Search Results (14,218)

Background: Chronic kidney disease (CKD) is characterised by a disrupted gut–kidney axis, wherein intestinal dysbiosis is associated with the accumulation of uraemic toxins and the potential depletion of beneficial short-chain fatty acids (SCFAs). Whilst acetate, propionate, and butyrate are known to modulate systemic inflammation and blood pressure, their precise circulating concentrations across different CKD stages and age groups remain poorly defined. This systematic review and meta-analysis aimed to quantify blood SCFA concentrations in CKD patients compared to healthy controls. Methods: We conducted a systematic search of Medline, EMBASE, and the Cochrane Library for clinical studies reporting blood SCFA concentrations in humans with CKD. Methodological quality was assessed using the NIH tool. Standardised mean differences (SMDs) were calculated for the quantitative meta-analysis, with subgroup analyses performed for age, CKD stage, and treatment modality (dialysis vs. transplantation). Results: Twenty-one studies encompassing 9661 participants were included. Quantitative synthesis revealed a significant and consistent systemic depletion of circulating acetate and propionate in adult CKD patients compared to healthy controls (p < 0.05). This depletion followed a stage-dependent trajectory, worsening alongside declining glomerular filtration rates. Notably, a “butyrate paradox” was identified in paediatric cohorts; whilst adults showed progressive butyrate depletion, children with CKD often maintained or exhibited elevated levels, particularly in the context of hypertension. Furthermore, whilst haemodialysis patients exhibited the most profound SCFA deficiencies, kidney transplantation appeared to partially restore these metabolites toward healthy baseline levels. Conclusions: CKD is associated with a profound systemic reduction in acetate and propionate, supporting the model of a compromised gut–kidney axis based on converging evidence. The divergent results for butyrate in paediatric versus adult populations suggest that SCFA metabolism is influenced by age-related factors or compensatory mechanisms. These findings highlight the potential for SCFA monitoring as a candidate or emerging markers for detecting early renal damage and stratifying risk. Full article

Background: Supplementation with long-chain omega-3 polyunsaturated fatty acids (LC n-3 PUFAs), particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), may mitigate exercise-induced muscle damage (EIMD) and enhance post-exercise recovery. However, the systematic reviews/meta-analyses evaluating these effects across populations and exercise models are limited and do not provide dosing recommendations. Objective: This systematic review and meta-analysis aimed to evaluate the effects of LC n-3 PUFA supplementation on key post-exercise recovery outcomes, including muscle soreness, muscle function, and muscle damage biomarkers in healthy adults. Methods: Following the PRISMA guidelines, a comprehensive search of PubMed, Scopus, and clinical trial registry databases was conducted (to January 2025). All studies that met the inclusion criteria underwent appropriate methodological quality assessments using established tools. The data were extracted for inputting into random-effects models, with effect sizes reported as Hedges’ g and 95% confidence intervals (CIs). Heterogeneity was assessed using the I² statistic. Results: Among the 2539 records, 43 studies met the inclusion criteria for the systematic review, and nine met the inclusion criteria for the meta-analysis. The effect of LC n-3 PUFA supplementation on recovery outcomes was equivocal, with significant methodological limitations noted across the literature. However, the meta-analysis of nine placebo-controlled, eccentric exercise trials demonstrated that LC n-3 PUFA supplementation significantly reduced delayed onset muscle soreness (DOMS) (Hedges’ g = −0.75; 95% CI: −1.14 to −0.36), creatine kinase (CK) (Hedges’ g = −0.40; 95% CI: −0.70 to −0.10), and muscle swelling (Hedges’ g = −0.45; 95% CI: −0.83 to −0.07), and significantly improved muscle strength (Hedges’ g = 0.45; 95% CI: 0.07 to 0.83) and range of motion (ROM) (Hedges’ g = 0.93; 95% CI: 0.33 to 1.53) at peak impairment compared with placebo. Conclusions: LC n-3 PUFA supplementation may support recovery from EIMD. However, due to the methodological limitations across the literature base it was not possible to assess effective dosing strategies. Future studies should address dose–response and duration requirements and incorporate objective assessments of omega-3 status (e.g., the Omega-3 Index [O3I] or comparable biomarkers) alongside standardized compliance measures. These approaches are necessary to determine effective dosing strategies and to test the relationship between omega-3 status and recovery outcomes. Full article

Background: Chronic stress is a major risk factor for cognitive decline and blood–brain barrier (BBB) disruption, yet the underlying molecular mechanisms remain elusive. This study aimed to investigate the specific role of the metabolic intermediate homocysteine (Hcy) in chronic stress-induced BBB dysfunction and cognitive impairment. Methods: We utilized a male Sprague-Dawley rat model of chronic unpredictable mild stress (CUMS) and administered vitamin B complex to lower Hcy levels in vivo. Regional Hcy accumulation, BBB permeability, and cognitive behaviors were assessed. In vitro, primary rat brain microvascular endothelial cells (BMECs) were exposed to Hcy to evaluate barrier-forming function, transcriptomic alterations, DNA methylation patterns, Cav1.2 expression, and reactive oxygen species (ROS) production. Results: CUMS selectively induced BBB hyperpermeability and significant Hcy accumulation predominantly within the rat hippocampus, which correlated intimately with cognitive deficits. Lowering Hcy levels via vitamin B supplementation successfully restored hippocampal BBB integrity and alleviated cognitive impairment. In addition, elevated Hcy severely impaired the barrier function of BMECs. Mechanistically, Hcy reduced global DNA methylation in BMECs and specifically induced targeted DNA hypomethylation at the intro region of Cacna1c. This epigenetic shift caused the transcriptional derepression and overexpression of the Cav1.2 calcium channel. Upregulated Cav1.2 subsequently triggered a robust ROS burst, leading to tight junction degradation. Conclusions: Our findings unveil a novel metabolic–epigenetic axis where Hcy-driven Cacna1c hypomethylation directly disrupts BMECs function to dismantle the hippocampal BBB. Lowering Hcy or targeting this Hcy-Cav1.2 pathway establishes a promising therapeutic strategy for mitigating stress-related neurovascular damage and cognitive disorders. Full article

Freezing rain is a high-impact winter weather phenomenon that acts as a major disturbance agent in forest ecosystems, causing canopy damage, stem breakage, tree mortality, and long-term changes in forest structure and functioning. Although ice storms have been studied for decades, research on freezing rain impacts on forests remains fragmented across multiple disciplines, and few studies have attempted an integrated synthesis that simultaneously combines climatological, ecological, and methodological perspectives. In this study, we present a systematic and integrative review of the scientific literature on freezing rain and forests, combining a large-scale bibliometric analysis with an in-depth qualitative synthesis. A total of 241 publications retrieved from the Scopus and Web of Science databases were analyzed following PRISMA guidelines. The bibliometric assessment examined publication trends, geographic distribution, institutional contributions, research domains, and keyword networks. The qualitative review synthesized current knowledge on freezing rain climatology, forest damage mechanisms, species-specific vulnerability, major ice storm events, detection and modeling approaches, and ecological consequences. Results reveal a strong increase in scientific output over the last two decades, dominated by research from North America and northern Europe. Ice accretion intensity emerges as the primary driver of forest damage, while species traits, crown architecture, tree size, stand structure, topography, and exposure strongly modulate damage severity. Freezing rain affects a wide range of forest types worldwide and triggers both immediate structural damage and long-term ecological effects, including altered successional dynamics and reduced forest productivity. Recent methodological advances—including passive remote sensing (e.g., optical satellite data), active remote sensing (e.g., LiDAR), experimental ice storm simulations, reanalysis datasets, and machine learning approaches—have significantly improved detection, monitoring, and forecasting capabilities. Despite these advances, major research gaps remain, particularly regarding long-term ecosystem recovery, trait-based vulnerability, socio-economic impacts, and future freezing rain regimes under climate change. This review highlights freezing rain as an increasingly important but underappreciated forest disturbance and underscores the need for interdisciplinary research and adaptive management strategies in ice-prone regions. Full article

The rapid and accurate assessment of residual ultimate strength after ship damage is crucial for rescue decision-making and navigation safety, while traditional methods struggle to meet the demands of complex random damage scenarios in terms of efficiency or accuracy. This study proposes a hybrid framework that integrates high-fidelity nonlinear finite element simulation (NFEM) and a Bayesian-regularized backpropagation neural network (BPNN). NFEM is used to accurately simulate a large number of random damage scenarios, generating a physically credible benchmark dataset. BPNN serves as an efficient surrogate prediction model, with its key parameters—the number of hidden layers and the training algorithm—systematically optimized to enhance generalization capability. The results show that: (1) The NFEM simulation results deviate by less than 5% compared to the Smith method, validating the reliability of the dataset. (2) The prediction performance of BPNN is highly dependent on the number of hidden layers and the training algorithm, exhibiting non-monotonic variation, with an optimal parameter combination identified as 8 hidden layers paired with the Bayesian algorithm, achieving a prediction regression value R of 0.91662. (3) Deep networks are prone to overfitting, while shallow networks suffer from insufficient feature capture. (4) The Bayesian algorithm performs best in terms of overfitting resistance and stability. This study not only provides a high-precision and efficient intelligent solution for residual strength assessment of damaged hulls, but its systematic neural network parameter optimization strategy, particularly the approach of identifying optimal depth and selecting anti-overfitting algorithms, also offers an important reference for the design of intelligent damage assessment models for similar engineering structures. Full article

Freak waves can cause damage or capsize marine structures. The efficient fixed-point generation of target wave trains containing freak waves in laboratories or numerical wave tanks is a crucial method for marine structure design and disaster inversion assessment. This study proposes a local coefficient assignment method. After no more than three iterations of local wave train processing, the method achieves accurate generation of measured freak wave trains at different positions. Among the results, the maximum crest error for the “New Year Wave” is less than 3%, and the simulation achieves excellent agreement in significant wave height, period, and overall wave surface elevation with the target wave surface. The assignment coefficient curve of the typical freak wave event “New Year Wave” within the farthest fixed-point generation range of the numerical simulation in this paper is provided, enabling high-precision one-time generation of the “New Year Wave” at any desired position. The resulting maximum wave height error is less than 5%, satisfying the application requirements of deep-water waves under different water depth conditions. Furthermore, based on the simulation results, wavelet transform analysis is performed on the wave train data to investigate the evolution characteristics of wave energy before, during, and after the occurrence of the freak wave. The findings of this study have strong practical engineering significance for research on the propagation and evolution characteristics of highly nonlinear waves, as well as for the design and analysis of wave loads on marine structures. Full article

Removing altered varnishes and retouching from oil paintings is a delicate and irreversible procedure in the conservation of cultural heritage. Surfactant-free gelled o/w emulsions containing dibasic esters (DBE) provide a green, safe, and environmentally friendly alternative to traditional solvent methods. The use of Xanthan gum and polyacrylate as thickening agents successfully restricted solvent diffusion, thereby minimizing the risk of interaction with water-sensitive substrates. Spectroscopic and microscopic analyses (FTIR and SEM) were employed to evaluate the cleaning efficacy and to assess the morphological integrity of the paint surface post-treatment, detecting potential inhomogeneities, erosion, or pigment loss. Determination of surface conductivity has allowed us to verify the degree of removal of any residues that could have undesirable long-term effects. Fatty acid leaching was quantified by gas chromatography-mass spectrometry (GC/MS): the use of free DBE resulted in a loss of up to 60% of the lipid component, while for surfactant-free gelled o/w emulsions with DBE, this figure was significantly reduced, with no observable surface damage. The tests were performed at both neutral pH and pH 8.5. The pH change was consistent with expected values: alkaline and ionizing conditions enhanced the emulsifying and removal effect, as well as the interaction with the painting medium. These results suggest that surfactant-free gelled o/w emulsions represent a promising alternative to conventional solvent-based systems, offering effective varnish removal while minimizing risks to both artifacts and restorers. Full article

Cadmium (Cd) is a typical heavy metal pollutant in aquatic environments. It enters fish through the gills, digestive tract, and body surface, and accumulates mainly in the liver and kidneys, with species- and tissue-specific distribution. Cadmium triggers apoptosis by inducing oxidative stress, calcium imbalance, and DNA damage. These signals are integrated and amplified by the mitogen-activated protein kinase (MAPK), nuclear factor kappa B (NF-κB), phosphatidylinositol 3-kinase (PI3K)/AKT, and nuclear factor erythroid 2-related factor 2 (Nrf2) pathways, ultimately activating three downstream apoptotic execution pathways: the death receptor, mitochondrial, and endoplasmic reticulum stress pathways. These three pathways form an interactive network through molecular nodes such as BH3 interacting domain death agonist (Bid), Ca²⁺, c-Jun N-terminal kinase (JNK), and C/EBP homologous protein (CHOP), synergistically amplifying the apoptotic effect, with the mitochondrial pathway playing a central role. Cadmium-induced apoptosis is dose-dependent: low concentrations activate protective responses, whereas high concentrations strongly promote apoptosis. Current research gaps remain regarding dynamic pathway crosstalk, chronic low-dose effects, species differences, and fish-specific apoptotic molecules (e.g., caspase-12 homologs). Future studies should focus on constructing multidimensional response maps, clarifying pathway activation thresholds and interaction contributions, and developing composite protective strategies based on Nrf2 activators, metal chelators, and antioxidants, thereby promoting translation into ecological risk assessment and aquaculture pollution control. Full article

Plastic products are extensively utilized in various industrial goods and consumer items. However, when these plastics fail to undergo complete degradation, they generate nanoplastic particles (NPs). As emerging environmental pollutants, such nanoplastics are highly likely to have widespread and adverse impacts on human health. Accumulating evidence indicates that NPs can penetrate biological barriers and exert toxic effects on multiple organs, including the nervous system. Although extensive studies have investigated the toxicity of NPs, the mechanisms underlying their long-term neurotoxic effects remain poorly understood. Here, we summarize the current understanding on the exposure pathways of NPs, their neurotoxic effects, and the molecular mechanisms involved in neurotoxicity. Emerging evidence suggests that NPs induce neurological damage through various mechanisms, including oxidative stress, neuroinflammation, ferroptosis, autophagy dysregulation, and gut–brain axis imbalance. A comprehensive understanding of these mechanisms will provide new insights into the potential impacts of environmental NPs exposure on the nervous system and contribute to more accurate health risk assessments. Full article

Purpose: Inflammatory bowel disease (IBD) is a chronic inflammatory disorder strongly associated with intestinal microbial dysregulation. Although 5-aminosalicylic acid (5-ASA) is widely used in the clinical management of IBD, its therapeutic efficacy is often limited. To address this, the present study aimed to develop a bifidobacterium-derived extracellular vesicle-based drug delivery system (B-MVs@5-ASA) to enhance the therapeutic outcomes of IBD. Methods: B-MVs were isolated by PEG precipitation and loaded with 5-ASA via sonication to obtain B-MVs@5-ASA. Their morphology, particle size, zeta potential, and encapsulation efficiency were analyzed using TEM, DLS, and UV spectrophotometry. Cellular uptake, cytotoxicity (LDH and NO assays), and anti-inflammatory effects were assessed in RAW 264.7 and Caco-2 cells. A DSS-induced colitis mouse model was established to evaluate therapeutic efficacy. Cytokines (ELISA), colon histopathology (H&E), tight-junction proteins (IF), and gut microbiota composition (16S rRNA sequencing) were systematically analyzed. Results: B-MVs@5-ASA exhibited a particle size of 104.3 ± 2.81 nm and an encapsulation efficiency of 11.14% ± 3.63%. B-MVs@5-ASA exhibited the strongest anti-inflammatory effect in vitro and most effectively alleviated DSS-induced colitis in vivo, outperforming monotherapies in reducing inflammation, tissue damage, and enhancing barrier integrity. B-MVs@5-ASA further promoted goblet cell regeneration and beneficially modulated the gut microbiota by enriching Akkermansia and suppressing Escherichia, thereby restoring microbial homeostasis. Conclusions: B-MVs@5-ASA provides potent anti-inflammatory and mucosal-protective effects by modulating cytokine balance, enhancing epithelial barrier function, and reshaping gut microbiota. These findings highlight probiotic vesicle-based nanoplatforms as a safe and promising strategy for targeted IBD therapy. Full article

Advanced glycation end products (AGEs) accumulate under chronic inflammation and metabolic stress and may contribute to long-term tissue damage. Skin autofluorescence (SAF) enables non-invasive assessment of tissue AGE accumulation, but data in inflammatory rheumatic diseases remain limited. The present study evaluated AGE-SAF levels in patients with seropositive rheumatoid arthritis (RA) and ankylosing spondylitis (AS) and investigated their associations with disease activity, inflammatory markers, metabolic parameters, and comorbidities. Patients with RA and AS, along with healthy controls, were included. AGE-SAF was measured non-invasively. Disease activity was assessed using the Disease Activity Score in 28 joints (DAS28) and the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). Between-group comparisons were performed both crudely and after multivariable adjustment for age, sex, and body mass index (BMI). Logistic regression and receiver operating characteristic (ROC) analyses were used to describe the exploratory discriminative performance of AGE-SAF, and propensity score analyses were conducted as sensitivity analyses to address baseline imbalance. In crude comparisons, AGE-SAF levels were higher in RA than in AS and controls, and higher in AS than in controls (p < 0.001). After adjustment for age, sex, and BMI, AGE-SAF remained significantly elevated in both RA (β = 0.440, 95% CI 0.298–0.583, p < 0.001) and AS (β = 0.304, 95% CI 0.183–0.425, p < 0.001) compared with controls; however, the difference between RA and AS was no longer statistically significant (β = 0.136, 95% CI −0.051 to 0.323, p = 0.154). Exploratory ROC analyses showed good discrimination for RA versus controls (AUC = 0.851) and moderate discrimination for AS versus controls (AUC = 0.695), whereas discrimination between RA and AS was limited (AUC = 0.670). In overlap-weighted sensitivity analysis, the RA-AS difference remained non-significant (β = 0.161, p = 0.293). AGE-SAF is elevated in inflammatory rheumatic diseases compared with healthy controls, and this elevation persists after adjustment for age, sex, and BMI. Although crude AGE-SAF values were higher in RA than in AS, this difference attenuated after confounder adjustment, indicating that a substantial part of the between-disease difference is attributable to demographic and treatment-related imbalance. AGE-SAF may therefore reflect cumulative disease-related and vascular–metabolic burden across both diseases rather than a disease-specific phenomenon. Full article

Parkinson’s disease (PD) and acute kidney injury (AKI) are two conditions with increasing prevalence and severe systemic complications and consequences. This research examines the combined neuroprotective and nephroprotective properties of three medicinal plants, Mucuna pruriens (Muc), Moringa oleifera (Mor), and Silybum marianum (SM), in a murine model of PD, AKI, and their comorbid state (PD–AKI), highlighting the role of the PI3K/AKT/mTOR and Nrf2/NF-κB signaling pathways. The mice were grouped as PD, AKI, or PD-AKI, and with or without the herbal pre-treatment, along with their respective controls. Motor impairments were assessed using the rotarod and pole climb assays. Biochemical indicators of renal function, oxidative stress markers, and inflammatory cytokines were quantified in kidney and brain tissues. Assessment of Nrf2, NF-κB, PI3K, AKT, and mTOR expression levels was performed using qRT-PCR. The AKI groups had significant renal impairment (4-fold increase in creatinine and 7.5-fold increase in BUN), oxidative stress (~5.5-fold increase), and increased cytokine levels (~1.5-fold increase), with downregulation of the PI3K/AKT/mTOR (~2-fold decrease) and Nrf2 signaling pathways (~1.8-fold decrease), alongside upregulation of NF-κB (~2.5-fold increase). The PD and PD-AKI groups exhibited significant neuroinflammation (~1.5-fold increase) and redox imbalance (~6-fold increase) in brain tissue, accompanied by motor impairments (1.6 to 4.6-fold decrease). Pre-treatment with Muc, Mor, and SM significantly ameliorated renal impairments (3.5-fold decrease in creatinine and ~5-fold decrease in BUN) and neurological deficits. These findings establish Muc, Mor, and SM extracts as potent, multi-target interventions capable of disrupting the feed–forward cycle of neuro-renal damage. Full article

Ship collisions pose substantial risks to maritime safety, causing vessel damage, casualties, and environmental impacts. Efficient extraction and analysis of key navigational and causal information from accident reports are important for risk assessment and decision support. This study proposes a framework for synthetic data generation, DistilBERT-based named entity recognition, and structured dataset construction for ship collision accidents. Using a template-based method, 56,000 annotated sentences were generated, covering navigational elements and causal factor trigger phrases. The fine-tuned DistilBERT model showed good performance on both synthetic and real accident reports. Statistical and co-occurrence analyses further indicated that failure to maintain proper lookout, failure to take effective evasive action, and failure to maintain safe speed were the main contributing factors across different environments and accident severity levels. Based on the extraction results, a standardized structured dataset was constructed to support subsequent causal analysis, dynamic risk modeling, and collision risk prediction. The study shows that combining template-based data synthesis with Transformer-based named entity recognition is a feasible approach for extracting information from maritime accident reports and transforming unstructured text into structured datasets. Full article

Background/Objectives: Melatonin (MEL) promotes sleep and recovery, while caffeine (CAF) enhances alertness and performance. Despite their common use among athletes, their potential interaction remains underexplored. This study examined the effects of MEL and CAF, administered separately or in combination, on sleep, physical performance, physiological, biochemical, and perceptual responses in trained males. Methods: In a randomized double-blind placebo-controlled crossover study, fourteen trained males (22.4 ± 2.9 years) underwent four conditions, designed to isolate the effects of each substance and their interaction: (1) PLA + PLA: placebo before sleep and placebo in the morning; (2) PLA + CAF: placebo before sleep and caffeine (3 mg·kg⁻¹) in the morning; (3) MEL + PLA: melatonin (6 mg) before sleep and placebo in the morning; and (4) MEL + CAF: melatonin before sleep followed by caffeine in the morning. One hour after the morning ingestion, participants performed the 5 m shuttle run test (5mSRT). Blood samples were collected pre- and post-exercise to assess markers of muscle damage (creatine kinase, lactate dehydrogenase, aspartate aminotransferase, and alanine aminotransferase) and inflammation (C-reactive protein). Peak heart rate (HR_peak) and rating of perceived exertion (RPE) were recorded throughout the test. Sleep was assessed only during the night following melatonin or placebo ingestion. Results: No differences were observed in sleep parameters between conditions (p > 0.05). Total distance in the 5mSRT increased following MEL + CAF and PLA + CAF conditions compared with PLA + PLA. Moreover, MEL + CAF reduced muscle damage and inflammation markers compared with PLA + PLA, MEL + PLA, and PLA + CAF conditions (p < 0.05). Conclusions: The ingestion of nocturnal MEL and next-day CAF was associated with improvements in certain high-intensity exercise performance outcomes, along with changes in muscle damage and inflammation. Full article

The Leibstadt Nuclear Power Plant (KKL) recently completed a comprehensive full-scope Fire Probabilistic Safety Assessment (Fire PSA) to fulfill the updated Swiss regulatory requirements (ENSI-A05) and align with international standards. The study was conducted using the NUREG/CR-6850 framework, incorporating state-of-the-art methodologies across different areas of the study, advanced fire modeling tools (CFAST and FDS), and the latest plant-specific data. As part of detailed fire modeling, a bespoke methodology was developed, tailored to KKL’s plant-specific characteristics, to ensure a systematic and standardized approach to fire scenario analysis while maintaining quality, consistency, and traceability. The analysis focused on evaluating fire risks in critical plant areas, such as the drywell, containment, main control room, remote shutdown areas, and cable spreading room. For each scenario, the fire-generated conditions, such as the extent of fire propagation and the time to damage targets, were analyzed using plant-specific heat release rate (HRR) and calorific potential (CALPOT) values. The study also addressed aspects such as multi-compartment analysis, fire-induced cable impacts, and treatment of multiple spurious operations. This paper highlights the methodological enhancements achieved by integrating international best practices and KKL-specific adaptations into a unified fire modeling framework. The results provide critical insights into fire propagation dynamics, validate the effectiveness of safety features, and support risk-informed decision-making for enhanced fire safety and regulatory compliance. The outcomes of fire modeling were utilized to develop fire event trees and refine the consequences of fire scenarios, thereby enabling a more realistic estimation of fire risk in the KKL Fire PSA study. Overall, the KKL PSA aims to serve as a benchmark for future fire risk assessments in the nuclear industry. Full article