To develop and empirically characterize a domain-specific, block-structured annotation schema and an expert-annotated reference corpus for German-language head and neck squamous cell carcinoma (HNSCC) pathology reports.

Yam virus X (YVX; Potexvirus ecsdioscoreae) is a positive-sense, flexuous RNA virus belonging to the family Alphaflexiviridae. It has been first reported from Guadeloupe, a French archipelago located in the Caribbean Sea. In this study, we investigated the virome in yam (Dioscorea spp.) plant material collected in the state of Bahia (Brazil) by high-throughput sequencing (HTS) on Illumina platform. The objective of the investigation was to explore the occurrence of YVX in yam from South America, and to study its genetic diversity compared to the only one YVX genome sequence available in the GenBank public database.

This study aimed to investigate the occurrence, antimicrobial resistance profiles, and genetic characteristics of extended-spectrum beta-lactamase (ESBL)-producing E. coli in wastewater collected in Dakar, Senegal.

The recent integration of artificial intelligence (AI) into academia could usher in transformative efficiencies across scholarly workflows-from manuscript drafting to data analysis-yet it also presents problematic ethical challenges that urgently require intense attention. While some surveys suggest that over 50% of researchers employ AI chatbots like ChatGPT and DeepSeek for tasks such as language refinement and administrative coordination, their adoption raises potential concerns about cognitive dependency, systemic bias, and accountability gaps. AI tools can enhance productivity by automating repetitive tasks, democratizing access for non-native English speakers, and streamlining literature synthesis. However, reliance on these systems could gradually erode critical thinking skills, particularly among early-career researchers pressured to prioritize publication quantity over rigor. Ethical ambiguities seem to persist: AI-generated content may complicate authorship norms, potentially entrench biases against Global South scholarship, and introduce risks of misinformation. Transparency deficits could further undermine trust, as undisclosed AI use might compromise peer review integrity and patient privacy in medical research. To balance innovation with ethical imperatives, this study advocates a tripartite framework: [1] ethical governance, including mandated disclosure of AI contributions and inclusive dataset curation to mitigate bias; [2] symbiotic human-AI collaboration, preserving human oversight in critical analysis and interpretation; and [3] equitable innovation, leveraging AI to bridge global research disparities. Unresolved challenges-such as accountability for AI errors and the potential cognitive consequences of prolonged dependency-appear to underscore the urgent need for global standards to clarify liability and preserve academic rigor while fostering equitable innovation. Proactive engagement from journals, institutions, and developers may be essential to ensure AI augments, rather than undermines, the integrity and equity of scholarly ecosystems.

Datasets for automatic analysis of laryngeal endoscopic images are scarce, particularly those providing detailed anatomical annotations beyond the glottal area. The BAGLS dataset previously introduced a large collection of laryngoscopic images with expert annotations of the glottal area. To facilitate research on more detailed anatomical modeling and segmentation tasks, we introduce BAGLS-VF, an extension of the BAGLS dataset that includes additional annotations of the left and right vocal folds.

Urine collection from neonates can be difficult. We therefore designed a study to compare success rates and effectiveness of different urine collection methods in neonates.

SSR markers are used for a myriad of genetic analyses, such as genotyping, parentage analysis or genetic structure, due to their high polymorphism, co-dominance and genomic ubiquity. Most downstream analysis tools usually require a diploid dataset but some plant species may have higher ploidy levels or there may be genotypes within the species that differ in ploidy level. Additionally, SSR markers can show multi-locus behaviour and are prone to genotyping errors. Consequently, existing analysis tools often do not meet the requirements of plant datasets. Nevertheless, accurately estimating genetic diversity parameters remains essential, even for polyploid datasets. This emphasizes the importance of adapting such datasets appropriately to enable subsequent analysis while preserving their biological validity.

Hepatitis A virus (HAV) causes acute hepatitis through ingestion of contaminated food and water, with bivalve molluscs as common vehicles of transmission. As filter feeders, HAV concentrates in their digestive tissues when grown in contaminated waters. In 2020, the Philippines produced nearly 75 MT of shellfish. However, maintaining proper sanitation in growing areas remains challenging, and data on the occurrence of HAV in these commercially significant shellfish is lacking. This study aimed to detect HAV in Philippine cupped oysters (Magallana bilineata), green mussels (Perna viridis), and seawater from their growing areas. Samples were collected in Pangasinan (August 2022), Cavite (April 2023), and Capiz (June 2023), and HAV detection was conducted using quantitative reverse transcription polymerase chain reaction (RT-qPCR).

Recently, deep learning models in medical imaging have undergone tremendous advancements. However, these deterministic discriminative models often tend to overfit and produce overconfident predictions. To explore a more efficient strategy, we propose a diffusion-conditioned representation learning that leverages the internal dynamics of a diffusion model to extract noise-level awareness and diverse semantic representations in disease classification and detecting distributional shifts. The proposed method inherently encodes aleatoric uncertainty by sampling features from multiple denoising time steps, which is then used to regularize prediction during training via entropy regularized loss.

Canine distemper virus (CDV) is a pathogen that causes systemic infection in dogs and wildlife. Among the highly variable regions in the genome of the virus, the H gene is commonly sequenced for phylogenetic studies. The aim of the present study was to screen for the presence of CDV infection in dogs in Iran and to identify the genotype of the virus. Seventy-five dogs with gastrointestinal symptoms were screened via an immunochromatographic test. Fifty of them were positive. CDV was isolated from rectal swabs, and PCR was performed. The top 10 positive cases were subsequently selected for sequencing. Phylogenetic analyses were subsequently conducted. Among the 75 dogs analyzed, 50 (66.7%) dogs were found to be infected with CDV via rapid tests. All 10 sequenced isolates were from the Arctic lineage, forming a monophyletic cluster. Our sequences closely clustered with some European strains. Some nucleotide variations were observed. The present study reports the presence of Arctic-like CDV strains in diarrheic dogs in Tehran. Ongoing molecular surveillance will help in assessing any alterations in genetic diversity and vaccine efficacy. Future studies in other regions in Iran would be helpful.

This study examined whether feeling thermometer ratings toward older adults vary across older-adult subgroups and how such ratings are positioned relative to other common prejudice targets. Using an online sample of 520 Japanese adults aged 18-64, we assessed feeling thermometer ratings (0 = coldest, 100 = warmest) for 14 targets: nursing-home, on-deathbed, handicapped, solitary, senile, on-welfare, and grumpy older adults, as well as immigrants and refugees, foreign tourists, sexual minorities, racial minorities, and persons with mental, physical, or intellectual disabilities. We also tested whether these evaluations differed by participants' age group (younger and middle-aged adults).

Motivational orientation and immersive tendency describe complementary questionnaire-based dimensions of player characterization. Motivation instruments capture why players report engaging with games, whereas immersive-tendency instruments describe individual predispositions toward absorption, involvement, and attention focusing in mediated environments. To support reuse in questionnaire-based player modelling, we created an open, item-level, single-cohort survey dataset linking Bartle Test responses, ITQ-18 responses, demographics, and self-reported gaming preferences among IT students and teachers.

Lichen planus (LP) is a chronic inflammatory condition that can have systemic implications, including effects on vascular health. This exploratory study aimed to evaluate orbital hemodynamics and vascular changes in patients with mucosal LP using color Doppler ultrasound (CDU).