Search Results (5,494)

The cessation of traditional mountain grazing has emerged as a principal driver of habitat degradation and the local extinction of Parnassius apollo (Linnaeus, 1758) in Serbia. While previous studies have cited multiple contributing factors, our research provides evidence that the abandonment of extensive livestock grazing has triggered vegetation succession, the disappearance of the larval host plant (Sedum album), and a reduction in microhabitat heterogeneity—conditions essential for the persistence of this stenophagous butterfly species. Through satellite-based analysis of vegetation dynamics (2015–2024), we identified clear structural differences between habitats that currently support populations and those where the species is no longer present. Occupied sites were characterized by low levels of exposed soil, moderate grass coverage, and consistently high shrub and tree density, whereas unoccupied sites exhibited dense encroachment of grasses and woody vegetation, leading to structural instability. Furthermore, MODIS-derived indices (2010–2024) revealed a consistent decline in vegetation productivity (GPP, FPAR, LAI) in succession-affected areas, alongside significant correlations between elevated land surface temperatures (LST), thermal stress (TCI), and reduced photosynthetic capacity. A wildfire event on Mount Stol in 2024 further exacerbated habitat degradation, as confirmed by remote sensing indices (BAI, NBR, NBR2), which documented extensive burn scars and post-fire vegetation loss. Collectively, these findings indicate that the decline of P. apollo is driven not only by ecological succession and climatic stressors, but also by the abandonment of land-use practices that historically maintained suitable habitat conditions. Our results underscore the necessity of restoring traditional grazing regimes and integrating ecological, climatic, and landscape management approaches to prevent further biodiversity loss in montane environments. Full article

Background: This systematic review investigates the role of virtual reality (VR)-based multisensory cognitive training in cognitive function, executive function and wayfinding ability among people diagnosed with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Methods: The review was carried out using PRISMA guidelines. PubMed, Scopus, Embase, and Google Scholar were searched up from inception to February 2025 using terms related to MCI, AD, VR, and cognitive functions. Studies were included if they involved participants with MCI or early AD, used VR-based training, collected baseline data, and reported cognitive outcomes. Results: Nine studies with MCI were included, but no eligible studies focused on AD. Seven out of nine eligible studies in MCI reported significant improvements in global cognitive function (MoCA, CERAD-K, MMSE). Some studies showed improvements in executive function (EXIT-25, TMT-A/B, and SCWT), while others found no significant differences. One study reported improved depression/mental status (GDS, MOSES, QoL-AD). Just one study reported improvement in functional ability (IADL). One study reported enhanced cognition and reduced discomfort (SSQ). VR programs were generally well-tolerated, with no significant adverse events reported. Conclusions: VR shows promise for improving cognitive function in MCI. VR also showed potential benefits in executive function and psychological outcomes like depression and quality of life, though consistency varied. Full article

The typical ranges available for electric vehicles (EVs) may be considered by users to be inadequate when compared to long, real-life trips, and charging operations may need to be planned along journeys. To evaluate the compatibility between vehicle features and charging options for realistic journeys performed by car, a simulation approach is proposed here, using travel data collected from real vehicles to obtain trip chains for multiple consecutive days. Car travel activities, including stops with the option of charging, were simulated by applying an agent-based approach. Charging operations can be integrated into trip chains for user activities, assuming that they remain unchanged in the event that vehicles switch to electric. The energy consumption of the analyzed trips, disaggregated by vehicle type, was estimated using the average travel speed, which is useful for capturing the main route features (ranging from urban to motorways). Data were recorded for approximately 25,000 vehicles in the Turin Metropolitan Area for six consecutive days. Market segmentation of the vehicles was introduced to take into consideration different energy consumption rates and charging times, given that the electric power, battery size, and consumption rate can be related to the vehicle category. Charging activities carried out using public infrastructure during idle time between consecutive trips, as well as those carried out at home or work, were identified in order to model different needs. Full article

Background/Objective: Exertional rhabdomyolysis (ER) is primarily driven by mechanical stress on muscles during strenuous or unaccustomed exercise, often exacerbated by environmental factors like heat and dehydration. While the general cellular pathway involving energy depletion and calcium overload is understood in horse ER models, the underlying mechanisms specific to the ER are not universally known within humans. This study aimed to evaluate whether patients with ER exhibited transcriptional signatures that were significantly different from those of healthy individuals. Methods: This study utilized RNA sequencing on skeletal muscle samples from 19 human patients with ER history, collected at a minimum of six months after the most recent ER event, and eight healthy controls to investigate the transcriptomic landscape of ER. To identify any alterations in biological processes between the case and control groups, functional pathway analyses were conducted. Results: Functional pathway enrichment analyses of differentially expressed genes revealed strong suppression of mitochondrial function. This suppression included the “aerobic electron transport chain” and “oxidative phosphorylation” pathways, indicating impaired energy production. Conversely, there was an upregulation of genes associated with adhesion and extracellular matrix-related pathways, indicating active restoration of muscle function in ER cases. Conclusions: The study demonstrated that muscle tissue exhibited signs of suppressed mitochondrial function and increased extracellular matrix development. Both of these facilitate muscle recovery within several months after an ER episode. Full article

China is one of the countries severely affected by earthquakes, making precise and timely identification of earthquake precursors essential for reducing casualties and property damage. A novel method is proposed that combines a rock acoustic emission (AE) detection technique with deep learning methods to facilitate real-time monitoring and advance earthquake precursor detection. The AE equipment and seismometers were installed in a granite tunnel 150 m deep in the mountains of eastern Guangdong, China, allowing for the collection of experimental data on the correlation between rock AE and seismic activity. The deep learning model uses features from rock AE time series, including AE events, rate, frequency, and amplitude, as inputs, and estimates the likelihood of seismic events as the output. Precursor features are extracted to create the AE and seismic dataset, and three deep learning models are trained using neural networks, with validation and testing. The results show that after 1000 training cycles, the deep learning model achieves an accuracy of 98.7% on the validation set. On the test set, it reaches a recognition accuracy of 97.6%, with a recall rate of 99.6% and an F₁ score of 0.975. Additionally, it successfully identified the two biggest seismic events during the monitoring period, confirming its effectiveness in practical applications. Compared to traditional analysis methods, the deep learning model can automatically process and analyse recorded massive AE data, enabling real-time monitoring of seismic events and timely earthquake warning in the future. This study serves as a valuable reference for earthquake disaster prevention and intelligent early warning. Full article

Background: Risk assessment in hyperthyroidism remains challenging. The aim of the present study is to determine the influence of hyperthyroid metabolic status on blood clotting and an increased risk of thrombosis. Methods: This prospective study included 50 patients after radical thyroidectomy and ablative radioiodine therapy because of thyroid carcinoma who were compared with 50 control subjects in a euthyroid metabolic state. Latent hyperthyroid patients with basal thyroid-stimulating hormone (TSH) ≤ 0.15 mU/L on levothyroxine hormone therapy were included. The control group was selected to match the patient group based on age and sex. The evaluation data were collected using laboratory coagulation tests and patient questionnaires. A bleeding and a thrombosis score were determined. Results: The coagulation parameters between the patient and control groups showed statistically significant differences. In particular, the patients’ group showed a significantly shortened activated partial thromboplastin time (aPTT/p = 0.009) and a significantly higher plasminogen activator inhibitor 1 (PAI-1/p < 0.001) compared to the control group. Age, sex, and medication use were not found to influence the patients’ laboratory results. Only body mass index was higher in the patient group than in the control group. Conclusions: Our results support a shift in the coagulation system in latent hyperthyroid metabolism towards increased coagulability and reduced fibrinolysis. A latent hyperthyroid metabolic state appears to be associated with an increased risk of thrombosis. Further prospective cohort studies with large patient populations are needed to verify the association between (latent) hyperthyroidism and thromboembolic events as well as to determine therapeutic anticoagulation or to adjust the indication for exogenous administration of thyroid hormone. Full article

Background/Objectives: This study aimed to assess real-world toxicity and efficacy data of patients with early and advanced breast cancer (BC) who received treatment with abemaciclib. Methods: This was a prospective/retrospective multi-institutional collection of clinicopathological, toxicity, and outcome data from patients with early or metastatic hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative BC who received treatment with abemaciclib in combination with endocrine therapy in departments of oncology in Greece. Treatment combinations of abemaciclib with any endocrine therapy were accepted. The primary end point was toxicity rate in all patients of the study. Results: From June/2021 to May/2024, 245 women received abemaciclib/endocrine combination therapy; the median age was 57 years. Of these, 169 (69%) received abemaciclib as adjuvant therapy for early-stage disease, while 76 (31%) were treated for advanced BC. At the time of the data cutoff, 133 (84.7%) patients remained in the 2-year treatment period. The most common adverse event (AE) was diarrhea (51%), primarily Grade ≤ 2. Dose modifications due to AEs were required in 19.2% of cases, while treatment discontinuation occurred in 5.1%. There was no difference in dose modification/discontinuation rates between older patients (>65 years) and the remaining patients. For early-stage BC patients, the 2-year DFS and OS rates were 90.8% and 100%, respectively. In patients with advanced cancer (70, 30.8%), 1-year PFS and OS rates were 78% and 96.3%, respectively. Conclusions: This study confirms the safety and effectiveness of abemaciclib in alignment with registrational trials offering valuable insights into toxicity management and clinical outcomes in routine practice without identifying new safety concerns. Clinical Trial Registration: ClinicalTrials.gov NCT04985058. Full article

Surveillance of swine influenza A virus (swIAV) traditionally focuses on respiratory matrices, yet emerging evidence suggests that fecal shedding and secondary environmental contamination may also contribute to viral dissemination. In this study, we collected and analyzed nasal, rectal, environmental, milk, and colostrum samples from naturally infected pigs in a commercial farm in Minas Gerais, Brazil. IAV RNA was detected in 25% of samples, including 42% from asymptomatic animals, with nasal swabs showing higher detection rates (30%) than rectal swabs (20%), though rectal Ct values were consistently higher, indicative of lower viral loads. We successfully isolated viable viruses from feces and effluent samples. Whole-genome sequencing revealed co-circulation of enzootic pH1N1 clade #2 (HA) and pN1 clade #4 (NA), alongside human-origin H3N2 sequences clustering within clade 3C.2a1b.2a.2a.1, and N2 segments related to pre-3C human lineages from 2001 to 2002. Phylogenetic and p-distance analyses support both recent reverse zoonosis and historical transmission events. Detection of complete HA/NA sequences from rectal swabs and treated effluent further emphasizes the surveillance value of non-respiratory matrices. The integration of respiratory and fecal/environmental sampling appears important to achieve more comprehensive IAV monitoring in swine herds and may have significant implications for One Health strategies in Brazil and beyond. Full article

African, Caribbean, and Black (ACB) communities face increased COVID-19 morbidity and mortality, coupled with significant barriers to vaccine acceptance and uptake. Addressing these challenges requires innovative, multifaceted strategies. Peer-led interventions, grounded in critical health literacy (CHL) and critical racial literacy (CRL), and integrating collaborative equity learning processes, can enhance community capacity, empowerment, and health outcomes, contributing to long-term health equity. This paper describes and presents the evaluative outcomes of a peer-led intervention aimed at enhancing COVID-19 vaccine confidence and acceptance. The Peer-Equity Navigator (PEN) intervention consisted of a specialized training curriculum grounded in CHL and CRL. Following training, PENs undertook a 5-month practicum in community or health settings, engaging in diverse outreach and educational activities to promote vaccine literacy in ACB communities. The evaluation utilized a modified Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) Framework, using quantitative and qualitative methods to collect data. Sources of data included tracking records with community feedback, and a PEN focus group, to assess program feasibility, outreach, and effectiveness. From 16 September 2022, to 28 January 2023, eight trained PENs conducted 56+ community events, reaching over 1500 community members. Both PENs and community members reported high engagement, endorsing peer-led, community-based approaches and increased vaccine literacy. The PEN approach proves feasible, acceptable, and effective in promoting positive health behaviors among ACB communities. This intervention has clear implications for health promotion practice, policy, and research in equity-deserving communities, including immigrants and refugees, who also face multiple and intersecting barriers to health information and care. Full article

Hurricanes and flooding events substantially elevate indoor fungal spore levels, which have been associated with increased risks of developing childhood asthma and other adverse respiratory outcomes. Although environmental fungal compositions following major hurricanes have been well characterized, the fungal communities within the nasal cavity (i.e., the nasal mycobiome) of exposed individuals remain unexplored. We collected nasal swab samples from infants following Hurricane Maria in San Juan, Puerto Rico, during two periods (March to August 2018 and February to September 2019). We processed a total of 58 samples (26 from the first year and 32 from the second year post-Hurricane Maria) and performed internally transcribed spacer (ITS) rRNA gene sequencing to characterize and compare the infant nasal mycobiome between the two groups. Although alpha-diversity did not differ significantly, beta-diversity analyses revealed significantly different fungal compositions between the two groups (p <0.01). Infants exposed during the first year post-Hurricane Maria had significantly higher abundances of Alternaria, Eutypella, Schizophyllum, and Auricularia, compared to infants from the second year. Alternaria was also more prevalent in the first-year than in the second-year infants (42% vs. 9%, p = 0.01). Our study provides evidence linking early-life hurricane exposures to elevated risks of developing childhood asthma. Full article

The Mw 7.8 Gorkha Earthquake of 25 April 2015 triggered over 25,000 landslides across central Nepal, with 4775 events concentrated in Gorkha District alone. Despite substantial advances in landslide susceptibility mapping, existing studies often overlook the compound role of post-seismic rainfall and lack robust spatial validation. To address this gap, we validated an ensemble machine learning framework for co-seismic landslide susceptibility modeling by integrating seismic, geomorphological, hydrological, and anthropogenic variables, including cumulative post-seismic rainfall. Using a balanced dataset of 4775 landslide and non-landslide instances, we evaluated the performance of Logistic Regression (LR), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) models through spatial cross-validation, SHapley Additive exPlanations (SHAP) explainability, and ablation analysis. The RF model outperformed all others, achieving an accuracy of 87.9% and a Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) value of 0.94, while XGBoost closely followed (AUC = 0.93). Ensemble models collectively classified over 95% of observed landslides into High and Very High susceptibility zones, demonstrating strong spatial reliability. SHAP analysis identified elevation, proximity to fault, peak ground acceleration (PGA), slope, and rainfall as dominant predictors. Notably, the inclusion of post-seismic rainfall substantially improved recall and F1 scores in ablation experiments. Spatial cross-validation revealed the superior generalizability of ensemble models under heterogeneous terrain conditions. The findings underscore the value of integrating post-seismic hydrometeorological factors and spatial validation into susceptibility assessments. We recommend adopting ensemble models, particularly RF, for operational hazard mapping in earthquake-prone mountainous regions. Future research should explore the integration of dynamic rainfall thresholds and physics-informed frameworks to enhance early warning systems and climate resilience. Full article

Background/Objective: In-hospital cardiac arrest has high incidence and poor survival rates, posing a significant healthcare challenge. It is important to intervene in the hours before the cardiac arrest to prevent poor outcomes. The modified early warning score (MEWS) is a validated tool for identifying a deteriorating patient. It is an aggregate of vital signs and level of consciousness. We retrospectively evaluated MEWS for trends that might predict patient outcomes. Methods: We performed a single-center, one-year, retrospective study. A comprehensive review was conducted for patients aged 18 years and above who experienced a cardiac arrest. Cases that occurred within an intensive care unit, emergency department, during a procedure, or outside the hospital were excluded. A total of 87 cases met our predefined inclusion criteria. We collected data at 12 h, 6 h and 1 h time periods prior to the cardiac arrest. A trend analysis using a linear model with analysis of variance with Bonferroni correction was performed. Results: Out of 87 patients included in the study, 59 (67.8%) had an immediate return of spontaneous circulation (ROSC). Among those who achieved ROSC, 41 (69.5%) died during the admission. Only 20.7% of the patients that sustained a cardiac arrest survived to discharge. A significant increase in the average MEWS was noted from the 12 h period (MEWS = 3.95 ± 2.4) to the 1 h period (MEWS = 5.98 ± 3.5) (p ≤ 0.001) and the 6 h period (4.65 ± 2.6) to the 1 h period (5.98 ± 3.5) (p = 0.023) prior to cardiac arrest. Conclusions: An increase in the MEWS may be a valuable tool in identifying at-risk patients and provides an opportunity to intervene at least 6 h before a cardiac arrest event. Further research is needed to validate the results of our study. Full article

Background/Objectives: Acne vulgaris is a widespread, chronic inflammatory skin condition that significantly impacts patients’ quality of life. Although oral isotretinoin remains the most effective treatment, recent evidence suggests that H₁-antihistamines such as desloratadine and levocetirizine may enhance acne therapy. This study assesses whether combining H₁-antihistamines to isotretinoin enhances treatment efficacy in acne vulgaris compared to isotretinoin alone. Methods: Our analysis included 10 randomized controlled trials involving 675 patients collectively, predominantly from Asia and the Middle East. Data were extracted by two independent reviewers, with discrepancies resolved by a third. Risk of bias was assessed using the Cochrane RoB 2 tool. Analyses were performed using RevMan 5.4 with random-effects models, and heterogeneity was evaluated via I² and Q tests. Sensitivity analyses were conducted to assess result robustness. Results: Combination therapy with isotretinoin and desloratadine showed a significantly greater reduction in GAGS (Global Acne Grading Scale) score by week 12 (p < 0.00001; MD 2.68, 95% CI 1.60 to 3.75; I² = 0%) while earlier timepoints showed non-significant or borderline results. For inflammatory lesions, significant improvements with desloratadine emerged at weeks 4, 8, and 12 after excluding an influential outlier, with low heterogeneity and consistent direction of effect. Non-inflammatory lesions did not differ significantly at weeks 4 or 8. At week 12, a significant reduction was seen in the desloratadine subgroup (OR 2.61, p = 0.003, I² = 11%) and in overall pooled analysis (OR 2.77, p < 0.0001, I² = 2%). Among side effects, acne flare-ups, pruritus, and cheilitis were significantly reduced in the desloratadine group, as well as in pooled analysis. Xerosis did not consistently differ between groups. Overall, desloratadine improved tolerability and reduced mucocutaneous adverse events more than levocetirizine. Conclusions: Current evidence suggests that combining oral antihistamines with isotretinoin may offer therapeutic benefits in acne management, particularly in enhancing tolerability and potentially improving clinical outcomes, as reflected by significant reductions in GAGS scores and mucocutaneous adverse effects such as cheilitis, pruritus, and acne flare-ups. Full article

Porcine reproductive and respiratory syndrome virus remains one of the most economically significant pathogens in swine production, with PRRSV-2 being the dominant variant in the United States. While lineage classification has traditionally relied on ORF5 sequencing, recent studies suggest that this single-gene approach may overlook key evolutionary events such as recombination. In this study, we performed whole-genome sequencing and phylogenetic analysis of seven PRRSV-2 isolates collected in the U.S. between 2006 and 2024. Using reference-guided assembly, lineage assignment, and recombination detection with RDP5 and SIMplot, we identified discordant phylogenetic placements between ORF5 and whole genomes in four of the seven isolates. These discordances were explained by multiple recombination events affecting different genomic regions, particularly ORF2–ORF7. In contrast, three isolates showed phylogenetic concordance and no strong evidence of recombination. Our findings demonstrate that recombination plays a significant role in shaping PRRSV-2 evolution and highlight the limitations of ORF5-based lineage classification. Whole-genome surveillance is therefore essential to accurately track viral diversity, detect recombinant strains, and inform control strategies. This work underscores the need for a broader adoption of full-genome analysis in routine PRRSV surveillance and research. Full article

Falls are a major safety concern in physically demanding occupations such as roofing, where workers operate on inclined surfaces under unstable postures. While inertial measurement units (IMUs) are widely used in wearable fall detection systems, they often fail to capture early indicators of instability related to foot–ground interactions. This study evaluates the effectiveness of plantar pressure sensors, alone and combined with IMUs, for fall detection on sloped surfaces. We collected data in a controlled laboratory environment using a custom-built roof mockup with incline angles of 0°, 15°, and 30°. Participants performed roofing-relevant activities, including standing, walking, stooping, kneeling, and simulated fall events. Statistical features were extracted from synchronized IMU and plantar pressure data, and multiple machine learning models were trained and evaluated, including traditional classifiers and deep learning architectures, such as MLP and CNN. Our results show that integrating plantar pressure sensors significantly improves fall detection. A CNN using just three IMUs and two plantar pressure sensors achieved the highest F1 score of 0.88, outperforming the full 17-sensor IMU setup. These findings support the use of multimodal sensor fusion for developing efficient and accurate wearable systems for fall detection and physical health monitoring. Full article