Search Results (182,541)

Metabolic syndrome (MetS) is a multifactorial disorder characterized by central obesity, insulin resistance, dyslipidemia, and hypertension, all of which increase the risk of type 2 diabetes and cardiovascular diseases. This study investigates the potential complementary effects of the standardized green and black ADM ComplexTea Extract (CTE) and the heat-treated postbiotic (BPL1^® HT) on the cardiometabolic alterations associated with MetS in a murine model. C57BL/6J mice were fed a high-fat/high-sucrose (HFHS) diet and treated with CTE, BPL1^® HT, or their combination for 20 weeks. Metabolic, inflammatory, oxidative, vascular parameters, and fecal microbiota composition were assessed. Both CTE and BPL1^® HT individually attenuated weight gain, organ hypertrophy, insulin resistance, and inflammation. However, their combined administration exerted synergistic effects, fully normalizing body weight, adipocyte size, lipid profiles, HOMA-IR index, and insulin sensitivity to levels comparable to lean controls. Co-treatment also restored PI3K/Akt signaling in liver and muscle, reduced hepatic steatosis, and normalized the expression of inflammatory and oxidative stress markers across multiple tissues. Furthermore, vascular function was significantly improved, with enhanced endothelium-dependent relaxation and reduced vasoconstrictor responses, particularly to angiotensin II. CTE, BPL1^®HT, and the blend prevented bacterial richness reduction caused by HFHS; the blend achieved higher bacterial richness than mice in Chow diet. Additionally, the blend prevented the increase in Flintibacter butyricus, which is associated with MetS clinical parameters, and showed a tendency to increase the abundance of Bifidobacterium. These findings suggest that the combination of CTE and BPL1^® HT offers a potential nutritional strategy to counteract the metabolic and cardiovascular complications of MetS through complementary mechanisms involving improved insulin signaling, reduced inflammation and oxidative stress, enhanced vascular function, and modulation of gut microbiota. Full article

Diabetic wounds exhibit impaired immune function, delayed neutrophils recruitment, and heightened infection risk which compromises early infection control and delays healing. We have demonstrated that topical CCL3 treatment restores neutrophil influx, reduces bacterial infection by ~99%, and accelerates wound healing in diabetic mice. As per Food and Drug Administration (FDA) Guidelines for Investigational New Drug (IND), we conducted a 14-day acute toxicity study in diabetic mice following a single topical administration of CCL3 at effective low dose (1 µg) and high dose (10 µg) per wound. Mice were monitored for clinical signs, body weight, and food intake throughout the study period. On day 14, serum biochemistry (ALT, AST, BUN, creatinine, metabolic markers) and histopathology of major organs (liver, kidney, heart, lungs, spleen) were assessed. CCL3-treated diabetic mice exhibited no adverse clinical effects. Hematological and biochemical parameters remained within normal limits, and histopathological analyses revealed no additional organ injury in CCL3-treated groups compared to diabetic control mice. Intriguingly, CCL3-treated mice showed improved ALT levels and reduced hepatic pathology, suggesting hepatoprotective effects and reduced serum IgG, indicating reduced systemic inflammation. Overall, our study demonstrates that diabetic mice tolerate topical CCL3 at doses up to 10 times the effective therapeutic concentration without evidence of systemic organ toxicity. These findings provide strong preclinical support for the translational development of CCL3 as a novel therapy for diabetic wound care. Full article

The review deals with the current knowledge on the global panzootic spread of highly pathogenic avian influenza viruses (HPAIVs), with an emphasis on the H5N1 clade 2.3.4.4b virus. It describes the viral structure, replication, pathotypes and molecular determinants of host range, including sialic-acid receptor usage and key genetic mammalian-adaptation markers (PB2-E627K and PB2-D701N mutations). The host spectrum nowadays extends from wild waterfowl and poultry including seabirds, terrestrial and marine mammals and, based largely on experimental studies or molecular detection, reptiles, amphibians, and fish. Recently, the H5N1 clade 2.3.4.4b virus has shown marked tropism for lactating mammary epithelium in dairy cattle, with virions shed in raw milk. The review reports epidemiology, geographical expansion, clinical presentation, pathogenesis and pathology, diagnosis, immune responses and vaccination approaches across species. It also analyses European Union (EU) and Italian regulatory frameworks, surveillance strategies and biosecurity measures from a One-Health perspective. The review highlights how climate change, wildlife–livestock interfaces, intensive farming and global trade favor viral persistence and genomic reassortment and concludes by stressing strategic actions to limit further host adaptation and panzootic/pandemic risks. Full article

Background: Respiratory Syncytial Virus is a predominant source of morbidity and mortality, particularly among babies, the elderly, and immunocompromised patients. Recent developments in RSV vaccines, approved by the FDA for high-risk groups, have highlighted the necessity for post-marketing surveillance to evaluate their real-world safety and efficacy. Method: This study utilized data from the Vaccine Adverse Event Reporting System (VAERS) covering RSV vaccine administration between 2023 and May 2025. The VAERS database reported data on vaccine types, including Arexvy^®, Abrysvo^®, and mRESVIA^® was analyzed for adverse events and vaccination errors. The demographic information, vaccination trends, and hospitalizations post-vaccination among the vaccinated individuals were accessed. Results: The analysis revealed that the most common adverse events were mild, such as injection site pain, erythema, fatigue, and extremity pain. The data also showed a gradual increase in hospitalization rates from 4.8% in 2023 to 7.5% in 2025. Vaccination errors, including inappropriate administration during pregnancy and excess doses, were also observed. A notable trend was the growing proportion of patients who experienced no adverse events, with the highest rate of symptom-free reports seen in 2025 (25.9%). Conclusions: RSV vaccines demonstrate a generally acceptable safety profile based on post-marketing surveillance data. However, the observed increase in hospitalization rates, vaccination errors, and pregnancy-related outcomes warrants continued active surveillance and cautious interpretation. Full article

Additive manufacturing (AM) has emerged as a pivotal technology in component fabrication, renowned for its capabilities in freeform fabrication, material efficiency, and integrated design-to-manufacturing processes. As a critical branch of AM, metal additive manufacturing (MAM) has garnered significant attention for producing metal parts. However, process anomalies during MAM can pose safety risks, while internal defects in as-built parts detrimentally affect their service performance. These concerns underscore the necessity for robust in-process monitoring of both the MAM process and the quality of the resulting components. This review first delineates common MAM techniques and popular in-process monitoring methods. It then elaborates on the fundamental principles of acoustic emission (AE), including the configuration of AE systems and methods for extracting characteristic AE parameters. The core of the review synthesizes applications of AE technology in MAM, categorizing them into three key aspects: (1) hardware setup, which involves a comparative analysis of sensor selection, mounting strategies, and noise suppression techniques; (2) parametric characterization, which establishes correlations between AE features and process dynamics (e.g., process parameter deviations, spattering, melting/pool stability) as well as defect formation (e.g., porosity and cracking); and (3) intelligent monitoring, which focuses on the development of classification models and the integration of feedback control systems. By providing a systematic overview, this review aims to highlight the potential of AE as a powerful tool for real-time quality assurance in MAM. Full article

Background: Osteoporosis and osteopenia are prevalent bone diseases characterized by reduced bone mineral density (BMD) and an increased risk of fractures, particularly in postmenopausal women. While dual-energy X-ray absorptiometry (DXA) remains the gold standard for diagnosis, it has limitations regarding accessibility, cost, and predictive capacity for fracture risk. Machine learning (ML) approaches offer an opportunity to develop automated and more accurate diagnostic models by incorporating both BMD values and clinical variables. Method: This study retrospectively analyzed BMD data from 142 postmenopausal women, classified into 3 diagnostic groups: normal, osteopenia, and osteoporosis. Various supervised ML algorithms—including Support Vector Machines (SVM), k-Nearest Neighbors (k-NN), Decision Trees (DT), Naive Bayes (NB), Linear Discriminant Analysis (LDA), and Artificial Neural Networks (ANN)—were applied. Feature selection techniques such as ANOVA, CHI2, MRMR, and Kruskal–Wallis were used to enhance model performance, reduce dimensionality, and improve interpretability. Model performance was evaluated using 10-fold cross-validation based on accuracy, true positive rate (TPR), false negative rate (FNR), and AUC values. Results: Among all models and feature selection combinations, SVM with ANOVA-selected features achieved the highest classification accuracy (94.30%) and 100% TPR for the normal class. Feature sets based on traditional diagnostic regions (L1–L4, femoral neck, total femur) also showed high accuracy (up to 90.70%) but were generally outperformed by statistically selected features. CHI2 and MRMR methods also yielded robust results, particularly when paired with SVM and k-NN classifiers. The results highlight the effectiveness of combining statistical feature selection with ML to enhance diagnostic precision for osteoporosis and osteopenia. Conclusions: Machine learning algorithms, when integrated with data-driven feature selection strategies, provide a promising framework for automated classification of osteoporosis and osteopenia based on BMD data. ANOVA emerged as the most effective feature selection method, yielding superior accuracy across all classifiers. These findings support the integration of ML-based decision support tools into clinical workflows to facilitate early diagnosis and personalized treatment planning. Future studies should explore more diverse and larger datasets, incorporating genetic, lifestyle, and hormonal factors for further model enhancement. Full article

Background/Objectives: Ocular graft-versus-host disease (oGVHD) is a chronic, immune-mediated complication of allogeneic hematopoietic stem cell transplantation that can progress to corneal ulceration or perforation. These cases are often refractory to standard therapy and present a high risk of graft failure after keratoplasty. We report a case of oGVHD-related corneal perforation successfully managed with a novel amniotic membrane-assisted “envelope” technique during corneal transplantation. Case Report: A 42-year-old man with chronic oGVHD and a full-thickness corneal perforation underwent urgent repair with a lamellar patch graft completely wrapped in cryopreserved amniotic membrane, followed by penetrating keratoplasty (PKP) using an amniotic membrane envelope surrounding the donor lenticule. Results: The amniotic membrane provided a 360° biological barrier that isolated graft antigens from the inflammatory environment while supporting epithelial healing and stromal remodeling. Despite recurrent inflammatory episodes and multiple procedures—including cataract extraction, pars plana vitrectomy, and multilayer amniotic membrane transplantation—the graft remained clear and stable at 12-month follow-up, achieving a best-corrected visual acuity of 20/40. Conclusions: The amniotic membrane envelope technique may represent a valuable adjunct in managing high-risk corneal perforations secondary to oGVHD. By combining immune modulation and regenerative support, this approach can enhance tectonic stability, reduce rejection risk, and promote durable surface recovery, potentially delaying or avoiding keratoprosthesis in refractory cases. Full article

Fetal growth restriction (FGR) remains a significant problem in obstetrics and is a key risk factor for perinatal brain injury. The fetal neuronal vesicles (FNVs) isolated from maternal blood represent an innovative approach—a “fetal brain liquid biopsy”—enabling early diagnostics of neuronal dysfunction in FGR. Western blotting was used to evaluate the protein pattern expression of FNVs isolated from the blood of pregnant women with FGR and uncomplicated pregnancy. Significant changes in the neurotrophic proteins levels (pro-BDNF, pro-NGF) and presynaptic neurotransmission proteins (SYN1, SYP, SYNPO) were identified. New data were obtained on changes in the expression of proteins of sumoylation (SUMO2/3/4) and neddylation (NAE1, UBC12), which differs in early-onset and late-onset FGR. Moreover, increased SUMO2/3/4 levels can be considered as an endogenous neuroprotective response to cerebral hemodynamic reaction in fetuses with late-onset growth restriction. An association has been established between changes in the expression of the studied proteins and intraventricular hemorrhage (IVH) in newborns with late-onset growth restriction. Full article

Oral squamous cell carcinoma (OSCC) is one of the most prevalent types of cancer in the oral cavity and head and neck region. Due to its location and psychological and social implications, early detection and treatment are very important. A liquid biopsy can be used to diagnose cancer by analyzing samples of bodily fluids, such as saliva, blood, or urine, for specific molecules released by tumor cells. The objective of this study was to evaluate the use of liquid biopsy in the diagnosis of oral squamous cell carcinoma. A systematic review was carried out, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (PROSPERO: CRD420251238037). Articles taken into consideration for the review were published before 30 September 2025. The search for manuscripts for the review was conducted using PubMed, Scopus, Google Scholar, and Cochrane databases. Forty-three articles were deemed eligible for inclusion in the systematic review. Key data extracted from the studies included authorship, publication date, study location, methodology, number of participants, and reported complications. Most of the analyzed biomarkers showed promising potential for future use in liquid biopsy for OSCC diagnosis. Tumor DNA and miRNA demonstrated the highest diagnostic accuracy. The standard approach to diagnosis and planning treatment relies on tumor biopsy and diagnostic imaging. Liquid biopsy may complement this process by enabling early detection in high-risk populations and monitoring response to therapy. As such, it serves as a prognostic factor or therapeutic target, successfully identifying disease recurrence. Full article

Rainfall infiltration is one of the main factors inducing slope instability, while the spatial heterogeneity and uncertainty of soil parameters have profound impacts on slope response characteristics and stability evolution. Traditional deterministic analysis methods struggle to reveal the dynamic risk evolution process of the system under heavy rainfall. Therefore, this paper proposes an uncertainty analysis framework combining Karhunen–Loève Expansion (KLE) random field theory, Polynomial Chaos Kriging (PCK) surrogate modeling, and Monte Carlo simulation to efficiently quantify the probabilistic characteristics and spatial risks of rainfall-induced slope instability. First, for key strength parameters such as cohesion and internal friction angle, a two-dimensional random field with spatial correlation is constructed to realistically depict the regional variability of soil mechanical properties. Second, a PCK surrogate model optimized by the LARS algorithm is developed to achieve high-precision replacement of finite element calculation results. Then, large-scale Monte Carlo simulations are conducted based on the surrogate model to obtain the probability distribution characteristics of slope safety factors and potential instability areas at different times. The research results show that the slope enters the most unstable stage during the middle of rainfall (36–54 h), with severe system response fluctuations and highly concentrated instability risks. Deterministic analysis generally overestimates slope safety and ignores extreme responses in tail samples. The proposed method can effectively identify the multi-source uncertainty effects of slope systems, providing theoretical support and technical pathways for risk early warning, zoning design, and protection optimization of slope engineering during rainfall periods. Full article

With the rapid growth of the low-altitude economy, ensuring safe unmanned aerial vehicle (UAV) operations over large public events has become a critical issue for urban air mobility. This study proposes a dynamic risk identification and mitigation framework that integrates UAV inherent risk, aerial traffic density, and ground crowd density into a risk evaluation model. To address the absence of real urban air-route data, a simulated low-altitude network was constructed using ArcGIS, K-means clustering, and Delaunay triangulation, while flight paths were optimized through the ripple-spreading algorithm. Based on this model, a risk-aware control mechanism combining rerouting and hovering strategies was implemented to adaptively respond to varying ground risk levels. A total of 412 UAV missions were simulated over a 6.5 h city marathon scenario, followed by an extended evaluation with 1873 missions to assess scalability. The results show that over 20% of UAVs required detouring or hovering under dynamic risk conditions, leading to a 35–50% reduction in high-risk exposure time while maintaining acceptable operational efficiency. The proposed framework demonstrates good adaptability and scalability for risk-aware UAV operations in complex urban environments. Full article

Background: Metabolically associated fatty liver disease (MASLD) constitutes a major burden. Glucagon-like peptide-1 agonists (GLP-1) could improve hepatic steatosis as well as weight loss. However, the effect of GLP-1 agonists on patients with and without diabetes and the effect of newer drugs (dual and triple agonists) are unclear. Objective: To investigate the effect of GLP-1 agonists, including dual and triple agonists, in patients with metabolic-associated liver steatosis and steatohepatitis, while exploring their effect on patients with and without type 2 diabetes. Methods: We searched PubMed, Scopus, and Web of Science in October 2025 for randomized parallel controlled trials that investigated the effect of GLP-1 agonists in patients with MASLD or metabolic-associated steatohepatitis (MASH). We assessed the quality of the included studies using Cochrane ROB2. We performed the analysis using RevMan 5.4. We performed subgroup analysis based on the status of diabetes, the control group, and the class of GLP-1 agonist (single, dual, or triple). Results: We included twenty studies. Compared to the control group, GLP-1 agonists were associated with a statistically significant increase in the resolution of MASH without worsening fibrosis (RR 3.03, p < 0.0001) and at least one stage of liver fibrosis without the worsening of MASH compared to the control group (RR: 1.45, p < 0.00001). GLP-1 agonists were associated with a statistically significant weight reduction (SMD −1.11, p < 0.0001), glycosylated hemoglobin (SMD −0.81, p < 0.00001), levels of aspartate aminotransferase (SMD −0.48, p = 0.008), and alanine aminotransferase (SMD −0.54, p = 0.008). However, in patients without type 2 diabetes, GLP-1 agonists had no significant effect on weight loss (SMD −0.97, p = 0.12) or improvement in fibrosis (RR 1.54, p = 0.24). There was a statistically significant increase in the overall adverse events (RR 1.10, p < 0.00001), while there was no significant difference in serious adverse events (p = 0.35). Conclusions: GLP-1 agonists improved liver fibrosis, steatohepatitis, weight loss, HbA1c, and liver enzymes in patients with MASLD or MASH. Overall, GLP-1 agonists were associated with a significantly higher risk of adverse events compared to the control, while serious adverse events were comparable between both groups. There was no significant effect on weight loss or improvement in fibrosis in patients without type 2 diabetes. However, there was a limited number of studies in this population. Thus, further research is needed before recommendations can be made for this subgroup. Full article

The unique natural environment and climate of tropical island regions present significant challenges to construction. Under these variable natural conditions and complex construction processes, identifying and analyzing potential risks that could lead to vulnerabilities in construction safety systems and clarifying their transmission pathways remains a pressing issue. To fill this research gap, a GV-IB model for vulnerability analysis of construction safety systems in tropical island building projects (CSSTIBPs) was established. This model constructs a vulnerability analysis index system for tropical island construction safety systems based on the Grey Relational Analysis (GRA) and Vulnerability Scoping Diagram (VSD), considering exposure, sensitivity, and adaptability. By combining the artificial fish swarm algorithm with the K2 algorithm and the EM algorithm, an Improved Bayesian Network (IBN) is constructed to analyze and infer the influencing factors and disaster chains of vulnerability in tropical island construction safety systems. The IBN can effectively overcome the dependence on node order and data gaps in traditional Bayesian Network construction methods. The effectiveness of the model is verified by analyzing Hainan Island, China. The research results show that (a) The IBN stability verification showed an Area Under ROC Curve (AUC) of 0.783 > 0.7, indicating high effectiveness in identifying vulnerability factors. (b) Within the vulnerability measurement nodes of the CSSTIBPs, the influence on the system decreases in the following order is exposure (0.41), sensitivity (0.31), and adaptability (0.03). (c) Emergency response time, safety training, hazard identification time, accident response time, and duration of severe weather are key factors affecting the vulnerability of CSSTIBPs. Full article

Silicosis is an irreversible and progressive pulmonary fibrotic disease caused by the long-term inhalation of silica dust. The precise molecular mechanisms underlying the disease remain incompletely understood, and effective early diagnostic biomarkers are still lacking. In this study, we used a silicosis mouse model and transcriptomic sequencing to identify 2950 mRNAs, 461 lncRNAs, 81 miRNAs, and 44 circRNAs that were differentially expressed in lung tissue. Enrichment analysis revealed that these differentially expressed genes were significantly enriched in the phosphatidylinositol 3-kinase (PI3K)–protein kinase B (Akt) signaling pathway, nuclear factor kappa-light-chain-enhancer of activated B cell (NF-κB) signaling pathway, and tumor necrosis factor (TNF) signaling pathway. The constructed competing endogenous RNA (ceRNA) network highlighted extensive regulatory interactions among lncRNAs/circRNAs, miRNAs, and mRNAs. Human validation showed that the expression levels of hsa-miR-215-5p and hsa-miR-146b-5p were significantly upregulated in the peripheral blood of early-stage pneumoconiosis patients, while hsa-miR-485-5p was downregulated. Logistic regression analysis revealed that hsa-miR-215-5p (OR = 1.966, 95% CI: 1.6938–2.2796, p < 0.001) and hsa-miR-146b-5p (OR = 1.9367, 95% CI: 1.697–2.201, p < 0.001) were independent risk factors for pneumoconiosis (p < 0.001). ROC curve analysis showed that both miRNAs demonstrated good diagnostic efficacy for pneumoconiosis, with AUC values of 0.9563 and 0.8876, respectively. These results provide novel insights into the complex ceRNA regulatory network involved in silicosis pathogenesis and suggest potential early, non-invasive diagnostic biomarkers. Full article

Monitoring construction-phase settlement of estuary-crossing tunnels founded on coastal soft soils is critical for risk management, yet dense in situ measurements are often unavailable along linear corridors. This study uses Sentinel-1A ascending SAR imagery (65 scenes, September 2022–August 2025) to retrieve time-series deformation along the Sanya Estuary Channel tunnel (China) using Permanent Scatterer InSAR (PS-InSAR) and Small Baseline Subset InSAR (SBAS-InSAR). The two approaches reveal a consistent subsidence hotspot at Tunnel Section D (DK0+000–DK0+330), while most of the corridor remains within ±5 mm/a. The line-of-sight deformation rates range from −24 to 17.7 mm/year (PS-InSAR) and −29.9 to 18.7 mm/a (SBAS-InSAR). Time-series analysis at representative points in Section D indicates a maximum cumulative settlement of −75.7 mm and a clear acceleration after May 2023. By integrating the deformation results with geological reports, construction logs and rainfall records, we infer that compressible marine clays and interbedded sand/aquifer zones control the hotspot, whereas excavation/dewatering and rainfall-related groundwater fluctuations further promote consolidation. The results provide a practical basis for subsidence risk screening and monitoring prioritization for estuary-crossing infrastructure in coastal soft-soil settings. From a sustainability perspective, the proposed joint PS–SBAS InSAR framework provides a scalable and cost-effective tool for continuous deformation surveillance, supporting preventive maintenance and risk-informed management of urban underground infrastructure. Full article