Browse Articles

Utility of SIRS criteria and QSOFA score in identifying patients with central nervous system infections at risk for poor outcome

Study on the spatial mechanical behavior of the cable tower anchorage zone in long-span curved T-shaped rigid-frame extradosed bridge for high-speed railway

Association between the left-sided atrial septal pouch and the cryptogenic stroke – an updated systematic review and meta-analysis

Abstract Cryptogenic stroke, named embolic stroke of undetermined source, refers to patients for whom the etiology of embolism remains unknown. Recently a new cardiac entity, the left-sided septal pouch (LSSP), has been identified as a possible source of thromboembolic events. In the current study, we aimed to perform a systematic review of the literature on this topic and to determine the association between the LSSP presence and occurrence of cryptogenic stroke using meta-analytical methodologies. A detailed search of electronic databases for studies that compared the presence of LSSP in subjects with cryptogenic stroke and non-stroke controls was performed. Data were extracted and pooled into a meta-analysis. We included eight studies in the meta-analysis, in which there were a total of 506 patients with cryptogenic stroke and 1600 patients in the control group. The pooled prevalence of LSSP among cryptogenic stroke patients was 31.6% (95% CI: 20.6–43.8). In the non-stroke control group the pooled prevalence of LSSP was 22.0% (95% CI: 15.0-29.8). The meta-analysis showed that there is a higher risk of cryptogenic stroke in patients with LSSP than in patients without LSSP (OR: 1.57, 95% CI: 1.23–2.01; p  < 0.01). A subgroup meta-analysis of transesophageal echocardiography studies demonstrated the same association (OR: 1.59; 95% CI: 1.21–2.08; p  < 0.01). In studies where the mean patient age was < 60 years, LSSP was associated with a higher risk of cryptogenic stroke (OR: 1.67; 95% CI: 1.22–2.29; p  < 0.01). However, in studies where the mean patient age was > 60 years, the association was not statistically significant (OR: 1.58; 95% CI: 0.75–3.32).

Machine learning applied to global scale species distribution models

Abstract Species Distribution Models (SDMs) are widely used in ecology to analyze historical and future patterns of marine species distributions. Given the growing impact of climate change, predicting potential shifts in species ranges has become a key challenge. In this study, we apply Bayesian Additive Regression Trees (BART), a non-parametric machine learning algorithm, to estimate and forecast the global distribution of marine turtle species under different climate change scenarios. We model both individual species and their combined functional group, assess their historical and future habitat suitability, and examine the contribution of key environmental predictors. To evaluate BART’s performance, we conduct a simulation study under two contrasting distributional scenarios: a cosmopolitan and a persistent species. We also test the sensitivity of BART to pseudo-absence data and compare its performance with MaxEnt and Generalized Additive Models (GAMs). Results indicate that BART performs slightly better overall, particularly under pseudo-absence settings, showing higher accuracy and more stable sensitivity and specificity. These findings highlight BART as a reliable alternative for long-term, global-scale species distribution modeling in marine systems.

Academic anxiety and cognitive reflection in neurodivergence based on evidence from a large international sample

Abstract Anxiety is commonly experienced by neurodivergent individuals participating in higher education, related to both cognitive performance and academic achievement. Whereas certain anxieties in neurodivergence (e.g., social and general anxiety) have received more attention, scant research has considered mathematics and statistics anxiety. In this study, 1383 university students (679 neurotypical, 704 neurodivergent individuals)—matched on age, gender, education level, and country of origin—completed measures assessing various types of academic-related anxiety, attitudes toward mathematics, self-efficacy, and cognitive reflection. Results showed that neurodivergent students exhibited higher anxiety levels across measures, including mathematics and statistics anxiety. However, only cognitive and somatic anxiety, and social anxiety were related to neurodivergent status after taking into account the effects of the other measures. Despite differing anxiety levels (which showed variability between different neurodivergences), neurodivergent and neurotypical students in general were equivalent in cognitive reflection scores, suggesting similar levels of analytic thinking skills, including reasoning about mathematical content. In both the neurotypical and neurodivergent groups, higher levels of cognitive reflection were associated with male gender, less fear of negative evaluation, and lower mathematics and creativity anxiety, replicating and extending previous work. Our findings have implications for supporting neurodivergent individuals in academic settings and other sectors.

Upscaling effects on infectious disease emergence risk emphasize the need for local planning in primary prevention within biodiversity hotspots

Abstract Zoonotic risk assessments are increasingly vital in the wake of recent epidemics. The microbial diversity of parasitic organisms correlates with host species richness, with regions of high biodiversity facing elevated risks of emerging zoonotic infections. While habitat loss and fragmentation reduce species diversity, anthropogenic encroachment, particularly in forested areas, amplifies human exposure to novel pathogens. This study integrates host habitat, biodiversity, human encroachment, and population at risk to estimate novel disease emergence and epidemic risk at multiple spatial scales. Using Java, Indonesia, as a case study, we demonstrate that degrading spatial resolution leads to information loss, with optimal resolutions typically below 2000 m, ideally around 500 m when native-resolution processing is unfeasible. Gravity models of epidemic spread highlight Jakarta and West Java as high-risk areas, with varying contributions from surrounding regions. Our spatial analysis underscores the influence of population centers on forest management and agroforestry practices. These findings offer valuable insights for guiding pandemic prevention research and improving pathogen- and driver-based risk monitoring strategies.

Identification of miRNA biomarkers for essential hypertension in small samples based on MPGAM

Investigating the expression changes of several key genes in prostate cancer cells under exposure to the ELF pulsed electromagnetic fields

An intelligent approach to predict the drilling penetration rate using acoustic emission technique (AET)

Investigating the effect of task engagement during intertrial rest periods on micro offline gains

Enhancing Urdu hate speech detection through differential transfer learning and adaptive loss functions

Wear behaviour of hybrid ceramic reinforced FSP surface composite at varying temperatures

Effects of different exercise levels on serum trace element concentrations

Assessing through focus groups the demand, facilitators, and barriers of a cognitive stimulation intervention for healthy older adults

Preclinical pancreatic cancer mouse models for treatment with small molecule inhibitors: a systematic review and meta-analysis

Abstract Pancreatic cancer (PC) is an aggressive malignant disease with poor prognosis, often diagnosed late, progressing rapidly, and resistant to chemotherapy. Although small molecule inhibitors (SMIs) show promise in preclinical PC models, translation into clinics remains challenging. In this systematic review and meta-analysis, we screened literature according to predefined criteria to identify preclinical PC mouse models used for SMI therapy in primary tumors, assess reporting quality, and evaluate tumor reduction, heterogeneity and publication bias. Following a pre-registered PROSPERO protocol (CRD42022314932), literature searches in PubMed and Embase yielded 2972 articles, of which 297 were included for data extraction. Most studies used PDX models or MiaPaCa-2 and PANC-1 cell lines as heterotopic xenografts, with Foxn1 nu mice representing the predominant genetic background. Reporting quality, assessed using the ARRIVE guidelines, revealed substantial gaps, particularly in blinding (94% not reported), inclusion/exclusion criteria (49% not reported), and randomization (34% not reported). Meta-regression accounted for part of the observed heterogeneity and funnel plot asymmetry was consistent with publication bias. This study emphasized the large variability among preclinical PC mouse models used to investigate SMI candidates and the complexity of model choice highlighting the critical need for improved reporting practices to enhance reproducibility and reliability of preclinical tumor models.

Triglyceride-glucose index variability and risk of all-cause and cardiovascular mortality

Sex specific seasonal variation in the diet of brown bears in human dominated landscapes

Abstract Understanding the foraging ecology of brown bears ( Ursus arctos ) in human-dominated landscapes is essential for effective wildlife management and conflict mitigation. In this study, we investigated the seasonal diet composition of brown bears in the Western Carpathians, Slovakia, using a combination of molecular genetic and microhistological scat analyses. We analysed 198 brown bear scats (101 males, 97 females) collected throughout the year in central Slovakia, to assess seasonal variation in diet, identify sex-specific foraging patterns, and evaluate the use of anthropogenic food resources. Vegetation constituted the primary dietary component year-round, with hard mast frequency dominating in spring ( FO  = 45%), autumn ( FO  = 67%), and winter ( FO  = 82%), while soft mast ( FO  = 48%) and anthropogenic food ( FO  = 30%) prevailed in summer. Dietary energy intake from anthropogenic food was considerable in spring ( EDEC  = 15%) but peaked in summer ( EDEC  = 34%) and was consistently higher in males across all seasons. In spring, males consumed a considerable amount of anthropogenic food ( EDEC  = 32%), while it was negligible for females ( EDEC  = 3%). In summer, male consumption of anthropogenic food increased further (EDEC = 40%), and although females still consumed less than males, their intake rose by 23% compared to spring ( EDEC  = 26%). Males also consumed more vertebrates and hard mast, whereas females relied more heavily on soft mast and natural food sources, likely reflecting sex-specific trade-offs between energetic needs and risk avoidance. Seasonal dietary diversity was highest in summer and lowest in winter, with the greatest trophic divergence between sexes occurring during spring and summer. These findings highlight the dietary plasticity of brown bears in response to seasonal and anthropogenic resource availability, and emphasize the importance of regulating anthropogenic food access, particularly supplemental feeding and agricultural crops, to reduce human-bear conflict.

Retraction Note: Vasculogenic mimicry formation in EBV-associated epithelial malignancies

Change of electronic structure of ultrathin film of indium tin oxide by “In situ” Ar+ ion non-reactive successive etching process

Tissue localization of natural killer cells dictates surveillance of lung metastasis

Abstract The lung is a common metastatic site for various cancer types. Successful immune surveillance of lung metastasis depends on Natural Killer (NK) cells, but the underlying mechanisms are elusive. Here, we show that the pulmonary vasculature recruits and maintains highly cytotoxic, differentiated CD11b high NK cells through the integrins Lymphocyte Function-associated Antigen 1 (LFA-1) and Very Late Antigen (VLA-4). These NK cells rapidly eradicate metastasizing tumor cells within the vasculature. However, after the initial clearing phase, differentiated pulmonary NK cells largely remain intravascular and fail to track extravasated tumor cells. In contrast, metastatic nodules are preferentially infiltrated with circulating, less differentiated CD27 high NK cells. Within the metastatic lung, CD11b high NK cells undergo a rapid impairment of their migratory and cytotoxic features, while the intranodular CD27 high subset transitions towards a transforming growth factor β (TGF-β)-driven state with limited persistence. Our findings demonstrate that the compartmentalization of NK cells is key for effective tumor cell surveillance in lung metastasis and suggests that TGF-β-resistant CD27 high NK cells may offer a promising therapeutic avenue to enhance local anti-tumor activity.