Search Results (2,156)

Coccidioidal meningitis (CM) is a rare but life-threatening complication of disseminated coccidioidomycosis, occurring in ~16% of cases, particularly among children in endemic regions such as the southwestern US and northern Mexico. Without timely diagnosis and antifungal therapy, pediatric CM is almost universally fatal within the first year. Hydrocephalus develops in up to 50% of cases. In 2000, Galgiani et al. established fluconazole as first-line therapy for CM. Subsequent guidelines refined management but did not specifically address pediatric patients (>1 month–≤19 years). No studies in the fluconazole era have systematically evaluated risk factors for complications in this population. We therefore conducted a systematic review and proportional synthesis of pediatric CM cases, focusing on CNS complications and outcomes. PubMed/MEDLINE, Embase (Ovid), and Web of Science were systematically searched (2000–2025). PROSPERO registration ID (1130290). Inclusion criteria encompassed epidemiological studies, case series, and case reports that described at least one pediatric case of CM or CNS involvement, confirmed by diagnostic methods. Cases in adults, neonates (<1 month), congenital infections, teratogenicity studies, reviews, or incomplete reports were excluded. Only cases with complete individual data (n = 48) were included. Methodological rigor was ensured using JBI Critical Appraisal Tools. Of 1089 studies, 31 met the inclusion criteria, representing 3874 pediatric cases. CM/CNS involvement was confirmed in 165 cases (4.25%; 95% CI: 3.6–4.9%), with hydrocephalus in 62 (37.5%). Among 48 case reports with complete data, fluconazole was first-line therapy in 65%. Serum CF titers ≥ 1:16 were associated with hydrocephalus plus stroke (p = 0.027) and independently predicted adverse outcomes (relapse/death; OR = 4.5, p = 0.037), whereas lifelong azole therapy was associated with improved outcomes (overall survival mean, 82 vs. 32 months; p = 0.002). Pediatric CM remains highly lethal, with hydrocephalus a frequent and severe complication. High serum CF titers (≥1:16) predict poor outcomes, emphasizing the urgent need for standardized, pediatric-specific diagnosis and management guidelines. Full article

This study investigates the development and application of the GDELT (Global Database of Events, Language, and Tone) news database. Through experiments, we conducted a quantitative statistical analysis of the GDELT event database to evaluate its practical characteristics. The results indicate that although the database achieves comprehensive coverage across all countries and regions and includes most major global media outlets, the accuracy rate of its key fields is only approximately 55%, with a data redundancy as high as 20%. Based on these findings, while the GDELT data demonstrates good coverage and data integrity, data correction and deduplication are recommended before its use in research contexts and industrial applications. Subsequently, a survey of the existing literature reveals that current studies using GDELT primarily focused on event-related metrics, such as event quantity, tone, and GoldsteinScale, for application in international relations analysis, crisis event prediction, policy effectiveness testing, and public opinion impact analysis. Nevertheless, news constitutes a fundamental channel of information dissemination in media networks, and the propagation of news events through these networks represents a critical area of study for information recommendation, public opinion guidance, and crisis intervention. Existing research has employed the Event, GKG, and Mentions tables to construct cross-national news flow network models. However, the informational correlations across different data table fields have not been fully leveraged in preliminary data selection, leading to substantial computational overhead. To advance research in this field, this study employs chained list queries on the Event and Mentions tables within GDELT. Using social network analysis, we constructed a media co-occurrence network of event reports, through which core hubs and associative relationships within the event dissemination network are identified. Full article

The global rise of antimicrobial resistance (AMR), exacerbated by the COVID-19 pandemic, has led to a surge in infections caused by multidrug-resistant (MDR) bacteria. A key driver of this phenomenon is co-selection, where exposure to one antimicrobial promotes resistance to others via horizontal gene transfer (HGT) mediated by mobile genetic elements (MGEs). Carbapenem-resistant Enterobacteriaceae, known for their genomic plasticity, are particularly worrisome; yet genomic data from Latin America—especially Ecuador—remain scarce. This study investigated four carbapenem-resistant clinical isolates (two Klebsiella pneumoniae ST1440 and two Serratia marcescens) from tracheal aspirates of three ICU patients during a COVID-19 outbreak at Hospital IESS Quito Sur, Ecuador. Phenotypic profiling and whole-genome sequencing were performed, followed by bioinformatic reconstruction of plasmid content. Nineteen plasmids were identified, carrying 70 resistance-related genes, including antimicrobial resistance genes (ARGs), metal resistance genes (MRGs), integrons, transposons, and insertion sequences. Hierarchical clustering revealed six distinct gene clusters, with several co-localizing ARGs and genes for resistance to disinfectants and heavy metals—suggesting strong co-selective pressure. Conjugative plasmids harboring high-risk elements such as blaKPC-2, qacE, and Tn4401 were found in multiple isolates, indicating potential interspecies dissemination. These findings emphasize the importance of plasmid-mediated resistance during the pandemic and highlight the urgent need to enhance genomic surveillance and infection control, particularly in resource-limited healthcare settings. Full article

This paper explores the methodological implications, processes, and opportunities relating to the use of participatory approaches in the study of intersecting inequalities. Within the context of an international, interdisciplinary project (Partnerships for Equality and Inclusion (PEI)), four sub-projects elected to use participatory methodologies to engage with marginalized and excluded communities so that their needs, voices, and knowledge were included in the data collection process and the dissemination of findings at micro (community) and macro (policy) levels. The four project teams in Kenya, Vietnam, Myanmar, and Nigeria engaged with training and research processes so that participants with lived experience could contribute both as peer researchers and in focus groups that contributed study data. In this paper, we bring together the findings and learning from each project about how these methods contributed to equity in the research process. We conclude with insights and recommendations on how participatory methods can enable an intersectional and grounded perspective from people facing multiple inequalities in periods of crisis and political change. Full article

Fowl adenovirus (FAdV) can cause different poultry diseases with economic losses in the broilers and layers commercial farms. FAdV is currently classified into five species and 12 serotypes, disseminated in poultry flocks worldwide. The present study aimed to identify FAdV species and serotypes in Brazilian poultry farms. A total of 678 chicken flocks from the main Brazilian poultry-producing regions were evaluated for FAdV infection between 2020 and 2023. FAdV was detected by a real-time PCR targeting 52K gene and further genotyped by partial sequencing of the hexon gene followed by phylogenetic analyses. The results demonstrated that FAdV was detected in 72 flocks (10.6%). In 46 of these samples, FAdV species and serotypes could be identified, including three main species: Aviadenovirus ventriculi (FAdV-A = 15), Aviadenovirus gallinae (FAdV-D = 15) and Aviadenovirus hepatitidis (FAdV-E = 16). Phylogenetic analysis based on 173 partial hexon sequences (including sequences from this study, 44 previously sequenced in Brazil, and 86 data from other countries) revealed five separate clades for FAdV species. All Brazilian FAdVs were classified into the same three species reported above (FAdV-A = 19, FAdV-D = 34, FAdV-E = 37), and also in well-supported subclades for each serotype: FAdV-A1 (n = 19), FAdV-D9 (n = 1), FAdV-D11 (n = 33), FAdV-E6 (n = 1), FAdV-E8a (n = 33), FAdV-E8b (n = 3). Amino acid substitutions in the hyper variable regions (1, 2 and 3) and conserved motifs of the Hexon protein were further analyzed, enabling discrimination between closely related serotypes. This study demonstrates the circulation of different FAdVs in Brazil, highlighting FAdV-A1, FAdV-D9, FAdV-D11, FAdV-E6, FAdV-E8a and FAdV-E8b. The findings reported here also indicate genetic and amino acid diversity in the Hexon protein of the FAdVs in Brazilian poultry farms, which are of importance for molecular surveillance and poultry diseases control strategies. Full article

Museum building information modeling is an emerging research field that harnesses the potential of digitization applied to both architecture and artworks. This present work aims to innovate the current practices by integrating virtual tours and semantic-aware models while also fostering the uses of the informed models beyond management or professional use. The methodology consists of a 3D informed model able to manage the collection catalog, leveraging the BIM paradigm. Subsequently, a VR desktop tool is developed based on panoramic images fully interoperable with data enrichment and all the informative layers. The results demonstrate the feasibility of a workflow for a multilayer platform for museums that balances computational issues and ensures correct representation of various levels of geometry and information. The assessment in a real-world scenario through a fully operative prototype of museum BIM to VR also allows us to outline perspectives for dissemination purposes. Full article

Introduction: Lumbar radiculopathies involving the entrapment of nerve roots in the lumbar spine are common neuropathic conditions. These conditions affect 40% to 70% of individuals in their lifetime and lead to significant medical costs. Objective: This study aims to identify clinical, psychological, and biomarker-based prognostic factors that predict functional outcomes following surgery for lumbar radiculopathy. Materials and Methods: This prospective cohort study, conducted at Hospital Central de la Defensa Gómez Ulla, Madrid (Spain), adheres to the STROBE guidelines. The study includes patients aged 18–75 with lumbar radiculopathy, confirmed by clinical diagnosis, imaging, and electromyography (EMG) findings. Exclusion criteria include previous lumbar spine surgeries and systemic diseases. The primary outcome is the Oswestry Low Back Pain Disability Questionnaire. Sample size calculations, based on a conservative effect size (f² = 0.20), determined the need for 172 participants, accounting for a 15% dropout rate and 80% power. Procedure: Patients will undergo an initial assessment, including EMG tests, sociodemographic and psychological questionnaires, blood sample tests, and physical questionnaires. This process will be repeated six months post-intervention, except for the blood sample test, expectations questionnaire, and EMG, which will be performed only once. Statistical Analyses: Data will be analyzed using Python 3.12.3, employing a multivariate linear regression analysis. Assumptions of linearity, independence, homoscedasticity, normality, and no multicollinearity will be validated. Corrective measures will be applied if assumptions are violated. Ethics and Dissemination: The study follows the Declaration of Helsinki guidelines and has been approved by the Ethics Committee of Universidad Rey Juan Carlos (070220241052024). Potential risks will be minimized, and adverse events will be recorded and addressed. Findings will be published in high-impact journals and presented at conferences. Full article

Extracellular vesicles (EVs) are rapidly gaining recognition as critical mediators of inter-cellular communication during viral infections. To contribute to fill the gap in knowledge regarding the role of EVs in adenovirus infection, we used human adenovirus type 4 of species Mastadenovirus exoticum (HAdV-E4), a prevalent respiratory and ocular pathogen, and characterized the cargo and biological properties of EVs released by HAdV-E4-infected A549 lung epithelial cells at a pre-lytic stage of infection. Using immunocapture-based isolation and multi-omics approaches, we found that infection profoundly alters the EV uploaded proteome and small non-coding RNA repertoire. Mass spectrometry identified 268 proteins unique to EVs purified from infected cells (AdV-EVs), with enrichment in pathways supporting vesicle trafficking and viral protein translation, and importantly also a few virus-encoded proteins. A small RNA transcriptome analysis showed differential uploading in AdV-EVs of various small non-coding RNAs, including snoRNAs, as well as the presence of virus associated RNAs I and II. Notably, AdV-EVs contained viral genomic DNA and could initiate productive infection upon delivery to naïve cells in the absence of detectable viral particles. Our data suggest that EVs released during the HAdV-E4 infection may serve as vehicles for non-lytic viral dissemination and highlight their possible role in intra-host dissemination Full article

Background/Objectives: As global aging accelerates, there is a pressing and empirically substantiated demand for integrated and sustainable strategies, as evidenced by the rising prevalence rates of chronic conditions, social isolation, and digital exclusion among older adults worldwide. These factors underscore the urgent need for multidimensional interventions that simultaneously target physical, psychological, and social well-being. The HOPE-FIT (Hybrid Outreach Program for Exercise and Follow-up Integrated Training) model and the SAGE (Senior Active Guided Exercise) program were designed to address this need through a hybrid framework. These programs foster inclusive aging by explicitly bridging digitally underserved groups and mobility-restricted populations into mainstream health promotion systems through tailored exercise, psychosocial support, and smart-home technologies, thereby functioning as a scalable meta-model across healthcare, community, and policy domains. Methods: HOPE-FIT was developed through a formative, multi-phase process grounded in the RE-AIM framework and a Hybrid Type II effectiveness–implementation design. The program combines professional health coaching, home-based and digital exercise routines, Acceptance and Commitment Performance Training (ACPT)-based psychological strategies, and smart-home monitoring technologies. Empirical data from pilot studies, large-scale surveys (N = 1000), and in-depth user evaluations were incorporated to strengthen validity and contextual adaptation. Culturally tailored content and participatory feedback from older adults further informed ecological validity and program refinement. Implementation Strategy/Framework: The theoretical foundation integrates implementation science with behavioral and digital health. The RE-AIM framework guided reach, fidelity, and maintenance planning, while the Hybrid E–I design enabled the concurrent evaluation of effectiveness outcomes and contextual implementation strategies. Institutional partnerships with community centers, public health organizations, and welfare agencies further facilitated the translation of the model into real-world aging contexts. Dissemination Plan: The multi-pronged dissemination strategy includes international symposia, interdisciplinary academic networks, policy briefs, localized community deployment, and secure, authenticated data sharing for reproducibility. This design facilitates evidence-informed policy, empowers practitioners, and advances digital health equity. Ultimately, HOPE-FIT constitutes a scalable and inclusive model that concretely addresses health disparities and promotes active, dignified aging across systems and disciplines. Full article

Due to the complexity of district heating systems, improved novel methods of district heating network (DHN) simulation are still being introduced in the literature. The subject of validation strategies for DHN simulation models emerges as one that has not been thoroughly analyzed before. Based on the considered subset of models reported in the literature, a general classification of the validation strategies of DHN models is proposed in this study. The proposed classification is based on two criteria: data and topology used in the validation case studies. This study provides insights into validation strategies for DHN models, their practical implementation and evaluation criteria, and the approaches used in the validation of these models. The standardization of DHN model validation approaches and the possibility to replicate the validation results seem to be limited. It seems that the dissemination of dedicated benchmarks or commonly accepted methodologies featuring evaluation criteria suitable for models’ intended applications could have a positive impact on the thoroughness of future DHN model validation and the replicability of validation results. To assist in future research, preliminary validation guidelines are proposed that may serve as a starting point in designing validation case studies for DHN models. Full article

Brain–Computer Interfaces (BCIs) offer a non-invasive pathway for restoring motor function, particularly for individuals with limb loss. This review explored the effectiveness of Electroencephalography (EEG) and function Near-Infrared Spectroscopy (fNIRS) in decoding Motor Imagery (MI) movements for both offline and online BCI systems. EEG has been the dominant non-invasive neuroimaging modality due to its high temporal resolution and accessibility; however, it is limited by high susceptibility to electrical noise and motion artifacts, particularly in real-world settings. fNIRS offers improved robustness to electrical and motion noise, making it increasingly viable in prosthetic control tasks; however, it has an inherent physiological delay. The review categorizes experimental approaches based on modality, paradigm, and study type, highlighting the methods used for signal acquisition, feature extraction, and classification. Results show that while offline studies achieve higher classification accuracy due to fewer time constraints and richer data processing, recent advancements in machine learning—particularly deep learning—have improved the feasibility of online MI decoding. Hybrid EEG–fNIRS systems further enhance performance by combining the temporal precision of EEG with the spatial specificity of fNIRS. Overall, the review finds that predicting online imagined movement is feasible, though still less reliable than motor execution, and continued improvements in neuroimaging integration and classification methods are essential for real-world BCI applications. Broader dissemination of recent advancements in MI-based BCI research is expected to stimulate further interdisciplinary collaboration among roboticists, neuroscientists, and clinicians, accelerating progress toward practical and transformative neuroprosthetic technologies. Full article

Grassland fire risk perception constitutes a fundamental element of fire risk assessment and underpins the evaluation of response capacities in grassland regions. This study examines Qinghai Province, the fourth-largest pastoral region in China, as a case study to develop an evaluation index system for assessing residents’ perceptions of grassland fire risk. Using micro-level survey data, the study quantifies these perceptions and applies a quantile regression model to investigate influencing factors. The results indicate that: (1) the average grassland fire risk perception index among residents in Qinghai Province’s grassland areas is 0.509, with response behaviors contributing the most and response attitudes contributing the least; (2) Residents in agricultural areas perceive higher risks than those in semi-agricultural/semi-pastoral or purely pastoral areas, and individuals in regions with moderate dependency ratios and moderate fire-susceptibility conditions demonstrate the highest performance, whereas those in pastoral and high-susceptibility zones exhibit signs of “risk desensitization”; (3) risk communication and information dissemination are the primary drivers of enhanced perception, followed by climate variables, whereas individual characteristics of residents attributes exert no significant effect. It is recommended to monitor the impacts of climate change on fire risk patterns, update risk information dynamically, address deficits in residents’ cognition and capabilities, strengthen behavioral guidance and capacity-building initiatives, and foster a transition from passive acceptance to active engagement, thereby enhancing both cognitive and behavioral responses to grassland fires. Full article

In large-scale recommendation scenarios, achieving high-precision ranking requires simultaneously modeling user interest dynamics and content propagation potential. In this work, we propose a unified framework that integrates a temporal interest modeling stream with a multimodal virality encoder. The temporal stream captures sequential user behavior through the self-attention-based modeling of long-term and short-term interests, while the virality encoder learns latent virality factors from heterogeneous modalities, including text, images, audio, and user comments. The two streams are fused in the ranking layer to form a joint representation that balances personalized preference with content dissemination potential. To further enhance efficiency, we design hierarchical cascade heads with gating recursion for progressive refinement, along with a multi-level pruning and cache management strategy that reduces redundancy during inference. Experiments on three real-world datasets (Douyin, Bilibili, and MIND) demonstrate that our method achieves significant improvements over state-of-the-art baselines across multiple metrics. Additional analyses confirm the interpretability of the virality factors and highlight their positive correlation with real-world popularity indicators. These results validate the effectiveness and practicality of our approach for high-precision recommendation in big data environments. Full article

Background/Objectives: Health literacy has an impact on students’ reproductive health. Therefore, the objective of our study is to systematically examine, identify, and summarize all research on the role of health literacy in fertility awareness and reproductive health among university students in order to understand how health literacy influences reproductive health outcomes in this population. Methods: Using the PRISMA guidelines, a comprehensive systematic search was conducted using electronic databases, such as PubMed, EMBASE, CINAHL, Scopus, and Google Scholar. The protocol was registered in the Prospective Register for Systematic Reviews (PROSPERO, CRD 42024566268). All studies were imported into EndNote software and screened using a two-level title/abstract screening process. The included studies were narratively summarized. Results: The database search identified 1360 articles; 116 duplicates were removed, and thus, 1244 were initially screened, leading to 1133 exclusions. A total of 111 articles underwent full screening, and 94 were then excluded. A total of 14 articles were included for data extraction. Health literacy impacts university students’ behaviour, fertility awareness, and reproductive health knowledge. Students with higher health literacy show more understanding of critical topics such as fertility and emergency contraception. Socioeconomic factors play a crucial role in shaping health literacy and reproductive choices, while gender disparities highlight the need for targeted educational interventions, particularly for male students. Effective educational programs have been shown to enhance health literacy. Additionally, technology integration serves as a valuable tool for disseminating reproductive health information. Cultural context also plays a vital role in influencing health literacy. Conclusions: The findings of this study emphasize the importance of comprehensive strategies to enhance health literacy among university students, and future research should focus on developing and evaluating targeted educational programs that address gender disparities and socioeconomic factors influencing health literacy. Full article

Much attention has been paid to female, pillar-based figurines from Iron II Judah, and the veneration of a major goddess in that territory. Similarly, female figurines throughout the Levant have largely been treated as evidence of goddess-worship, writ large. While the focus on goddesses and fertility has been critiqued by contemporary scholarship, the prevalence of female terracotta figurines remains a productive ground for critical inquiry. There is still no consensus explaining the dissemination of female figurines throughout Levantine states during the Iron IIB-C and how to interpret the similarities and differences among these corpora. Do the similarities that distinguish the Levantine figurines from those of other regions indicate a widespread diffusion of similar praxis across Levantine religion? Do the unique features of figurine design, technology, and deposition that demarcate the corpora of one Levantine state from another provide evidence for a “religion of place” on a more local scale? How should scholars approach iconographic similarities when interpreting the use and function of figurines in different locales? In an attempt to address these questions, this paper uses Levantine composite female terracotta figurines as a test case to explore the way archaeological data both support and impede a geographically contextualized approach to religious praxis. Full article