bluuebunny/crossref_metadata_2025_split huggingface dataset:
Textbook Selection in Nursing Education: An Updated Perspective
Authors: Anderson Judy K. , Downing Lucille , Heitman Susan , Heiser Vickie R. , Rauch Linda J. 
Published: January 2025

Background:
Evidence-based guidelines about textbook selection for nursing didactic courses are lacking. Therefore, this study explored the priorities of faculty in baccalaureate nursing programs for selecting primary textbooks.

Purpose:
The study aimed to identify the ranking of essential characteristics in nursing textbooks, including content, general characteristics, supplemental resources, organization, and specific considerations about electronic textbooks.

Methods:
Using a cross-sectional design, a descriptive survey was conducted among faculty members across the United States.

Results:
Results from 59 faculty participants demonstrated a strong preference for textbooks emphasizing clinical judgment and application to practice, with content being the top priority. Additionally, instructor resources, such as test banks and teaching strategies, were prioritized within supplemental resources. Few participants reported formal training in textbook selection, indicating a potential area for nursing education improvement.

Conclusions:
The study found the need for further research and development of structured guidelines to aid in the textbook selection process.
Prevalence and incidence of HPV-related dysplasia of oropharyngeal, cervical, and anal mucosae in Spanish people living with HIV (PLHIV)
Authors: Hidalgo-Tenorio Carmen , Calle-Gómez Inmaculada , Moya Raquel , Omar Mohamed , Lopez-Hidalgo Javier , Rodriguez-Granges Javier , Muñoz Leopoldo , García-Martinez Carmen 
Published: January 2025

Background:
Objectives were to determine the prevalence/incidence of HPV-related dysplasia and clearance/acquisition rates of high-risk HPV (HR-HPV) genotypes in genital mucosa of women-LHIV and oropharyngeal and anal mucosa of PLHIV and to evaluate factors related to HR-HPV infection in oropharyngeal mucosa at 12-months.

Material and methods:
Prospective, longitudinal study with 12-month follow-up, enrolled PLHIV between December 2022 and April 2023. At baseline and 12-months, HIV-related clinical and analytical variables were recorded, oropharyngeal mucosa exudates were taken for polymerase chain reaction (PCR) studies for HPV and other sexually transmitted infections, while anal and female genital samples were self-sampled for HPV detection and genotyping by PCR and thin-layer cytology.

Results:
276 PLHIV with mean age of 45.3 years, 79% male, 24.3% with history of AIDS, 100% under ART, and 30.1% with completed HPV vaccination. HPV infection prevalence in oropharyngeal mucosa was 11.6% at baseline, most frequently by genotype 16 (2.2%), without dysplasia. No oropharyngeal dysplasia was observed at 12 months, and HR-HPV clearance and acquisition rates were 5.5% and 4.4%, respectively. Incidence of anal HSIL was 1,811.6 casesx100,000 people-year, and HR-HPV clearance and acquisition rates were 16.2% and 25.6%, respectively. Incidence of CIN2/CIN3 or cervical cancer was zero, and HR-HPV clearance and acquisition rates were 11.3% and 7.5%. HIV-RNA viral load <50 cop/mL protected against HPV infection in oropharyngeal mucosa (97.2 vs. 87%, HR 0.044; 95%CI [0.042 – 0.956]).

Conclusions:
Among PLHIV, HSIL incidence and HR-HPV acquisition rate are higher in anal versus oropharyngeal and genital mucosae. Non-detectability protects against oropharyngeal HPV infection.
Ultraviolet B Induces Cutaneous Lupus Erythematosus by Triggering a Ribotoxic-Stress-Response-Dependent MIF-p38 Feedback Loop in Keratinocytes
Authors: Guo Chipeng , Luo Siweier , Luo Jigang , Lv Haoran , Zhang Yating , Wang Le , Wang Liangchun , Liu Tao , Zhou Yiming 
Published: January 2025

AbstractUltraviolet B (UVB) is one of the most common triggers of cutaneous lupus erythematosus (CLE), but the mechanism is still unclear. Here, we discovered that the expression of macrophage migration inhibitory factor (MIF), a multipotent cytokine, was significantly increased in keratinocytes of lupus patients in scRNA-seq data and clinical samples. We further discovered that UVB exposure induced MIF releasing from lupus keratinocytes and contributed to the tissue remodeling and inflammation by regulating the expression of matrix metalloproteinases (MMPs) and pro-inflammatory cytokines in keratinocytes and fibroblasts. Mechanistically, UVB exposure triggered a ribotoxic stress response (RSR) in lupus keratinocytes, which was featured by the increased level of phospho-ZAKα. The RSR induced MIF releasing through the activation of p38 and GSDMD cleavage. The released MIF could further promote the activation of p38 through its receptor CD74, forming a positive feedback loop triggered by UVB exposure in lupus keratinocytes. Intradermal injection of a Mif-shRNA AAV significantly improved the skin lesions in lupus mice. To further investigate the potentials of MIF as a therapeutic target, we developed a microneedle patch capable of intradermal administration of a MIF inhibitor, which effectively protected lupus mice from skin lesions induced by UVB exposure. In conclusion, our findings suggest a novel mechanism by which UVB exposure contributes to the development of CLE by triggering a positive feedback loop of MIF-p38 in lupus keratinocytes. Our results also demonstrate the translational potentials of microneedle patch targeting MIF in the treatment of CLE.
Exploring new Bacteroidota strains: Functional Diversity and Probiotic Characteristics
Authors: Ladewig Lisa , Tufail Muhammad Aammar , Kinfu Birhanu M. , Fokt Hanna , Baines John F. , Schmitz Ruth A. 
Published: January 2025

AbstractBacteroidota, a diverse phylum of bacteria, are increasingly recognized for their significant contributions to host health, particularly through their antimicrobial and probiotic properties. This study investigates the functional diversity and probiotic potential of 42 new Bacteroidota strains enriched and identified from diverse hosts, including mouse ceca and human stool samples. Using 16S rRNA gene sequencing, we phylogenetically characterized the strains of the genera Bacteroides, Phocaeicola and Sphingobacterium and assessed their functional properties related to probiotic potential. The strains were evaluated concerning their ability to inhibit biofilm formation of WHO declared clinically significant pathogens, including gram-positiveStaphylococcus aureusandStaphylococcus epidermidis, gram-negativeKlebsiella oxytocaandPseudomonas aeruginosa, and the eukaryotic fungusCandida albicans.Additionally, we investigated bile salt hydrolase and quorum quenching activities of the strains, key traits associated with probiotic efficacy. Our findings demonstrate that all examined Bacteroidota strains consistently exhibit a capacity to inhibit biofilm formation but to different extent. Furthermore, 14 strains showed quorum quenching activity, and 39 bile salt hydrolase activity, highlighting their probiotic potential. High biofilm inhibition as well as quorum quenching activity against both autoinducers, AHL and AI-2, were predominantly observed inBacteroides caecimurisandBacteroides muris, making them attractive candidates for next-generation probiotics. Overall, this study advances the field of next-generation probiotics by identifying promising candidates for therapeutic applications potentially revolutionizing approaches to microbiome-based interventions and pathogen control in clinical settings.
An explainable artificial intelligence framework reveals mutations associated with drug resistance inMycobacterium tuberculosis
Authors: Cen Hui , Zhang Peng , Ling Yunchao , Zhao Guoping , Zhang Guoqing 
Published: January 2025

AbstractUnderstanding the mechanisms of drug resistance inMycobacterium tuberculosis(MTB) is essential for the rapid detection of resistance and for guiding effective treatment, ultimately contributing to reducing the global burden of tuberculosis (TB). Under anti-TB drugs pressure, MTB continues to accumulate resistance loci. The current repertoire of known resistance-associated mutations requires further refinement, necessitating efficient methods for the timely identification of potential resistance sites. Here, we introduce xAI-MTBDR, an explainable artificial intelligence framework designed to identify new resistance-associated mutations and predict drug resistance in MTB. It outperforms state-of-the-art methods in predicting drug resistance for all first-line drugs, and scoring each mutation’s contribution to resistance. By leveraging public whole-genome sequencing data from nearly 40,000 MTB isolates, the framework identified 788 candidate resistance-related mutations and revealed 30 potential resistance markers, several of which are structurally located closer to their respective drugs compared to known resistance mutations. Furthermore, these scores enabled the framework to efficiently subgroup isolates with different resistance mechanisms and reflect varying levels of resistance. The framework serves as a valuable tool for accurate detection of drug-resistant MTB and offers new insights into its underlying mechanisms.
A novel human blood-brain barrier model reveals pericytes as critical regulators of viral neuroinvasion
Authors: Richards Alexsia , Khalil Andrew , Bisht Punam , Whitfield Troy W. , Gao Xinlei , Kamm Roger , Mooney David , Gehrke Lee , Jaenisch Rudolf 
Published: January 2025

AbstractThe blood-brain barrier (BBB) plays a vital role in regulating the passage of biomolecules between the bloodstream and the central nervous system (CNS) while also protecting the CNS from pathogens. Pericytes reside at the interface between the endothelial cells that form the vessel walls and the brain parenchyma. These cells are critical for maintaining BBB integrity and play key roles in regulating vessel permeability, blood flow, and immune cell migration. In this study, we developed a novel serum-free protocol to generate neural crest cell-derived pericytes (NCC-PCs) from human pluripotent stem cells (hPSCs). These NCC-PCs enhance BMEC barrier function and can be co-cultured with hPSC-derived brain microvascular endothelial cells (BMECs) in a contact co-culture BBB model that recapitulates thein vivocellular interactions at the BBB. We used this model to evaluate the pathological consequences of BBB cell infection by highly neuroinvasive flaviviruses. Our results identify a previously undescribed role for NCC-PCs in maintaining BMEC barrier integrity during infection and reducing the spread of viral infection to the CNS.
Visual experience contributes to separation of face and language responses in the ventral stream
Authors: Saccone Elizabeth J. , Akshi  , Murty N. Apurva Ratan , Kim Judy S. , Tian Mengyu , Kanwisher Nancy , Bedny Marina 
Published: January 2025

SummaryHuman ventral occipitotemporal cortex (vOTC) contains specialized regions that support visual recognition of behaviorally-relevant categories, including faces, written language and places (e.g.,1–4). An open question is how experience interacts with innate constraints to enable functional specialization. We investigate this question by comparing vOTC function across sighted and congenitally blind adults. In sighted adults, a region in lateral vOTC called the fusiform face area (FFA) responds preferentially to faces, whereas distinct left-lateralized portions of vOTC respond to written language1,2,5–12. In blind people, lateral vOTC responds to face touching, braille and speech, but their functional co-localization has not been tested13–16. The same group of congenitally blind adults (n=20) touched faces and spatial layouts (Experiment 1) and performed a reading (braille) and spoken language task (Experiment 2). Sighted adults performed analogous tasks in the visual modality (n=28). Using within subject analyses, we replicate the separation of faces and written language in sighted adults: written language responses are found only in left vOTC and within that hemisphere they are separate from faces. By contrast, left and right vOTC responds to language in people born blind and in the left hemisphere face and language responses overlap. These findings suggest that visual experience contributes to segregating responses to face and language in vOTC. Co-localization of face and language responses suggests an innate predisposition for communication-relevant processing in lateral vOTC.
Long-Term Seizure Reduction Associated with Vagal Nerve Stimulation in Dravet Syndrome
Authors: Bajaj Sunanjay , Ivaniuk Alina , Bruenger Tobias , Coelho Da Silva Émile Moura , Huth Emily , Montanucci Ludovica , Leu Costin , Taylor Gary , Sinha Mousumi , Tai Rahil A. , Shah Manish N. , Watkins Michael W. , Lankford Jeremy E. , Kommuru Indira M. , Pati Sandipan , Kotagal Prakash , Alexopoulos Andreas , Lhatoo Samden D. , Knight Elia Pestana , Von Allmen Gretchen , Lal Dennis 
Published: January 2025

AbstractSCN1Avariants cause a range of epilepsy syndromes, including Dravet syndrome, leading to early cognitive and functional impairment. Despite advances in medical management, drug-resistant epilepsy remains common. Vagal nerve stimulation (VNS) has been suggested reducing seizure frequency in these patients but there is a lack of long-term follow-up, quantitative analysis that corrected for confounding factors such as antiseizure medications (ASMs) and the impact of VNS settings on response.This two-center, retrospective cohort study analyzed 12-month and for the first time up to ten-year seizure outcomes in therapy-refractory epilepsy patients with loss-of-functionSCN1Avariants (93.75% Dravet Syndrome) who underwent VNS implantation. A ≥50% seizure frequency reduction was observed in 93.75% (15/16) of patients in the 12-month and 87.5% (14/15) in the ten-year period. Median seizure frequency was significantly lower in both follow-up periods than in the pre-implantation period. Linear mixed-effects regression showed that the reduction in seizure burden was independent of ASM use, and the VNS duty cycle was significantly associated with seizure reduction. Three individuals (18.8%) experienced minor side effects.Our results highlight the benefits of genotype-driven therapeutic interventions such as VNS in patients withSCN1A-related epilepsy. This study emphasizes the need for further implementation of genotype-driven clinical decision-making.
The Dynamics of Cognitive Decline towards Alzheimer’s Disease Progression: Results from ADSP-PHC’s Harmonized Cognitive Composites
Authors: Kang Kaidi , Zhang Panpan , Dumitrescu Logan , Mukherjee Shubhabrata , Lee Michael L. , Choi Seo-Eun , Trittschuh Emily H. , Mez Jesse , Saykin Andrew J. , Gifford Katherine A. , Buckley Rachel F. , Gao Xiaoting , Di Jianing , Crane Paul K. , Hohman Timothy J. , Liu Dandan 
Published: January 2025

AbstractINTRODUCTIONAccurately assessing temporal order of cognitive decline across multiple domains is critical in Alzheimer’s disease (AD). Existing literature presented controversial conclusions likely due to the use of a single cohort and different analytical strategies.METHODSHarmonized composite cognitive measures in memory, language and executive functions from 13 cohorts in the ADSP-PHC data are used. A novel double anchoring events-based sigmoidal mixed model was developed using time to the incident of AD diagnosis as the time scale.RESULTSDecline in memory occurred before decline in language which was followed by the decline in executive function. Throughout the entire AD continuum, APOE-ε4 non-carriers and non-Hispanic Whites showed better memory performance, respectively, in all three cognitive domains.DISCUSSIONUsing harmonized data across multiple cohorts is the key to accurately characterizing the temporal order of AD biomarkers. Time to incident AD diagnosis should be used as the time scale for reproducibility purposes.
ICU Readmission Prediction for Intracerebral Hemorrhage Patients using MIMIC III and MIMIC IV Databases
Authors: Li Hexin , Monger Rachel , Pishgar Elham , Pishgar Maryam 
Published: January 2025

ABSTRACTBackgroundIntracerebral hemorrhage (ICH) is a critical form of stroke resulting from bleeding within the brain, with a mortality rate of 40-50% within a few days and significant risk of long-term disability. Despite the high incidence of ICU readmissions among ICH patients, the specific factors contributing to these readmissions remain unclear. This study utilizes MIMIC-III and MIMIC-IV databases to develop machine learning models that predict ICU readmissions in ICH patients.MethodsData from 2,144 patients were extracted using ICD-9 and ICD-10 codes. Four machine learning models - AdaBoost, Random Forest, XGBoost, and LightGBM - were implemented. Recursive Feature Elimination with Cross-Validation reduced features from 50 to 18 key predictors. The RandomUnderSampler technique addressed class imbalance by reducing majority class samples to 60% of the minority class, while the Optuna framework with Tree-structured Parzen Estimator optimized model parameters. Performance was primarily evaluated using AUROC, which effectively handles class imbalance and provides threshold-independent assessment, complemented by accuracy, sensitivity, and specificity metrics.ResultsThe AdaBoost model achieved an AUROC of 0.877 (95% CI: 0.815-0.913) and accuracy of 0.810, improving from the previous best AUROC of 0.736. Sensitivity notably increased from 22.6% to 84.0%, demonstrating substantial improvement in identifying high-risk patients. This enhancement resulted from effective class imbalance handling and AdaBoost’s adaptive weighting mechanism. Through comprehensive SHAP and ablation analyses, we identified oxygen saturation and cardiovascular disease as crucial predictive features for ICU readmission risk assessment, providing new insights into patient monitoring and care management.ConclusionsOur preprocessing methodology and model selection strategy significantly improved high-risk ICH patient identification. Through comprehensive improvements combining advanced hyperparameter optimization, balanced sampling techniques, and dual feature importance analysis, we achieved a 19.2% AUROC improvement while reducing feature dimensionality from 51 to 18. This integrated approach demonstrates the potential of machine learning in enhancing clinical decision-making. The framework provides a promising foundation for developing clinical decision support tools in ICU settings, improving resource allocation and enabling more personalized patient care interventions.
Comprehensive cerebrospinal fluid analysis indicates key roles for B cells in multiple sclerosis
Authors: Fernández-Zapata Camila , Otto Carolin , Gallaccio Gerardina , Chen Qianlan , Wang Meng , Uluvar Burulça , Teves Matteo , Samol Claudia , Buthut Maria , Bösl Fabian R. , Dehlinger Adeline , Jang GueHo , Böttcher Christian , Radbruch Helena , Priller Josef , Schindler Patrick , Raposo Catarina , Shippling Sven , Pedotti Rosetta , Kunkel Desiree , Pietzner Maik , Franke Christiana , Oefner Peter J. , Gronwald Wolfram , Prüß Harald , Lohmeier Johannes , Paul Friedemann , Ruprecht Klemens , Böttcher Chotima 
Published: January 2025

AbstractMultiple sclerosis (MS) is a complex inflammatory and neurodegenerative disease of the central nervous system (CNS) with a multifaceted pathophysiology, likely involving a variety of mechanisms and effectors. To characterize the spectrum of cellular and molecular factors involved in MS at an unprecedented level, we here performed a comprehensive analysis of cerebrospinal fluid (CSF) and peripheral blood using multiple high-dimensional technologies, including mass cytometry, metabolomics and proteomics (NULISA and Olink Explore®3072). Enriched B cells and proteins involved in B cell functions in the CSF separated MS patients from other neurological disease entities. Specific B cell subpopulations and molecular markers including gut-microbiota-derived metabolites and neurofilament light protein, a marker of neuroaxonal damage, in CSF correlated with clinical (acute vs. stable disease) and/or radiological (gadolinium enhancement) disease activity. Altogether, unbiased broad phenotyping suggests key roles of diverse B subpopulations and B cell related molecular markers in MS, which are associated with both, inflammatory and degenerative aspects of the disease and may serve as disease activity and treatment response biomarkers.
Actinobacteriophage Inteins: Host Diversity, Local Dissemination, and Non-Canonical Architecture
Authors: Gosselin Sophia P. , Arsenault Danielle , Gogarten Johann Peter 
Published: January 2025

AbstractIntein presence within Actinobacteriophages (within PhagesDB) was last surveyed in 2016, and despite a 5-fold increase in the size of the database, has not been updated since. To address this, we present a modern survey of the current iteration of the PhagesDB database. We developed a new algorithm — Iterative Cluster Expansion BLAST (ICE-BLAST) — to expand our search to more divergent sequences. Nearly 800 inteins were retrieved through this process; the majority of which were previously unreported. We describe the nature of these inteins, their classes, integration target sites, distribution within phage clusters, and explore the geographical location of nearly identical intein sequences found in divergent exteins. Our findings suggest that these inteins recently invaded local phage populations. We also find two instances of a Cas4 exonuclease intein evolving from a terminase intein, and propose a model by which one of these inteins was able to utilize sequence similarity conferred by a shared nucleotide binding site to jump between genes. Additionally, we find inteins with never-before reported homing endonucleases, and inteins with homing endonucleases encoded in a reading frame separate from that which encodes the extein and the intein’s self-splicing domains. We provide predicted structures for these elements and hypothesize on their evolution and relation to free-standing homing endonucleases within phage genomes. Finally, we provide evidence that these “non-canonical” inteins are still transferring between host genomes, in a fashion similar to other inteins with canonical homing endonucleases within the dataset.
Computational Fluid Dynamics (CFD) Modeling of Ilamycin E Production inStreptomyces atratusSCSIO ZH16 Submerged Fermentation
Authors: Zhou Weiyan , Zheng Gaofan , Wang Jialuo , Xin Xiujuan , Zhuang Liwei , An Faliang 
Published: January 2025

AbstractA computational fluid dynamics (CFD) model was developed and validated against experiments for a laboratory-scale 5-L bioreactor. Numerical simulation was performed to describe the bioreaction ofStreptomyces atratusSCSIO ZH16 fermentation for ilamycin E production with the dynamic changes in viscosity of the fermentation broth due to biomass growth and decay. This model can account for the two-way coupling between the fermentation environment and medium, which allowed for the elucidation of the impact of the flow field in the bioreactor on bacterial growth and production, as well as the influence of viscosity changes on the flow field. This work represents the first integration of Streptomyces fermentation with CFD, enabling the simulation of flow field and mass transfer under varying stirring speed, aeration rate, and viscosity duringStreptomycesfermentation. An optimum range of fermentation broth viscosity (10-30 mPa s) was identified for ilamycin E production byS.atratusSCSIO ZH16 fermentation. Furthermore, the addition of sorbitol to optimize the viscosity of the fermentation broth in the later stages of fermentation. The enhanced mass transfer efficiency strengthens the respiration, energy supply, and carbon source consumption inStreptomyces, thereby increasing the ilamycin E production. This research offers a practical strategy for the process intensification and industrial scale-up for such bioreactors.Graphical abstract