bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative responses of legume vs. non-legume tropical trees to biochar additions
Authors: Thomas Sean C. , Halim Md. Abdul , Ali Syed Tuhin 
Published: February 2025

AbstractNitrogen-fixing plants in the legume family (Fabaceae) may show particularly large positive responses to biochar additions due to their capacity to compensate for reduced N in biochar-amended soils. Prior studies also suggest that biochar may have specific developmental effects on legumes, including increased root nodulation and altered morphology. We examined the growth and morphometric responses of legume and non-legume tropical trees to biochar additions in a common garden experiment. Four legume species (Acacia auriculiformis,A. mangium,Delonix regia, andPterocarpus santalinus) and four non-legumes (Eucalyptus alba,Melia azedarach, Swietenia macrophylla, andSyzygium cumini) were compared in terms of sapling responses to additions of a wood-feedstock biochar applied at 10 and 20 t/ha. Overall, strong positive effects of biochar additions on sapling performance were observed, with an average increase of 30% in total biomass and a notable increase in height relative to diameter growth. Species showed pronounced differences in responses, with strong interactive effects of species and biochar treatments on growth metrics. Legume species showed an average increase somewhat higher than non-legumes; however, responses were variable among species, with the twoAcaciaspecies showing the largest responses, resulting in a non-significant pattern. A literature-based meta-analysis of tropical and subtropical trees likewise suggests higher biochar responses in legumes, but also falls short of statistical significance. In addition, experimental results indicate large interactive effects of species and biochar on soil pH and other soil properties. High growth responses of certain taxa of legumes (and other taxa) to biochar, and pronounced species-specific effects on soil properties, may reflect evolved responses to fire disturbance that can be leveraged in the context of forest restoration and enhanced carbon sequestration in degraded tropical landscapes.
Initiation and maturation of the early axonal βII-spectrin membrane-associated periodic skeleton requires active cytoskeletal remodelling
Authors: Bodas Shivani , Mishra Ashish , Pullarkat Pramod , Ghose Aurnab 
Published: February 2025

ABSTRACTThe axonal membrane-associated periodic skeletal (MPS) consisting of evenly spaced F-actin rings crosslinked by spectrin heterotetramers has been observed in many neuronal subtypes across multiple species. The MPS has been implicated in a diversity of functions ranging from a load-bearing tension buffer to a periodic ruler positioning channels and signalling complexes. However, the initiation and early development of the axonal MPS are poorly understood.Using superresolution imaging of embryonic dorsal root ganglion axons, we show that the early development of the βII-spectrin MPS involves recruitment and stabilisation of the βII-spectrin to the axonal cortex followed by progressive establishment of long-range periodic order. Microtubule dynamics are essential for MPS formation in the early stages, while microtubules have a passive stabilizing function in the mature MPS. We show that the early subplasmalemmal recruitment and confinement of βII-spectrin is dependent on cortical actin. Further, active nucleation of F-actin is required in early development but dispensable for the maintenance of the mature MPS. Finally, using a βII-spectrin knockout model, we demonstrate that the actin-binding and lipid interacting domains of βII-spectrin are critical for its subplasmalemmal confinement and, subsequently, MPS maturation.Our study provides insights into the mechanisms governing the development and maturation of the axonal MPS, highlighting the critical role of cytoskeletal dynamics.
Lifespan Mapping of EEG Source Spectral Dynamics withξ−αNET
Authors: Reyes Ronaldo Garcia , Gonzales Ariosky Areaces , Wang Ying , Jin Yu , Minatti Ludovico , Valdes-Sosa Pedro A. 
Published: February 2025

ABSTRACTWe formulate a new class of parametric, multivariate, and structurally informed spectral components model of the EEG, theξ − αNET, that allows us to map the Lifespan of EEG source spectral dynamics across a large data set of EEG cross spectrum at high spatial resolution. This approach accurately estimates source spectral components and effective connectivity through the use of biophysical modeling while maintaining computational efficiency, as confirmed by simulation benchmarks. We are able to analyze source dynamics with a resolution of 8,003 voxels from the HarMNqEEG dataset, which includes scalp EEG cross-spectrum tensors collected from 1965 subjects across 9 countries, using various devices and accounting for different age groups. Our findings indicate that the Bayesian Model Inversion of theξ − αNET allows to map Lifespan of conduction delays that follows a U-shaped trajectory, which contrasts with independently recorded myelin concentration measurements. Moreover, we assess the spatiotemporal distribution of spectral components, revealing that the aperiodic or fractal component has an isotropic spatial distribution on the cortical surface. While the generator’s spectral peak in theαband, i.e.,α-rythms, is localized on the visual areas of the brain. Using a Zero Inflated Gaussian model, our findings indicate that the mode frequency that characterizes theα-rythms or Peak Alpha Frequency shows an inverted U-shaped trajectory for both hemispheres across the Lifespan and a spatial gradient of zero inflation in PAF across the cortex that flattens the trajectory from posterior to frontal areas. We provide both the code of theξ−αNET and the source solution of the spectral dynamics for the HarMNqEEG.
New insights into the 17β-hydroxysteroid dehydrogenase type 10 and amyloid-β 42 derived cytotoxicity relevant to Alzheimer’s disease
Authors: Houfková Aneta , Schmidt Monika , Benek Ondřej , Fabrik Ivo , Andrýs Rudolf , Zemanová Lucie , Soukup Ondřej , Musílek Kamil 
Published: February 2025

ABSTRACTThe multifunctional mitochondrial enzyme 17β-hydroxysteroid dehydrogenase type 10 (HSD10) plays an important role in the pathology of several diseases, of which Alzheimer’s disease (AD) is the most debated. HSD10 overexpression and its interplay with amyloid-β peptide (Aβ) are considered a factor contributing to mitochondrial damage and neuronal stress observed in AD patients. This study confirms that individual overexpression of HSD10 or APP (amyloid precursor protein that gives rise to Aβ) leads to cytotoxicity, and both pathological conditions are linked to mitochondrial damage. However, the metabolic changes caused by these two overexpressions significantly differ, particularly in their effect on the tricarboxylic acid cycle and β-oxidation. Furthermore, the enzymatic activity of HSD10 is identified as the primary factor of HSD10 cytotoxicity, which is significantly exacerbated in an Aβ-rich environment and can be partially reversed by HSD10 inhibitors. Notably, a previously published and competitive benzothiazole inhibitor was effective in restoring the viability of HSD10 overexpressing cells alone and in an Aβ-rich environment, implying the potential benefit of HSD10 inhibitors in mitochondrial diseases and/or AD treatment.GRAPHICAL ABSTRACT
QWENDY: Gene Regulatory Network Inference Enhanced by Large Language Model and Transformer
Authors: Wang Yue , Tian Xueying 
Published: February 2025

AbstractKnowing gene regulatory networks (GRNs) is important for understanding various biological mechanisms. In this paper, we present a method, QWENDY, that uses single-cell gene expression data measured at four time points to infer GRNs. It is based on a gene expression model and solves the transformation for the covariance matrices. Unlike its predecessor WENDY, QWENDY avoids solving a non-convex optimization problem and produces a unique solution. Then we enhance QWENDY by transformer neural networks and large language models to obtain two variants: TEQWENDY and LEQWENDY. We test the performance of these methods on two experimental data sets and two synthetic data sets. TEQWENDY has the best overall performance, while QWENDY ranks the first on experimental data sets.
Simons Sleep Project (SSP): An open science resource for accelerating scalable digital health research in autism and other psychiatric conditions
Authors: Hacohen Micha , Levi Adam , Kaiser Hadas , Snyder LeeAnne , Amatya Alpha , Gundersen Brigitta B. , Spiro John E. , Dinstein Ilan 
Published: February 2025

AbstractWearable and nearable devices offer a novel opportunity to measure extensive behavioral and neurophysiological data directly from participants in their home environment. The Simons Sleep Project (SSP) was designed to accelerate research into sleep and daily behaviors in individuals with autism using such techniques. This open-science resource contains raw and processed data from Dreem3 EEG headbands, multi-sensor EmbracePlus smartwatches, and Withings Sleep mats, as well as parent questionnaires and daily sleep diaries. Data were collected successfully for >3600 days/nights from 102 adolescents (10-17 years old) with idiopathic autism and 98 of their non-autistic siblings. Whole-exome sequencing data is also available for all participants and their parents. To demonstrate the utility of this extensive dataset, we first present the breadth of synchronized high-resolution data available across multiple sensors/devices. We then demonstrate that objective sleep measures (e.g., total sleep time) from the three devices are more accurate and reliable than parent reported measures and reveal that sleep onset latency (SOL) was the only objectively defined sleep measure that differed significantly between autistic children and their siblings (of those examined in the study). Moreover, SOL was reliably associated with the severity of multiple behavioral difficulties in all children, regardless of autism diagnosis. These results highlight the importance of measuring sleep directly from participants using objective measures and demonstrate the extensive opportunities afforded by the SSP to further study autism and develop new digital phenotyping techniques for multiple research domains.
Biomonitoring Fumonisin B1 and Zearalenone to improve public food safety for female cereal value chain workers in Ghana
Authors: Quartey N.K-A. , Kumi J. , Lutterodt H.E. , Ankar-Brewoo G.M. , Ampofo J. , Ellis W.O. , Ofosu I.W. 
Published: February 2025

AbstractMonitoring biomarkers offers more reliable results, compared to typical mycotoxin exposure estimation approaches that employ their prevalence in food in combination with population food intake data. Free forms of fumonisins B1 and B2 (FB1+ FB2), and free zearalenone (ZEN) together with three of its enteric metabolites have been identified as fitting indicators for exposures to the parent mycotoxins. This study investigated the similarities in regional and age-related mycotoxin exposures among sampled females employed in the cereal value chain in Ghana. After obtaining ethical clearance to conduct the study, spot urine samples were collected from females in cereal growing communities in The Upper West, Northern, Ashanti and Greater Accra regions of Ghana. The collected bio-samples were processed appropriately and LC-MS/MS chromatographic methods used to determine the presence and levels of FB1, FB2, ZEN, α-ZEL, β-ZEL and ZEN-14, glucuronide. The results indicate that while probable daily intake of the mycotoxins decreased with age, being higher for the 10-19 age groups, exposures were higher in the 55+ age group, consistent with age-related accumulation. The creatinine adjusted mycotoxin levels also presented a snapshot of renal function across the four regions being generally homogenous for participants in the Ashanti region. Wide variations in creatinine concentrations were observed for the Upper West and Northern regions and the spread was heterogenous for Greater Accra. The insight into age-related mycotoxin exposures agrees with previous findings of significant links between FB1 exposures and adverse health outcomes. ZEN exposures were higher in the 10-19 age group suggesting the potential for younger age groups to face significant risks due to exposure to the mycotoxin. The findings from this biomonitoring exercise prompts heightened public health interventions, guided by strategies that will adequately address the age-related risk of mycotoxin exposures in different populations.
Robust Cancer Crowdfunding Predictions: Leveraging Large Language Models and Machine Learning for Success Analysis
Authors: Roy Abhishikta , Srivastava Vineet , Boggavarapu Lokesh , Bhaumik Runa , Chandrasekharan Ranganathan , Mensah Edward , Galvin John 
Published: February 2025

AbstractBackgroundIn the field of medical crowdfunding prediction, traditional statistical methods have long been the standard. Machine learning algorithms are popular because they can model complex relationships between variables, capture interactions, and provide more accurate predictions, even when input variables are highly correlated. Furthermore, previous research has largely overlooked the quantitative assessment of success levels and the selection of key predictors. To address these limitations, a novel approach is needed that leverages advanced machine learning techniques.ObjectiveThis study aimed to address these gaps by proposing a robust feature engineering approach that leverages the capabilities of large language models (LLMs). The goal was to extract the success determinants using a large language model for a cancer crowdfunding campaign. Furthermore, this study evaluated the performance of four machine learning algorithms in predicting campaign success and quantitatively assessed the level of success.MethodWe separately analyzed linguistic and social determinants of health features to understand how much each factor contributes to a crowdfunding campaign’s success. These features were generated using a large language model (GPT-4o). A random forest algorithm with a permutation technique was used to rank the features. We comparatively evaluated the prediction accuracy, sensitivity, and specificity of four machine learning algorithms, random forest, gradient boosting, logistic, and elastic net, using a 10-fold cross-validation.ResultsGradient Boosting consistently outperforms the other algorithms in terms of sensitivity (consistently around 0.786 to 0.798), indicating its superior ability to identify successful crowdfunding campaigns using linguistic and social determinants of health features. The permutation importance score reveals that for severe medical conditions, income loss, chemotherapy treatment, clear and effective communication, cognitive understanding, family involvement, empathy and social behaviors play an important role in the success of campaigns.ConclusionsThis study highlights the critical role of linguistic, social, demographic, and medical features in predicting the success of cancer crowdfunding campaigns, with risk communication and medical severity emerging as key predictors. The study also suggests the need for more nuanced and optimized models and improved income protection and healthcare policies to reduce reliance on crowdfunding for cancer treatment.
The Association Between IT-Profession-Specific Stressors and Mental Health Conditions Plus the Role of Mental Health Literacy in Help-Seeking
Authors: Garcia Colato Edlin , Liu Nianjun , Chow Angela , Sherwood-Laughlin Catherine , Macy Jonathan T. 
Published: February 2025

AbstractBackgroundThe Information Technology (IT) sector is growing and encompasses all professions, from leisure and recreation to hospitals and emergency response groups. IT professionals are experiencing increased threats (e.g., ransomware attacks), but little is known about the relationship between these IT-profession-specific stressors and the professionals’ mental health. This study aimed to 1) estimate the associations between IT-profession-specific stressors and anxiety, depression, and stress, and 2) examine the role of mental health literacy (MHL) as a mediator of the relationship between depression, anxiety, stress, and help-seeking.MethodsBetween February and May 2023, 388 IT professionals working in the US were surveyed online. Participants reported demographic characteristics, and their MHL, mental health symptoms, and help-seeking intentions were assessed with the following scales: MHL-in the workplace (MHL-W), Center for Epidemiological Studies Depression-10 (CESD-10), Generalized Anxiety Disorder-7 (GAD-7), Perceived Stress Scale-10 (PSS-10), and the mental help seeking intention scale (MHSIS).ResultsRespondents who had experienced ransomware attacks in the past year reported significantly higher symptoms of depression, anxiety, and stress. Adapting to rapid changes in technology and business requirements was associated with higher levels of stress. MHL was found to partially mediate the relationship between depression and help-seeking, but not between anxiety or stress and help-seeking.ConclusionThese findings provide insight into the workplace stressors that pose a greater psychological health risk for IT professionals. These results emphasize the important role of MHL in helping facilitate the connection between depressive symptoms and help-seeking.
Foundation time series models for forecasting and policy evaluation in infectious disease epidemics
Authors: Kalahasti Suprabhath , Faucher Benjamin , Wang Boxuan , Ascione Claudio , Carbajal Ricardo , Enault Maxime , Cassis Christophe Vincent , Launay Titouan , Guerrisi Caroline , Boëlle Pierre-Yves , Baldo Federico , Valdano Eugenio 
Published: February 2025

AbstractEpidemic forecasting and policy evaluation rely on mathematical models to predict infectious disease trends and assess the impact of public health policies. Traditional models typically require extensive epidemiological data and may struggle in data-limited settings. Transformer-based, foundation AI models have demonstrated strong predictive capabilities in various time series applications. We investigated whether they can be the basis of a new epidemic modeling framework. We evaluated five foundation models - TabPFN-TS, TimeGPT, TimesFM, Lag-Llama, and Chronos - across diverse pathogens, diseases and locations, including influenza-like illness, RSV, chickenpox, dengue, COVID-19 and neonatal bronchiolitis. Models were tested for long-term forecasting (multi-season predictions), short-term forecasting (four-week-ahead predictions), and epidemic peak timing estimation. We also assessed their ability to generate counterfactual scenarios in policy evaluation, using COVID-19 restriction measures in Italy, RSV immunization in France, and synthetic epidemic data as validation. Foundation models demonstrated strong predictive accuracy, possibly outperforming traditional statistical and mechanistic models in data-limited contexts. They generated multi-season forecasts and short-term forecasts with good accuracy and stable uncertainty. They gave reliable peak timing estimates months before the actual peak. In policy evaluation, TabPFN-TS accurately estimated intervention effects, matching estimates from an independent epidemiological study. Our findings suggest that foundation models can complement existing approaches in epidemic modeling. Their ability to generate accurate forecasts and counterfactual analyses with minimal data input highlights their potential for real-time public health decision-making, particularly in emergent and resource-constrained settings. Further research should explore domain-specific adaptations to optimize performance for infectious disease modeling.
An inflatable ‘finger-lock’ for stabilizing nailfold capillary videos and modulating blood flow velocities
Authors: Forst Marcus L. , Rincon Gabriela , Levy Juliette H. , Cornfield David N , Quake Stephen R 
Published: February 2025

AbstractHigh-resolution video capillaroscopy shows promise as a non-invasive method to directly observe blood cells as they flow through and interact with the microvas-culature. When imaging microvasculature in the nailfold, the inherent shaking of the fingers requires physical stabilization for image noise reduction. However, any external force applied to the fingers will affect the rate of blood flow. We designed an inflatable ‘finger-lock’ for nailfold capillaroscopy, which stabilizes the finger against a coverslip with constant pressure. Testing 72 participants, we demonstrated that increasing ‘finger-lock’ pressure improves video stability and decreases the velocity of capillary blood cells. This shows that capillary blood cell velocity measurements should monitor and control external pressure. Our work introduces a method to perturb local capillary blood flow and measure the microvascular response, enabling further studies investigating how person-specific factors (e.g. age, disease) impact vascular health.
Plasmodiumactin-like proteins are essential for DNA segregation during male gametogenesis and malaria transmission
Authors: Varshney Aastha , Pandey Eisha , Nirdosh  , Mishra Satish 
Published: February 2025

AbstractProtozoan parasites of the genusPlasmodiumcause malaria and involve infection of multiple hosts and cell types during the life cycle. Producing sexually fit gametocytes is essential for transmitting thePlasmodiumparasite into an anopheline mosquito vector. After the uptake of malaria parasites, male gametocytes undergo three rounds of DNA replication to produce eight nucleated flagellar gametes. Here, we report that the actin-like proteins Alp5a and Alp5b are involved in DNA segregation during male gametogenesis. ThePlasmodium-specific paralogous genes Alp5a and Alp5b superimposed on human Arp2 and Arp3, localize to the nucleus, and interact with each other. Alp5a and Alp5b are dispensable for the development ofP. bergheiblood-stages individually but indispensable simultaneously. In agreement with genetic studies, the inhibitory activity of the Arp2/3 complex inhibitor inPlasmodiumsupports an essential role for this complex during the blood stage. Deletion of Alp5a or Alp5b did not affect actin nucleation, parasite growth, or gametocytemia in the blood. The knockout parasites successfully invaded the midgut and developed into oocysts, but their size was significantly reduced, and they failed to survive. Genetic crosses revealed defects in male gamete integrity. We found that the reduced oocyst development was due to impaired DNA segregation during male gametogenesis. This study provides molecular insight into the fundamental requirements of the Alps inPlasmodium, which are essential for malaria transmission.