bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sensitivity of M2tidal magnetic signals to seasonal and spatial variations of ocean electric conductivity
Authors: Velímský J. , Šachl L. 
Published: December 2024

Electrical conductivity of the Earth’s oceans is an important oceanographic parameter related through its dependence on temperature and salinity to the state of the ocean. The tidally induced magnetic field then provides a directly and globally observable physical variable affected by the ocean conductivity spatial and temporal distribution. This contribution addresses two topics of the impact of the ocean conductivity variations on the principal lunar semi-diurnal magnetic signals. First, using high-resolution forward modelling, we investigate the sensitivity of the magnetic field to seasonal conductivity variations. Here, we find that the differences between magnetic signatures calculated for individual monthly conductivity climatologies are small, and localized to the marginal seas of the global ocean. Second, we formulate an inverse method to provide a constraint for the ocean conductivity in the upper 1000 m of the ocean, and test it using a synthetic dataset, demonstrating a proof-of-concept for such an approach.This article is part of the theme issue ‘Magnetometric remote sensing of Earth and planetary oceans’.
Molecular characterization of enteroviruses circulating among pigs and goats in two Central African countries, Cameroon and the Central African Republic.
Authors: MODIYINJI Abdou Fatawou , JOFFRET Marie-Line , NOMBOT-YAZENGUET Marina Prisca de Marguerite , ENDENGUE ZANGA Marie-Claire , SADEUH-MBA Serge , NJOUOM Richard , Bessaud Mael 
Published: December 2024

To date, data on animal enteroviruses (EVs) are scarce, especially in Central Africa. The aim of this study was to characterize EVs among pigs and goats in Cameroon and Central African Republic. A total of 226 pig and goat faecal samples collected in two previous studies carried out in Cameroon and CAR were pooled and were screened with molecular assays targeting EV-Es, EV-Fs and EV-Gs. EV genomes were amplified by RT-PCR and their sequences obtained by Illumina sequencing and de novo assembly. Based on the capsid sequences, 27 EV-G sequences were identified and assigned to 11 virus types while no EV-E or EV-F was observed. Phylogenetic analysis revealed that the EV-Gs detected in Central Africa do not form specific cluster compared to EV-Gs previously reported in other continents. This suggests a worldwide circulation of EV-Gs, which is likely due the massive international trade of live animals. One human EV, EVC-99, which belongs to the species Enterovirus C, was detected in pigs. This is the third detection of such an event in a similar context, reinforcing the hypothesis that some EV-Cs could be infecting pigs. Our work provides new data on the genetic diversity of EVs circulating among domestic animals in Central Africa.
Transformer-based long-term predictor of subthalamic beta activity in Parkinson’s disease
Authors: Falciglia Salvatore , Caffi Laura , Baiata Claudio , Palmisano Chiara , Isaias Ioannis Ugo , Mazzoni Alberto 
Published: November 2024

AbstractDeep brain stimulation (DBS) of the subthalamic nucleus (STN) is a mainstay treatment for patients with Parkinson’s disease (PD). The adaptive DBS approach (aDBS) modulates stimulation, based on the power in the beta range ([12 30] Hz) of STN local field potential, aiming to follow the patient’s clinical state. Control of aDBS relies on identifying the correct thresholds of pathological beta power. Currently, in-person reprogramming sessions, due to changes in beta power distribution over time, are needed to ensure clinical efficacy. Here we present LAURA, a Transformer-based framework predicting the nonlinear evolution of subthalamic beta power up to six days in advance, based on the analysis of chronic recordings. High prediction accuracy (>90%) was achieved in four PD patients with chronic DBS over months of recordings, independently from stimulation parameters. Our study paves the way for remote monitoring strategies and the implementation of new algorithm for personalized auto-tuning aDBS devices.
A-tDCS over DLPFC is no more effective than placebo in improving cognition and pain-experience in chronic lower back pain
Authors: Corti Emily J. , Marinovic Welber , Nguyen An T. , Gasson Natalie , Loftus Andrea M. 
Published: November 2024

AbstractChronic pain is associated with deficits in cognitive functioning and increased pain intensity. Research investigating the potential for transcranial direct current stimulation (tDCS) to improve cognitive functioning, pain experience, and psychological health in individuals with chronic lower back pain (CLBP) yield mixed results. The present randomised, placebo-controlled study examined the impact of anodal-tDCS over left-dorsolateral prefrontal cortex (left-DLPFC) on cognitive functioning, pain experience, and psychological health in those with CLBP. Thirty participants with CLBP (Mage = 57.47 years, SDage = 14.28 years) received 20-minutes of sham or anodal tDCS, twice weekly, for 4 weeks. Cognitive functioning was assessed using two measures for each of the five cognitive domains; memory, attention and working memory, executive function, visuospatial, and language. Cognition, pain experience, and psychological health were assessed prior to and immediately following the tDCS intervention. Linear Mixed Models revealed a significant tDCS group and time interaction on an attention and working memory task, whereby participants in the a-tDCS showed a significant improvement on the letter number sequencing task at post-intervention. There was a significant main effect of time for both tDCS groups across the five cognitive domains. Both groups demonstrated a significant improvement on at least one measure for each of the five cognitive domains. Linear Mixed Models revealed there was a significant main effect of time for both tDCS groups on pain intensity, disability, catastrophising, anxiety, and stress, whereby both groups demonstrated a significant reduction on these outcome measures. There was a significant main effect of time for both tDCS groups on quality of life, whereby both groups demonstrated a significant improvement in quality of life. There was no significant main effect of tDCS group or interaction between tDCS group and time on pain intensity, disability, catastrophising, anxiety, stress, and quality of life. These findings suggest anodal-tDCS over left-DLPFC is no more effective than sham-tDCS in improving cognition, pain experience, and psychological health in those with CLBP.
Impact of Medical Cannabis Treatment on Healthcare Utilization in Patients with Post-traumatic Stress Disorder: A Retrospective Cohort Study
Authors: Doucette Mitchell L. , Macfarlan D. Luke , Kasabuski Mark , Chin Junella , Fisher Emily 
Published: November 2024

AbstractIntroductionMedical cannabis is increasingly used as a therapy for managing post-traumatic stress disorder (PTSD). Patients with PTSD often have high healthcare utilization rates, particularly for acute services. This study examines the association between medical cannabis treatment and healthcare utilization among patients with PTSD.MethodsWe conducted a retrospective cohort study using cross-sectional data with tem-poral elements, derived from administrative records provided by Leafwell, among patients with PTSD. The cohort was defined based on medical cannabis use: the treated group included patients who had used medical cannabis for at least one year (returning for medical card renewal), while the untreated group consisted of cannabis-naive patients reporting no prior cannabis use. The primary outcomes were healthcare utilization within the past six months, including at least one urgent care visit, emergency department (ED) visit, or hospitalization related to their primary medical condition. We used inverse probability weighting with regression adjustment (IPWRA) to estimate the average treatment effect (ATE) of medical cannabis use on healthcare utilization, controlling for key demographics and health factors, including PTSD severity. Sensitivity analyses were conducted to assess the robustness of our findings.ResultsAmong the 1,946 participants, the treated group (n = 1,261) had significantly lower healthcare utilization rates compared to the untreated group (n = 685). Using the doubly robust IPWRA model, medical cannabis treatment was associated with a significant 35.6% reduction in urgent care visits (coefficient = -0.024, Standard Error (SE) = 0.0117) and a 35.1% reduction in ED visits (coefficient = -0.027, SE = 0.0124). Hospitalization rates were 26.3% lower among the treated group but did not reach statistical significance. Sensitivity analyses utilizing alternative ATE estimation strategies displayed consistent reductions in urgent care and ED visits among cannabis users, though hospitalizations remained non-significant. Adjusting the IPWRA model’s tolerance levels strengthened the found associations while maintaining strong covariate balance. Fewer than 2% of the treated group reported an adverse event.DiscussionThese findings suggest that medical cannabis treatment among patients with PTSD may be associated with reduced utilization of urgent care and ED services. This relationship remains robust across multiple statistical models and sensitivity analyses, underscoring the potential role of medical cannabis in reducing acute healthcare needs in this population. Further longitudinal research is warranted to explore causality and assess its impact on hospitalization rates.
Sleep Quality Mediates the Relationship Between Sleep Hygiene and Psychological Stress Among Adults With Multiple Cardiovascular Risk Factors
Authors: Liu Xiaoyue , Li Junxin , Hu Jinyu , Fletcher Jason , Commodore-Mensah Yvonne , Himmelfarb Cheryl R. 
Published: December 2024

ABSTRACTBackgroundPoor sleep quality and psychological stress are interrelated and disproportionately affect adults with multiple cardiovascular disease (CVD) risk factors. Maintaining an optimal home environment and engaging in healthy bedtime behaviors are important components of sleep hygiene practices that influence sleep health and mental well-being. However, research is scarce in exploring the associations between sleep hygiene, sleep quality, and psychological stress among adults with multiple CVD risk factors.MethodsA cross-sectional study was conducted with 300 adults diagnosed with hypertension and type 2 diabetes. Individuals were recruited from a large academic health center and were asked to complete an online survey. Sleep hygiene was assessed by nine individual factors focusing on negative household environment (safety, physical comfort, temperature, and light) and poor bedtime behaviors (watching TV, playing video games, using small screens, and eating) and by a composite score. Multiple regression and mediation analysis with bootstrapping were employed to examine the associations.ResultsOf the sample, 78% reported poor sleep quality and 44% reported high psychological stress. Individual sleep hygiene factors as well as the composite score were significantly associated with poorer sleep quality and higher psychological stress. Sleep quality mediated the association between the composite score and psychological stress (Indirect effect: 0.16; 95% bootstrap confidence interval: 0.04-0.35).ConclusionsThe study highlights strong links between sleep hygiene, sleep quality, and psychological stress. Although causality cannot be established, current evidence suggests that promoting home environment and bedtime behaviors may alleviate sleep and psychological burdens in adults with multiple CVD risk factors.CLINICAL PERSPECTIVEWhat Is New?Adults with hypertension and type 2 diabetes often experience poor sleep quality and elevated psychological stress.Room environment and bedtime behaviors are important components of sleep hygiene practices that strongly associate with sleep quality and mental well-being.Sleep quality may serve as a mediating factor between sleep hygiene and psychological stress.What Are the Clinical Implications?Enhancing room environment and bedtime behaviors is crucial for adults with multiple cardiovascular disease risk factors.Given the crucial roles of both sleep and psychological stress in cardiovascular health, promoting modifiable sleep hygiene practices may be an effective strategy to mitigate health risks in this population.
Structure and organization of full-length Epidermal Growth Factor Receptor in extracellular vesicles by cryo-electron tomography
Authors: Gonzalez-Magaldi Monica , Gullapalli Anuradha , Papoulas Ophelia , Liu Chang , Leung Adelaide Y.-H. , Guo Luqiang , Brilot Axel , Marcotte Edward M. , Ke Zunlong , Leahy Daniel J. 
Published: November 2024

AbstractWe report here transport of the Epidermal Growth Factor Receptor (EGFR), Insulin Receptor, 7-pass transmembrane receptor Smoothened, and 13-pass Sodium-iodide symporter to extracellular vesicles (EVs) for structural and functional studies. Mass spectrometry confirmed the transported proteins as the most abundant in EV membranes, and the presence of many receptor-interacting proteins demonstrates the utility of EVs for characterizing membrane protein interactomes. Cryo-electron tomography of EGFR-containing EVs reveals that EGFR forms clusters in the presence of EGF with a ∼3 nm gap between the inner membrane and cytoplasmic density. EGFR extracellular regions do not form regular arrays, suggesting that clustering is mediated by the intracellular region. Subtomogram averaging of the EGFR extracellular region (ECR) yielded a 15 Å map into which the crystal structure of the ligand-bound EGFR ECR dimer fits well. These findings refine our understanding of EGFR activation, clustering, and signaling, and they establish EVs as a versatile platform for structural and functional characterization of human membrane proteins in a native-like environment.Significance StatementAtomic or near-atomic resolution structural studies of proteins embedded in cell membranes have proven challenging. We show that transporting integral membrane proteins to cell-derived extracellular vesicles enables structural and functional studies of human membrane proteins in a native membrane environment. We have used this approach to visualize an active form of full-length Epidermal Growth Factor Receptor (EGFR) and show that it forms clusters in the membrane and projects its cytoplasmic signaling domains ∼3 nm away from the membrane surface. EGFR is essential for normal development, but abnormal EGFR activity is associated with several human cancers and is the target of many anticancer therapies. Our studies refine current models of how ligand binding to EGFR transmits signals across cell membranes.
Machine Learning Approaches for Survival Prediction in Bladder Cancer: A Single-Center Analysis of Clinical and Inflammatory Markers
Authors: Causio Francesco Andrea , De Vita Vittorio , Nappi Andrea , Sawaya Melissa , Rocco Bernardo , Foschi Nazario , Maioriello Giuseppe , Russo Pierluigi 
Published: November 2024

AbstractThis study investigated the application of machine learning algorithms for survival prediction in bladder cancer patients undergoing cystectomy. We analyzed retrospective data from 370 patients, developing predictive models for disease-free survival (DFS), overall survival (OS), and cause of death. Multiple machine learning approaches were employed, including linear regression, random forests, gradient boosting, support vector machines, and neural networks. The models achieved mean absolute errors of 22-23 months for survival predictions and 66.67% accuracy in cause-of-death classification. Clinical T-stage emerged as the strongest predictor, while the Systemic Immune-Inflammation Index (SII) demonstrated a consistent negative correlation with survival outcomes. An unexpected positive correlation between age and survival was observed, possibly reflecting selection bias in surgical candidates. The study’s findings suggest that machine learning approaches, despite current limitations, offer promising tools for risk stratification in clinical trial design and patient allocation, though further refinement is needed for individual prognostication.
EasyPubPlot: a shiny web application for rapid omics data exploration and visualization
Authors: Tien Nguyen Tran Nam , Thu Nguyen Quang , Kim Dong Hyun , Park Seongoh , Long Nguyen Phuoc 
Published: November 2024

ABSTRACTComputational toolkits for data exploration and visualization from widely used omics platforms often lack flexibility and customization. While many tools generate standardized output, advanced programming skills are necessary to create high-quality visualizations. Therefore, user-friendly tools that simplify this crucial yet time-consuming step are essential. We developed EasyPubPlot (Easy Publishable Plotting), a straightforward, easy-to-use, user experience-oriented, open-source, and shiny web application along with its associated R package to streamline data exploration and visualization for functional omics-empowered research. EasyPubPlot generates publishable scores plots, volcano plots, heatmaps, box plots, dot plots, and bubble plots with minimal necessary steps. The tool was designed to guide new users for accurate and efficient navigation. Step-by-step tutorials for each type of plot are also provided. Herein, we demonstrated EasyPubPlot’s competent functionality and versatility by showcasing metabolomics and transcriptomics data. Collectively, EasyPubPlot reduces the gap between data analysis and stunning visualization, thereby diminishing friction and focusing on science. The app can be downloaded and installed locally (https://github.com/Pharmaco-OmicsLab/EasyPubPlot) or used through a web application (https://pharmaco-omicslab.shinyapps.io/EasyPubPlot).
Small-Angle and Quasi-Elastic Neutron Scattering from Polydisperse Oligolamellar Vesicles Containing Glycolipids
Authors: Bange Lukas , Rahimzadeh Amin , Mukhina Tetiana , von Klitzing Regine , Hoffmann Ingo , Schneck Emanuel 
Published: November 2024

AbstractGlycolipids are known to stabilize biomembrane multilayers through preferential sugar-sugar interactions that act as weak transient membrane cross-links. Here, we use small-angle and quasi-elastic neutron scattering on oligolamellar phospholipid vesicles containing defined glycolipid fractions in order to elucidate the influence of glycolipids on membrane mechanics and dynamics. Small-angle neutron scattering (SANS) reveals that the oligolamellar vesicles (OLVs) obtained by extrusion are polydisperse with regard to the number of lamellae,n, which renders the interpretation of the quasi-elastic neutron spin echo (NSE) data non-trivial. To overcome this problem, we propose a method to model the NSE data in a rigorous fashion based on the obtained histograms ofnand on theirq-dependent intensity-weighted contribution. This procedure yields meaningful values for the bending rigidity of individual lipid membranes and insights into the mechanical coupling between adjacent membrane lamellae, including the effect of the glycolipids.
Efficient creation and characterization of multi-kilobase knockins by CRISPR/Cas9 and multiple rAAVs
Authors: Sentmanat Monica F. , Wang Zi Teng , Kouranova Evguenia , Peters Samuel , Chan Wan Ching , Lin Jed , Miao Yong , Ritchey Julie , O’Neal Julie , Dipersio John , White J. Michael , Wallace Mia , Cui Xiaoxia 
Published: November 2024

AbstractWe report the successful creation of multi-kilobase knockin mice and cell lines using three rAAV donors and CRISPR/Cas9 via consecutive homology-directed repair and reliable generation of over 120 KI mice with rAAV donors. For comprehensive analysis of the post-edit genome, we combined target capture and long-read sequencing for a multiplexable and high-throughput, all-in-one method to detect on-target insertion and as importantly, various undesired editing outcomes in the genome. Together, the two novel methods greatly improve the efficiency and accuracy of challenging large KI mouse and cell models.
Charge screening and hydrophobicity drive progressive assembly and liquid-liquid phase separation of reflectin protein
Authors: Gordon Reid , Levenson Robert , Malady Brandon , Al Sabeh Yahya , Nguyen Alan , Morse Daniel E. 
Published: November 2024

AbstractThe intrinsically disordered reflectin proteins drive tunable reflectivity for dynamic camouflage and communication in the recently evolvedLoliginidaefamily of squid. Previous work revealed that reflectin A1 forms discrete assemblies whose size is precisely predicted by protein net charge density (NCD) and charge screening by the local anion concentration. Using dynamic light scattering (DLS), Forster resonant energy transfer (FRET) and confocal microscopy, we show that these assemblies, of which 95-99% of bulk protein in solution is partitioned into, are dynamic intermediates to liquid protein-dense condensates formed by liquid-liquid phase separation (LLPS). Increasing salt concentration drives this progression by anionic screening of the cationic protein’s Coulombic repulsion, and by increasing the hydrophobic effect which tips the balance between short-range attraction and long-range repulsion (SALR) to drive protein assembly and ultimately LLPS. Measuring fluorescence recovery after photobleaching (FRAP) and droplet fusion dynamics, we demonstrate that reflectin diffusivity in condensates is tuned by salt concentration and protein NCD. These results illuminate the physical processes governing reflectin A1 assembly and LLPS, and demonstrate the potential for reflectin A1 condensate-based tunable biomaterials. They also compliment previous observations of liquid phase separation in the Bragg lamellae of activated iridocytes and suggest that LLPS behavior may serve a critical role in governing the tunable and reversible dehydration of the membrane-bounded Bragg lamellae and vesicles containing reflectin in biophotonically active cells.