bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model-based fed-batch cultivation ofViola odorataplant cells exhibiting antimalarial and anticancer activity
Authors: Babu R , Veeramani Manokaran , Wallepure Aadinath , Muthuvijayan Vignesh , Singh Shailja , Srivastava Smita 
Published: October 2024

AbstractViola odoratais used in the indigenous medicine to treat respiratory tract disorders and is limited in availability. Bioprocess principles can be applied to develop sustainable methods to produce high-qualityV. odoratabiomass. To this effect, a modified stirred tank reactor and a balloon-type bubble column reactor were used to improve biomass production. Nutrient feeding strategies were developed using first principle-based mathematical modelling to achieve higher cell density in the reactor. Experimental validation of the fed-batch model-predicted strategy resulted in a two-fold enhancement in biomass production (32.2 g DW L-1) at the bioreactor level. Also, bioreactor-cultivated biomass extracts were tested forin vitrohemolytic, cytotoxic, anti-inflammatory, andin vivoantiplasmodial activities. This is the first report on fed-batch cultivation in bioreactors and the antiplasmodial activity ofV. odorata. Overall, the bioactive potential of thein vitro-generated biomass extracts is found to be similar to that in the natural plant biomass extracts.HighlightsCultivation ofV. odoratacell suspension culture using a modified stirred tank and balloon-type bubble column bioreactors.Batch kinetic models were developed and extrapolated into a fed-batch model.Enhanced biomass production (32.2 g DW L-1) in bioreactors using a nutrient-feeding strategy.Extracts showed anti-inflammatory effects and up to 80 % inhibition of parasite growth, with no hemolytic activity.Confirmed antiplasmodial activityin vivo, effective alongside artesunate.In vitro-generated biomass extracts showed comparable bioactive potential to that of natural plants.Graphical Abstract
Reducing flight time during running decreases tibial-fibular strains: a finite element analysis
Authors: Khassetarash Arash , Nigg Benno. M. , Edwards W. Brent 
Published: October 2024

AbstractPurposeReducing strains within the tibia and fibula during running may reduce the risk of stress fractures. We examined the effect of reduced flight time during running (i.e., grounded running) on finite-element predicted bone strains within the tibia-fibula complex.MethodsNine physically active males ran on an instrumented treadmill at 2.2 m/s using a preferred and reduced flight time technique in a randomized order. Three-dimensional force and motion capture data were recorded during running and a computed tomography image was subsequently acquired for the participant’s left leg. An inverse-dynamics-based musculoskeletal modeling workflow was used to calculate bone-on-bone contact and muscle forces during the stance phase of running. These forces served as inputs to a participant-specific finite-element model to estimate peak bone strains and strained volume (i.e., the volume of bone experiencing strains above a specific threshold) within the tibia-fibula complex.ResultsGuided attempts to reduce flight time was successful with an 18 ms (95% CI: 12 ms, 25 ms; p<0.001) reduction in flight time. Reducing flight time was associated with significant reductions in peak tibial/fibular strains (17% lower; 95% CI: -7.1%, -25.0%; p=0.002) and strained volume (35% lower; 95% CI: -13.57%, -50.87%; p=0.007).ConclusionWe conclude that guided attempts to reduce flight time significantly reduces strains in the tibia and fibula during treadmill running at a fixed speed. These results suggest that grounded running may be a viable technique to reduce musculoskeletal loading and stress fracture risk, particularly in slow runners and those runners coming back from injury.
Establishment of a locally adaptive allele in multidimensional continuous space
Authors: Sakamoto Takahiro 
Published: October 2024

AbstractLocal adaptation is widely seen when species adapt to spatially heterogeneous environments. Although many theoretical studies have investigated the dynamics of local adaptation using two-population models, there remains a need to extend the theoretical framework to continuous space settings, reflecting the real habitats of species. In this study, we use a multidimensional continuous space model and mathematically analyze the establishment process of local adaptation, with a specific emphasis on the relative roles of mutation and migration. First, the role of new mutations is evaluated by deriving the establishment probability of a locally adapted mutation using a branching process and a diffusion approximation. Next, the contribution of immigrants from a neighboring region with similar environmental conditions is considered. Theoretical predictions of the local adaptation rate agreed with the results of Wright–Fisher simulations in both mutation-driven and migration-driven cases. Evolutionary dynamics depend on several factors, including the strength of migration and selection, population density, habitat size, and spatial dimensions. These results offer a theoretical framework for assessing whether mutation or migration predominantly drives convergent local adaptation in spatially continuous environments in the presence of patchy regions with similar environmental conditions.
Prey attraction in a generalist microbial predator,Dictyostelium discoideum
Authors: Shreenidhi P. M. , McCabe Rachel I. , Queller David C. , Strassmann Joan E. 
Published: October 2024

AbstractGeneralist predators often live in environments that vary in the type and abundance of prey species. The prey species in turn vary in their susceptibility and suitability to predation. How do generalists navigate this variation in prey abundance and profitability and seek out their preferred prey? We investigated this in the soil protistDictyostelium discoideum, a generalist predator of many species of bacteria. Despite their generalist diet, amoebas experience considerable variation in growth rate on their prey bacteria. We tested if amoebas innately prefer the more profitable prey bacteria. We found that the levels of chemoattraction of naïve amoebas towards prey bacteria increased with increasing growth rate of the amoebas on those bacteria. This suggests thatD. discoideumamoebas have an innate prey preference that is adaptive. Next, we tested how experience with prey bacteria affects chemoattraction in amoebas. Given the number of bacterial species in soil, learning from experience should be advantageous. However, we found no evidence for learning; instead amoeba preference in learning experiments was partially explained by innate attractiveness of the prey bacteria. Our results suggest that generalist amoebas are innately attracted to the more profitable prey bacteria and this innate attraction cannot be overridden by recent experience.
lucie: An Improved Python Package for Loading Datasets from the UCI Machine Learning Repository
Authors: Ge Kenneth , Nguyen Phuc , Arnaout Ramy 
Published: October 2024

AbstractThe University of California–Irvine (UCI) Machine Learning (ML) Repository (UCIMLR) is consistently cited as one of the most popular dataset repositories, hosting hundreds of high-impact datasets. However, a significant portion, including 28.4% of the top 250, cannot be imported via theucimlrepopackage that is provided and recommended by the UCIMLR website. Instead, they are hosted as .zip files, containing nonstandard formats that are difficult to import without additional ad hoc processing. To address this issue, here we presentlucie—loadUniversityCalifornia Irvineexamples—a utility that automatically determines the data format and imports many of these previously non-importable datasets, while preserving as much of a tabular data structure as possible.luciewas designed using the top 100 most popular datasets and benchmarked on the next 130, where it resulted in a success rate of 95.4% vs. 73.1% forucimlrepo. lucieis available as a Python package on PyPI with 98% code coverage.
A Measure of Event-Related Potentials (ERP) Indices of Motivation During Cycling
Authors: Renoud-Grappin Rémi , Gabriel Damien , Broussard Emmanuelle , Mourot Laurent , Giustiniani Julie , Pazart Lionel 
Published: October 2024

AbstractAlthough motivation is a central aspect of the practice of a physical activity, it is a challenging endeavour to predict an individual’s level of motivation during the activity. The objective of this study was to assess the feasibility of measuring motivation through brain recording methods during physical activity, with a specific focus on cycling. The experiment employed the Effort Expenditure for Reward Task (EEfRT), a decision-making task based on effort and reward, conducted under two conditions: one involving cycling on an ergometer at moderate intensity and the other without cycling. The P300, an event-related potential linked to motivation, was recorded using electroencephalography.A total of 20 participants were recruited to complete the EEfRT, which involved making effort-based decisions of increasing difficulty in order to receive varying levels of monetary reward. The results demonstrated that the P300 amplitude was influenced by the act of cycling, exhibiting a reduction during the cycling session. This reduction may be explained by a reallocation of cognitive resources due to the exertion of physical effort, which is consistent with the transient hypofrontality theory. In terms of behaviour, participants demonstrated a tendency to make more challenging choices when the potential rewards were higher or the probability of gaining them was lower. This pattern was observed in both the cycling and non-cycling conditions. A positive correlation was identified between P300 amplitude and the proportion of difficult choices, particularly under conditions of low reward probability. This suggests that P300 may serve as a neural marker of motivation.The study demonstrates the feasibility of using electroencephalography to monitor motivation during exercise in real-time, with potential applications in rehabilitation settings. However, further research is required to refine the design and explore the effects of different exercise types on motivation.
Prefrontal Cortical Deficits are a Putative Susceptibility Factor for PTSD
Authors: Nalloor Rebecca , Shanazz Khadijah , Vazdarjanova Almira 
Published: October 2024

AbstractA subset of people who experience a traumatic event develop Post-Traumatic Stress Disorder (PTSD) suggesting that there are susceptibility factors influencing PTSD pathophysiology. While post trauma sequelae factors are extensively studied, susceptibility factors are difficult to study and therefore poorly understood. To address this gap, we previously developed an animal model - Revealing Individual Susceptibility to PTSD-like phenotype (RISP). RISP allows studying susceptibility factors by identifying, before trauma, rats that are likely to develop a PTSD-like phenotype after trauma. Hypofunctioning prefrontal cortex has been reported in people with PTSD, however, it is unclear if it is a susceptibility factor, sequalae factor, or both. Using RISP, we tested the hypothesis that altered medial prefrontal cortical (mPFC) function is a putative susceptibility factor. Susceptible male rats showed altered expression of plasticity-related immediate early genes (ArcandHomer1a) in the Prelimbic and Infralimbic subregions of the mPFC following spatial learning. Susceptible rats also showed deficits in attentional set shifting task when task demands increased. These findings suggest that Susceptible rats have mPFC deficits both at the cellular and functional level before trauma. Consistent with the findings in rats, military personnel who showed pre-trauma deficits in cognitive tasks involving mPFC developed PTSD post-trauma. Combined, these findings suggest that mPFC deficits are a putative susceptibility factor for PTSD and enhancing mPFC function in susceptible individuals before trauma may confer resilience to developing PTSD.SummaryA subset of people who experience a traumatic event develop Post-Traumatic Stress Disorder (PTSD) suggesting that there are susceptibility factors influencing (PTSD) pathophysiology. While post trauma sequelae factors are extensively studied, susceptibility factors are difficult to study and therefore poorly understood. In the manuscript, we report data from both an animal model of susceptibility to a PTSD-like phenotype, and from military personnel, which is consistent with the hypothesis that deficits in prefrontal cortex function exist in susceptible individuals before PTSD-inducing trauma. The reported experiments include both a cellular molecular technique (Arc/Homer 1acatFISH), based on the expression of effector immediate-early genes necessary for consolidation of learning-induced plasticity, as well as behavioral experiments for assessing cognitive function in rats and humans.
Rapid microfluidic perfusion system enables controlling dynamics of intracellular pH regulated by Na+/H+exchanger NHE1
Authors: Tran Quang D. , Bouret Yann , Noblin Xavier , Jarretou Gisèle , Counillon Laurent , Poët Mallorie , Cohen Céline 
Published: October 2024

AbstractpH regulation of eukaryotic cells is of crucial importance and influences different mechanisms including chemical kinetics, buffer effects, metabolic activity, membrane transport and cell shape parameters. In this study, we develop a microfluidic system to rapidly and precisely control a continuous flow of ionic chemical species to acutely challenge the intracellular pH regulation mechanisms and confront predictive models. We monitor the intracellular pH dynamics in real-time using pH-sensitive fluorescence imaging and establish a robust mathematical tool to translate the fluorescence signals to pH values. By varying flow rate across the cells and duration for rinsing process, we manage to tweak the dynamics of intracellular pH from a smooth recovery to either an overshooting state, where the pH goes excitedly to a maximum value before decreasing to a plateau, or an undershooting state where the pH is unable to recover to ∼ 7. We believe our findings will provide more insight into intracellular regulatory mechanisms and promote the possibility of exploring cellular behavior in the presence of strong gradients or fast changes in homogeneous conditions.
CryoLike: A python package for cryo-electron microscopy image-to-structure likelihood calculations
Authors: Tang Wai Shing , Soules Jeff , Rangan Aaditya , Cossio Pilar 
Published: October 2024

ABSTRACTExtracting conformational heterogeneity from cryo-electron microscopy (cryo-EM) images is particularly challenging for flexible biomolecules, where traditional 3D classification approaches often fail. Over the past few decades, advancements in experimental and computational techniques have been made to tackle this challenge, especially Bayesian-based approaches that provide physically interpretable insights into cryo-EM heterogeneity. To reduce the computational cost for Bayesian approaches, we introduce CryoLike, a computationally efficient algorithm for evaluating image-to-structure (or image-to-volume) likelihoods across large image datasets, which is built on Fourier-Bessel representations of the images and packaged in a user-friendly Python workflow.
Complementary evaluation of computational methods for predicting single residue effects on peptide binding specificities
Authors: Ayyildiz Merve , Noske Jakob , Gisdon Florian J. , Kynast Josef P. , Höcker Birte 
Published: October 2024

AbstractUnderstanding the interactions that make up protein-protein or protein-peptide interfaces is a crucial step towards applications in biotechnology. The ability to discriminate between different partners defines the specificity of a binding protein and is equally important as its affinity to the target. Whereas many established computational methods provide an estimate of binding or non-binding, comparing similar ligands is still significantly more challenging. Here we evaluated the capability of predicting ligand binding specificity using three established but conceptually different physics-based methods for protein design. As a model system, we analyzed the binding of peptides to designed armadillo repeat proteins, where a single residue of the peptide was changed systematically, and compared the results with an experimental reference data set. The mutation of a single residue can have a strong impact on binding affinity and specificity, which is difficult to capture in sampling and scoring. We critically assessed the prediction accuracy of the computational methods and found that the prediction performance of each method is differently affected, suggesting the use of a complementary approach of the evaluated methods.Author SummaryProteins have to recognize other proteins and peptides in the cell with high specificity. To be able to predict such interactions with high precision would be immensely useful for medical and biotechnological applications. Here we tested three computational methods that use physics-based force fields on an experimental dataset and evaluated how well these predictions can be used to discriminate binding pockets on a single residue level. The predicted values of each method and the experimentally determined specificities correlated well, even though each approach had its biases. Therefore, we correlated the predictions with each other to complement the strengths and weaknesses of all approaches.
Reenacting a mouse genetic evolutionary arms race in yeast reveals SLXL1/SLX compete with SLY1/2 for binding to Spindlins
Authors: Arlt Martin F. , Kruger Alyssa N. , Swanepoel Callie M. , Mueller Jacob L. 
Published: October 2024

AbstractThe house mouse X and Y chromosomes have recently acquired high copy number, rapidly evolving gene families representing an evolutionary arms race. This arms race between proteins encoded by X-linkedSlxl1/Slxand Y-linkedSlygene families can distort male offspring sex ratio, but how these proteins compete remains unknown. Here, we report howSlxl1/SlxandSlyencoded proteins compete in a protein family-specific and dose-dependent manner using yeast. Specifically, SLXL1 competes with SLY1 and SLY2 for binding to the Spindlin SPIN1. Similarly, SLX competes with SLY2 for binding the Spindlin SSTY2. These competitions are driven by the N-termini of SLXL1, SLX, SLY1, and SLY2 binding to the third Tudor domains of SPIN1 and SSTY2. SLY1 and SLY2 form homo- and heterodimers, suggesting the competition is between complex multimers. Residues under positive selection mapping to the interaction domains and rapid exon gain/loss are consistent with competition between the X- and Y-linked gene families. Our findings support a model in which dose-dependent competition of these X- and Y-linked encoded proteins to bind Spindlins occurs in haploid X- and Y-spermatids to influence X-versus Y-sperm fitness and thus sex ratio.Significance StatementIn house mouse, an evolutionary arms race between proteins encoded by the X-linkedSlxl1/Slxand Y-linkedSlygene families during spermatogenesis can distort male offspring sex ratio, but how these proteins compete remains unknown. We report how SLXL1/SLX competes with SLY1/SLY2 by demonstrating their dose-dependent competitive binding to Spindlins, the key protein domains and rapidly evolving residues and exons that drive the competition, and how the competition is likely between complex multimers. Our findings have broad implications for the mechanics of evolutionary arms and how competition between sex chromosomes influences X-versus Y-sperm fitness and sex ratio.
Academic Success and Mental Health: The Paradox of Frontoparietal-Default Mode Network Coupling among Children Facing Poverty
Authors: Pacheco Selina , Bunge Silvia A. , Ellwood-Lowe Monica E. 
Published: October 2024

AbstractChildhood family income is a powerful predictor of academic achievement and mental health. Here, we ask whether children living in poverty who succeed academically are subsequently protected from, or at risk for, internalizing symptoms. Prior research indicates that children in poverty with better academic performance tend to have higher temporal coupling between the Lateral Frontoparietal Network (LFPN) and Default Mode Network (DMN) than lower-performing children in poverty. An open question is whether higher LFPN-DMN coupling has maladaptive long-term consequences for mental health for this population. In this pre-registered longitudinal study, we analyzed data from 10,829 children (1,931 in poverty) in the ABCD study across four time points (ages 9-13). Higher grades correlated with fewer internalizing symptoms; this association was more pronounced for children below poverty. Longitudinally, LFPN-DMN connectivity correlated positively with internalizing symptoms across both groups and timepoints. Thus, although higher academic performance was associated with better mental health outcomes for all children, the specific pattern of LFPN-DMN connectivity that supports academic resilience among children in poverty may be a risk factor for developing internalizing symptoms. These findings highlight the complex nature of academic resilience in the context of structural inequity.HighlightsHigh grades linked to fewer internalizing symptoms, especially for kids in poverty.High LFPN-DMN connectivity predicts higher internalizing symptoms in children.Neural correlates of academic resilience may predispose children to internalizing.Children below poverty had higher internalizing symptoms.
ALDH1 subtype-specific inhibitor targets key cancerous epithelial cell populations in aggressive subtypes of breast cancer
Authors: Pequerul Raquel , Constantinescu Andrada , Janji Bassam , Kumar Akinchan , Parés Xavier , Palacios Oscar , Colignon Delphine , Berrou Axelle , Fournet Guy , Berchard Paul , Martin Guillaume , Ceylan Ismail , Rebollido-Ríos Rocio , Farrés Jaume , Perez-Alea Mileidys 
Published: October 2024

ABSTRACTAggressive breast cancer subtypes, particularly triple-negative breast cancer (TNBC), lack effective targeted therapies, requiring novel approaches. This study focuses on the aldehyde dehydrogenase 1A (ALDH1A) subfamily, comprising ALDH1A1, ALDH1A2, and ALDH1A3, and their roles in tumor biology and the tumor microenvironment. Comprehensive transcriptomic and single-cell analyses revealed subtype- and cell-specific expression patterns of ALDH1A isoforms, withALDH1A3predominantly expressed in epithelial cancer cells of basal-like tumors, whileALDH1A1andALDH1A2were expressed in stromal and immune-associated subpopulations. Guided by these findings, we developed ABD0171, a selective ALDH1A3 inhibitor that demonstrated potent isoform-specific activity. ABD0171 effectively disrupted key pathways in TNBC cellsin vitro, including IL6/JAK/STAT3, tPA and Src/FAK, and exhibited superior selectivity, robust antitumor and antimetastatic effects, and a favorable safety profilein vivo. These results establish ALDH1A3 as a promising therapeutic target and validate ABD0171 as a candidate to address current challenges in aggressive breast cancers.