZ-CHT), and compounded fluid loss reducers (BZ-OLG/BZ-OSL), the system maintained excellent rheological stability (yield point > 4.3 Pa) and filtration control capacity (HTHP fluid loss < 4.8 mL) even after aging at 220 °C. The system demonstrated a resistance to contamination by 30–50% composite brines, 15% salt–gypsum cuttings, and 10% cement, proving its capability to effectively handle extremely thick mud shale, salt–gypsum layers, and high-pressure brine. Field tests were conducted in wells GL 3C, DB X, Boz 13X, and Boz 3X. The results indicated that the high-temperature, high-density diesel oil-based drilling fluids and completion fluids can effectively address the technical challenges posed by wellbore instability in thick salt–gypsum layers, high-pressure brine invasion, and performance degradation under ultra-high temperature conditions, providing reliable technical support for the safe and efficient drilling of similar complex formations. Full article

The initiation of debris flows in mountainous areas is dynamically influenced by multiple factors, including rainfall intensity, duration, and antecedent rainfall conditions. Traditional static threshold methods struggle to adapt to these dynamic environmental conditions. To address this issue, this paper proposes a dynamic threshold determination method for the critical rainfall triggering debris flows in mountainous regions. Firstly, high-risk areas are identified based on the frequency ratio model, and the effective rainfall is quantified using the Crozier model. Subsequently, a combination of dynamic variables, such as soil saturation and safety factor, is constructed, and the Jensen–Shannon (JS) divergence is introduced for sensitivity screening to select the most relevant variables. These optimized variables are then fed into an LSTM-TCN (Long Short-Term Memory-Temporal Convolutional Network) framework to extract temporal features and predict the probability of debris flow occurrence time. Finally, real-time threshold determination is achieved by integrating the absolute rainfall energy with a dynamic threshold model. Test results demonstrate that this method can effectively quantify the dynamic nature of rainfall across different regions, screen key variables, and achieve threshold determination with high coverage (average of 0.978) and precise interval width (average of 0.023). This approach provides a more accurate and adaptive means of predicting and managing debris flow risks in mountainous areas, enhancing our ability to respond to these natural hazards in a timely and effective manner. Full article

Shale gas “sweet spot” prediction serves as a pivotal technical link in shale gas exploration and development, directly governing the efficiency of exploration deployment and the economic viability of development projects. To address the research gap in sweet spot prediction for complex synclinal structures, this study establishes an integrated geology–engineering–economics evaluation framework, incorporating artificial intelligence (AI)-assisted parameter optimization and dynamic weight adjustment. This innovative approach overcomes the inherent limitations of single-parameter and static evaluation methods commonly employed in new exploration areas. Focusing on the Upper Ordovician Wufeng Formation to Lower Silurian Longmaxi Formation shale sequences within the Anchang Syncline of northern Guizhou, a comprehensive geological characterization of shale reservoirs was accomplished through the fine processing of 3D seismic data (dominant frequency: 30 Hz; signal-to-noise ratio: 8.5) and statistical analysis of logging data. Prestack elastic parameter inversion technology was utilized to quantitatively predict key geological sweet spot parameters, including the total organic carbon (TOC) content and total gas content, with model validation conducted using core test data. Coupled with prestack and poststack seismic attribute analysis, engineering sweet spot evaluation indicators—encompassing fracture development, in situ stress, the pressure coefficient, and the brittleness index—were established with well-defined quantitative criteria. By integrating multi-source data from geology, geophysics, and engineering dynamics, a three-dimensional evaluation system encompassing “preservation conditions–reservoir quality–engineering feasibility” was constructed, with the random forest algorithm employed for sensitive parameter screening. Research findings indicate that high-quality shale in the study area exhibits a thickness ranging from 17 to 22 m, characterized by a TOC content ≥ 4%, gas content of 4.3–4.8 m³/t, effective porosity of 3.5–5.25%, and brittleness index of 55–75. These properties collectively manifest the “high organic matter enrichment, high gas content, and high brittleness” characteristics. Through multi-parameter weighted comprehensive evaluation using the Analytic Hierarchy Process (AHP), complemented by sensitivity testing, sweet spots were classified into three grades: Class I (63 km²), Class II (31 km²), and Class III (27 km²). An optimized well placement scheme for the southern region was proposed, taking into account long-term production dynamics and economic assessment. This study establishes a multi-parameter, multi-technology integrated sweet spot evaluation system with strong transferability, providing a robust scientific basis for the large-scale exploration and development of shale gas in northern Guizhou and analogous complex structural regions worldwide. Full article

Organoid technology has transformed experimental virology by offering physiologically relevant 3D human models that bridge the gap between conventional 2D cell cultures and complex in vivo systems. Derived from pluripotent or adult stem cells, organoids self-organize into multicellular structures that recapitulate native tissue architecture and function, enabling more accurate modeling of host–virus interactions and disease mechanisms. This review outlines the evolution and application of organoid-based systems across neural, intestinal, hepatic, pulmonary, and renal tissues for studying a broad range of human viruses that remain a public health burden. These models can reproduce viral tropism, immune signaling, and host variability, offering new molecular insights into infection dynamics. Integration with single-cell transcriptomics, CRISPR editing, and antiviral screening has expanded the translational utility of organoids, establishing them as a powerful platform for antiviral discovery, vaccine testing, and precision medicine. Full article

Background: Poultry-associated Enterococcus spp. are widespread commensals but may serve as One Health indicators when virulence-associated determinants and antimicrobial resistance co-occur. We characterized paired phenotypic and genomic profiles to delineate species-stratified virulome and resistome patterns. Methods: Isolates originated from a previously established poultry collection with MIC testing. Genotype–phenotype analyses were restricted to the whole-genome sequenced subset (n = 31). The acquired antimicrobial resistance genes were identified using the Comprehensive Antibiotic Resistance Database (CARD), and virulence-associated determinants were screened using the Virulence Factors Database (VFDB). Results were summarized as isolate-level presence/absence matrices and integrated with MIC-derived susceptible/intermediate/resistant categories. Results: The WGS subset comprised E. faecalis (n = 23) and E. faecium (n = 8) with diverse sequence types. Virulome architecture was strongly species-dependent: E. faecalis carried a broad repertoire of adhesion/biofilm-associated determinants, whereas E. faecium showed a limited set of high-confidence virulence-associated hits. Acquired resistance determinants were common across isolates, and resistome profiles displayed structured co-occurrence. Integrated analyses suggested only a modest overall association between virulence-gene burden and acquired resistome size, largely driven by species-level differences. Genotype–phenotype concordance was class-dependent, with incomplete alignment in several antimicrobial classes, consistent with mechanisms beyond the screened acquired gene set. The acquired resistance determinants detected in the WGS subset predominantly mapped to antimicrobial classes commonly used in food-producing animals (e.g., tetracyclines, macrolides, lincosamides, aminoglycosides, and phenicols), supporting interpretation in the context of production-associated antimicrobial selection rather than implying last-line clinical resistance by default. Conclusions: Poultry-derived enterococci may combine genetic features compatible with persistence/colonization and acquired antimicrobial resistance, with co-occurrence patterns shaped primarily by species/lineage background. These findings support risk-stratified One Health surveillance and targeted functional and mechanism-focused follow-up. This integrated virulome–resistome view highlights species-specific risk signatures in poultry-associated Enterococcus and identifies discordant high-level phenotypes that merit targeted mechanistic follow-up. Full article

This study investigates droplet-induced corrosion, a localized corrosion phenomenon driven by oxygen depletion within electrolyte droplets, distinct from bulk volume corrosion. To evaluate the performance of corrosion inhibitors under droplet conditions, a rapid screening electrochemical test method was employed, using a two-electrode setup to monitor corrosion currents. The study examined systematically different exposure environments including dissolved oxygen, pH, electrolyte molarity, and droplet geometry as key factors influencing atmospheric corrosion. Results show that dissolved oxygen levels significantly affect corrosion mechanisms, while larger droplets amplify the Evans droplet effect. Importantly, effective corrosion inhibitors mitigate this effect by reducing the cathodic reaction rate in droplet conditions. These findings advance the understanding of droplet corrosion mechanisms and provide insights into designing sustainable protection strategies to improve the longevity of steel structures in aggressive environments. Full article