bluuebunny/crossref_metadata_2025_split huggingface dataset:
Time-dependent chromatin maturation during 3D spheroid culture improves preclinical modeling of non-small cell lung cancer
Authors: Darracq Anaïs , Sgarioto Nicolas , Huot Marielle , McInnes Gabrielle , Meant Antoine , Langford Alexandra , Villarreal Oscar D , Marois François , Caron Maxime , Saint-Onge Pascal , Leclerc Severine , Cagnone Gaël , Andelfinger Gregor , Richard Stéphane , Sinnett Daniel , McGraw Serge , Raynal Noël J-M 
Published: January 2025

ABSTRACTNon-small cell lung cancer (NSCLC) is the deadliest cancer worldwide. Therapeutic progress stagnate, highlighting the complexity to replicate NSCLC in preclinical models. Drug discovery studies rely mostly on cancer cells in two-dimension (2D), which poorly predict drug efficacy in patients. There is a growing interest in three-dimensional (3D) preclinical models, such as 3D spheroids, to better model tumor phenotype and improve therapeutic prediction. However, a comprehensive view of 3D culture methods impact on transcriptomes, epigenomes and pharmacological responses and their correlations to NSCLC tumors is still missing. Here, we demonstrate that NSCLC spheroids undergo time-dependent transcriptomic and epigenomic changes, which peak after 3 weeks of culture. While DNA methylome remained stable, chromatin methylation and acetylation marks gained features of advanced NSCLC in a time-dependent manner. Single-cell transcriptomic profiling of spheroids demonstrated that time of 3D culture improved the correlation to NSCLC tumors. Moreover, long-term culture of 3D spheroids increased drug screening predictability, by showing resistance to drugs that failed in NSCLC patients (such as HDAC inhibitors) while demonstrating novel pharmacological vulnerabilities and synergistic interactions (such as combination of PRMT and HDAC inhibitors). Strikingly, reverting 3D spheroids back to 2D culture rapidly reversed transcriptomic, epigenetic and pharmacological signatures acquired after 3 weeks of 3D culture, highlighting the critical impact of cell culture conditions on NSCLC phenotype. Collectively, our findings demonstrate that implementing a time-dependent maturation process into 3D spheroid culture induces chromatin and transcriptomic changes that enhance NSCLC preclinical modeling.
A Diverse Genetic Basis for Metabolic Reactions is Revealed Through Pangenome analysis
Authors: Ardalani Omid , Phaneuf Patrick V. , Krishnan Jayanth , Li Gaoyuan , Burrows Joshua , Nielsen Lars K. , Palsson Bernhard O. 
Published: January 2025

ABSTRACTSequenced genomes for thousands of strains of a bacterial species allow for a comprehensive analysis of its pangenome. We present a pangenome study ofEscherichia coli’s metabolism by formulating ‘gene-to-protein-to-reaction associations’ (GPRs) for about 2,700 metabolic reactions in 2,377 fully sequenced strains. On one hand, these GPRs reconstruct strain–specific networks that allow computational predictions (and experimental validation) of metabolic phenotypes, while on the other hand, they give the genetic basis for a given metabolic reaction in every strain. A pangenome-wide analysis of GPRs shows that: 1) We can reveal the genetic basis for a specific metabolic property at the species level; 2) The genetic basis for many metabolic reactions is diverse; 3) Many rare genes show variation in the gene’s genomic neighborhood which often contain genes from transposable elements, 4) Many rare genes show large-scale fragmentation and horizontal gene transfer (>11,000 rare genes in 2,377 strains); and 5) The aromatic amino acids and branched chain amino acids pathways are enriched with rare genes, with Acetolactate synthase having 29 distinct genes. Thus, analysis of GPRs across the pangenome reveals a complex dynamic evolutionary history of metabolism, revealing the role of conserved, fragmented, and horizontally transferred metabolic genes.
End-to-end Learning of Safe Stimulation Parameters for Cortical Neuroprosthetic Vision
Authors: Küçükoğlu Burcu , Rueckauer Bodo , de Ruyter van Steveninck Jaap , van der Grinten Maureen , Güçlütürk Yağmur , Roelfsema Pieter R. , Güçlü Umut , van Gerven Marcel 
Published: January 2025

AbstractDirect electrical stimulation of the brain via cortical visual neuroprostheses is a promising approach to restore basic sight for the visually impaired by inducing a percept of localized light called ‘phosphenes’. Apart from the challenge of condensing complex sensory information into meaningful stimulation patterns at low temporal and spatial resolution, providing safe stimulation levels to the brain is crucial. We propose an end-to-end framework to learn optimal stimulation parameters (amplitude, pulse width and frequency) within safe biological constraints. The learned stimulation parameters are passed to a biologically plausible phosphene simulator which takes into account the size, brightness, and temporal dynamics of perceived phosphenes. Our experiments on naturalistic navigation videos demonstrate that constraining stimulation parameters to safe levels not only maintains task performance in image reconstruction from phosphenes but consistently results in more meaningful phosphene vision, while providing insights into the optimal range of stimulation parameters. Our study presents a stimulus-generating encoder that learns stimulation parameters (1) satisfying safety constraints, and (2) maximizing the combined objective of image reconstruction and phosphene interpretability with a highly realistic phosphene simulator accounting for temporal dynamics of stimulation. End-to-end learning of stimulation parameters this way enables enforcement of critical biological safety constraints as well as technical limits of the hardware at hand.
A non-invasive approach to awake mouse fMRI compatible with multi-modal techniques
Authors: Laxer Sam , Eed Amr , Bellyou Miranda , Zeman Peter , Gilbert Kyle M , Naderi Mohammad , Menon Ravi S 
Published: January 2025

AbstractMouse functional magnetic resonance imaging (fMRI) studies contribute significantly to neuroimaging research, playing an important role in advancing our understanding of the human brain. Efforts to scan mice in the awake state and avoid the use of anesthesia have demonstrated many benefits. However, the majority of current awake fMRI approaches involve head fixation through invasive surgical means. These approaches are limited for several reasons including increased subject morbidity and mortality, prolonged study timelines due to surgical recovery, a higher risk of susceptibility artifacts contaminating T2*-weighted images and obstructed access to the head for multi-modal recording techniques such as electrophysiology and fibre photometry. To address this need, we propose a non-invasive restraint to scan mice in the awake state. The restraint was designed to be compatible with brain stimulation and recording approaches. It was evaluated on the basis of motion, fMRI data quality, and animal stress levels, and subsequently compared to a conventional headpost restraint. We found the proposed approach was effective at restraining mice across a broad range of weights without the need for any anesthesia for setup. Conservatively, acquiring 25% more data with the non-invasive restraint compensates for censored frames in high motion runs and results in comparable network spatial specificity to less motion-vulnerable headpost approaches. This validation of network robustness paired with its non-invasive nature makes it a favourable approach for applications requiring high-throughput and/or multimodal imaging studies.
BioMaster: Multi-agent System for Automated Bioinformatics Analysis Workflow
Authors: Su Houcheng , Long Weicai , Zhang Yanlin 
Published: January 2025

AbstractMotivationThe rapid expansion of biological data has significantly increased the complexity of bioinformatics workflows, which often involve intricate, multi-step processes. These tasks demand considerable manual effort from bioinformaticians, creating inefficiencies and limiting scalability. Recent advancements in large language model (LLM)-powered agents offer promising solutions to streamline and automate these workflows. However, existing automated systems, while effective for short, well-defined tasks, often struggle with long, multi-step workflows due to challenges such as error propagation, limited adaptability to emerging tools, and the inability of LLMs to generalize to niche bioinformatics tasks. Achieving effective workflow automation requires robust task coordination, dynamic knowledge retrieval, and mechanisms to ensure errors are identified and resolved before they impact downstream processes.ResultsWe present BioMaster, a multi-agent framework designed to automate and streamline complex bioinformatics workflows. BioMaster incorporates specialized agents with role-based responsibilities, enabling precise task decomposition, execution, and validation. It leverages Retrieval-Augmented Generation (RAG) to dynamically retrieve domain-specific knowledge, improving adaptability to new tools and niche analyses. BioMaster also introduces enhanced control over input and output validation to ensure pipeline consistency and employs a memory management strategy optimized for handling long workflows. Experiments across diverse bioinformatics tasks, including RNA-seq, ChIP-seq, single-cell analysis, and Hi-C processing, demonstrate that BioMaster significantly outperforms existing methods in accuracy, efficiency, and scalability. By addressing key limitations in workflow automation, BioMaster offers a robust solution for modern bioinformatics challenges.Availabilityhttps://github.com/ai4nucleome/BioMasterContactyanlinzhang@hkust-gz.edu.cn
Achievement-Based Differences in Cognitive-Emotional Interplay During Classroom Learning: A Multimodal Analysis with Experience Sampling Method
Authors: Liu Xiaobo , Fu Lan , Yang Zihao , Zhang Zheng , Zhang Yu 
Published: January 2025

AbstractBackgroundThe relationship between cognition and emotion during learning is crucial for educational theories and has been under debate for a long time, from the ancient philosophy to current scientific analyses. However, the relationship may not be uniform and may vary across diverse individual groups.AimsTherefore, this study aims to explore whether the relationship between cognition and emotion varies across different student groups. Furthermore, it examines whether neurophysiological evidence can provide insights into such group differences.SampleThe study involved 22 high school students (11 high-performing and 11 low-performing) over 13 math lessons. Surveys were administered three times during each lesson, yielding a multilevel dataset with 777 samples.MethodsThe experience sampling method was employed to gather data on cognitive and emotional states periodically, as well as their regulations. Simultaneously, multimodal neurophysiological data, including electroencephalograph (EEG), electrodermal activity (EDA), and photoplethysmography (PPG), were collected during classroom learning to analyze the relationship further.ResultsCognitive state, cognitive regulation, emotional state, and emotional regulation were highly correlated overall. In high-performing students, the association was higher than that in low-performing students, especially at the level of within-subject repeated-measures. Multimodal data revealed the common neurophysiological basis of the correlated variation between cognition and emotion, and highlighted different neurophysiological patterns between high and low achievers.ConclusionsThe joint evidence from the experience sampling survey and neurophysiological measures reveals that the cognitive-emotional relationship differs by academic achievement levels, with high achievers revealing a more consistent variation between cognition and emotion. Such co-variation shares a common neurophysiological pattern with features associated with high student-teacher interaction and high concentration, further explaining the group differences.
Assessing predictive accuracy of species abundance models in dynamic systems
Authors: Brown Christopher J. , Buelow Christina , Stuart-Smith Rick D. , Barrett Neville , Edgar Graham , Oh Elizabeth 
Published: January 2025

AbstractCascading human pressures and environmental change are affecting the natural dynamics of animal populations. Forecasting population abundances from time-series data provides an important avenue for testing competing ecological theories, and for supporting conservation planning and sustainable use, yet changing system dynamics may lead to erroneous predictions. Predictions from a model fitted and tested on historical system dynamics may become irrelevant if system dynamics change. Here we describe methods to test forecast skill in a rapidly changing system where model parameters are likely to be non-stationary. We presented two ways to split time-series into training and test datasets so that training data were: 1) contemporary to the testing data (‘modern split’), and 2) not contemporary to the testing data (‘legacy split’). As a case-study, we use animal abundance data from a 30-year time-series from a global warming hotspot. We tested our approach on four temperate reef species with different temporal trends. The case-study and simulation tests confirmed larger forecast errors in legacy split when compared to the modern split. We found that the legacy split had errors that could be more than for times larger for a species that had a rapid collapse in abundance and non-stationary population dynamics. As expected for the species with rapid collapse, the legacy split estimated much higher forecast error than the modern split. Our approach is applicable to a large range of species and systems, including fisheries and threatened species population monitoring, where rapidly changing environments present threats to both the species and management efficacy. Accumulated lessons from across species and systems should shed light on critical generalities that precede broader ecosystem change.
Neural Changes to Transcranial Alternating Current Stimulation in the Gamma Range Over the Left Frontoparietal Network: A Preliminary eLORETA EEG Study
Authors: Lee Tien-Wen , Tramontano Gerald 
Published: January 2025

ABSTRACTApplying transcranial alternating current stimulation (tACS) at 40 Hz to the frontal and parietal regions can improve cognitive dysfunctions. This study aimed to explore the neural changes following transcranial electrical stimulation treatment. Electroencephalography (EEG) recordings were obtained from a cohort of 34 participants with various cognitive impairments before and after 12 sessions of tACS treatment. Alternating currents at 2.0 mA were administered to the electrode positions F3 and P3 for 20 minutes of each session, following the 10-20 EEG convention. Using eLORETA, scalp-recorded signals were reconstructed into cortical current source density (CSD). We then assessed the differences in power and connectivity strength across multiple spectra (delta to gamma). We observed a consistent trend of decreased CSD at the stimulating sites across different spectra, most prominent at beta and gamma bands (P< 0.01). On the contrary, the right hemisphere showed a trend of increased CSD, which was likely mediated by inter-hemispheric rivalry. In addition, the connectivity strength between the left frontal and parietal regions increased significantly (P= 0.017). Artificial injections of tACS would de-synchronize regional oscillation and enhance inter-regional crosstalk. The pattern of neural changes was concordant with our previous tACS reports (5-Hz), suggesting common neural mechanisms driving the neurophysiological effects of tACS.
Genome-scale spatial mapping of the Hodgkin lymphoma microenvironment identifies tumor cell survival factors
Authors: Shanmugam Vignesh , Tokcan Neriman , Chafamo Daniel , Sullivan Sean , Borji Mehdi , Martin Haley , Newton Gail , Nadaf Naeem , Hanbury Saoirse , Barrera Irving , Cable Dylan , Weir Jackson , Ashenberg Orr , Pinkus Geraldine , Rodig Scott , Uhler Caroline , Macosko Evan , Shipp Margaret , Louissaint Abner , Chen Fei , Golub Todd 
Published: January 2025

AbstractA key challenge in cancer research is to identify the secreted factors that contribute to tumor cell survival. Nowhere is this more evident than in Hodgkin lymphoma, where malignant Hodgkin Reed Sternberg (HRS) cells comprise only 1-5% of the tumor mass, the remainder being infiltrating immune cells that presumably are required for the survival of the HRS cells. Until now, there has been no way to characterize the complex Hodgkin lymphoma tumor microenvironment at genome scale. Here, we performed genome-wide transcriptional profiling with spatial and single-cell resolution. We show that the neighborhood surrounding HRS cells forms a distinct niche involving 31 immune and stromal cell types and is enriched in CD4+ T cells, myeloid and follicular dendritic cells, while being depleted of plasma cells. Moreover, we used machine learning to nominate ligand-receptor pairs enriched in the HRS cell niche. Specifically, we identified IL13 as a candidate survival factor. In support of this hypothesis, recombinant IL13 augmented the proliferation of HRS cellsin vitro. In addition, genome-wide CRISPR/Cas9 loss-of-function studies across more than 1,000 human cancer cell lines showed that IL4R and IL13RA1, the heterodimeric partners that constitute the IL13 receptor, were uniquely required for the survival of HRS cells. Moreover, monoclonal antibodies targeting either IL4R or IL13R phenocopied the genetic loss of function studies. IL13-targeting antibodies are already FDA-approved for atopic dermatitis, suggesting that clinical trials testing such agents should be explored in patients with Hodgkin lymphoma.
Endogenous retrovirus-drivenPcgf5plays critical roles in zygotic genome activation and noncanonical imprinting
Authors: Mashiko Satoshi , Yamamoto Takuto , Minami Naojiro , Ikeda Shuntaro , Honda Shinnosuke 
Published: January 2025

SummaryMERVL (murine endogenous retrovirus with leucine tRNA primer) is expressed during zygotic genome activation (ZGA) in mammalian embryos. Here, we show that the Polycomb group ring finger 5 (Pcgf5), a key component of Polycomb repressive complex 1 (PRC1), forms a chimeric transcript with MT2C_Mm, one of the long terminal repeat sequences of MERVL. Knockdown ofPcgf5reduced developmental rates and decreased H3K27me3 and H2AK119ub1 modification during embryogenesis. In addition, not only genes expressed during ZGA but also imprinting genes were upregulated inPcgf5knockdown embryos. Moreover,Pcgf5was involved in the addition of the H3K27me3 modification to the maternalXistregion. This is the first report of a MERVL-regulated transcript regulatingXistexpression in mouse preimplantation embryos. Our results suggest that analysis of chimeric transcripts with MERVL will provide insight into the relationship between ZGA and noncanonical imprinting.
Motor cortical circuits are uniquely impacted by different exercise intensities
Authors: Harroum Nesrine , O’Farrell Amanda , Youssef Layale , Bohbot Louna , Maati Hajar , Joubert Marie , Pageaux Benjamin , Neva Jason L. 
Published: January 2025

ABSTRACTAcute aerobic exercise (AEX) can enhance motor learning and promote neuroplasticity. However, the effect of AEX intensity on primary motor cortex (M1) excitability has not been systematically examined. Hence, the dose-response relationship between AEX intensity and M1 excitability modulation remains unclear. This study investigated the impact of AEX intensity on distinct M1 circuits using transcranial magnetic stimulation (TMS). Thirty right-handed adults underwent four experimental sessions: rest (control), light (LIIT), moderate (MIIT), and high-intensity interval training (HIIT) AEX. AEX intensity was prescribed with the heart rate reserve (HRR) method, and the interval cycling sessions consisted of alternating between 3 min at the target intensity (LIIT: 35% HRR; MIIT: 55% HRR; HIIT: 80% HRR) and 2 min of active recovery (25% HRR) for 20 min total. We performed TMS measures before (Pre), immediately post (Post0), and 20 min post (Post20) AEX/rest to assess modulation of corticospinal excitability and GABAergic inhibition as measured by short interval-intracortical inhibition (SICI). This study found that: (1) HIIT and MIIT increased corticospinal excitability, with HIIT eliciting a sustained increase; and (2) all AEX intensities (LIIT, MIIT and HIIT) decreased SICI, with the greatest sustained reduction following MIIT. Also, there was a greater reduction in GABAergic inhibition when measured with anterior-posterior than posterior-anterior TMS current following MIIT. Collectively, our results demonstrate the impact of HIIT and MIIT to enhance corticospinal excitability and reduce GABAergic inhibition in M1. This study provides evidence for a dose-response effect of AEX intensity on the modulation of distinct motor cortical circuits.KEY POINTS SUMMARYAcute aerobic exercise (AEX) is known to modulate primary motor cortex (M1) excitability, but the effect of AEX intensity is unclear.This study examined the impact of light-, moderate-, and high-intensity interval training (LIIT, MIIT, HIIT) AEX and rest (non-AEX, control) on distinct M1 cortical circuits using transcranial magnetic stimulation (TMS).HIIT induced a sustained increase in M1 output excitability, MIIT induced a transient increase, and LIIT showed no effect.All exercise intensities (LIIT, MIIT and HIIT) decreased GABAergic inhibition, as measured by short-interval intracortical inhibition (SICI), with MIIT showing a sustained decrease.SICI measured with an anterior-to-posterior TMS current demonstrated greater GABAergic disinhibition compared to posterior-to-anterior TMS current following MIIT.This study demonstrates a nuanced dose-response impact of AEX intensity on distinct M1 cortical circuits.
Movement path as an ethological lens into interval timing
Authors: Balcı Fuat , Hernandez Varsovia , Hoşer Ahmet , León Alejandro 
Published: January 2025

AbstractInterval timing behavior is traditionally investigated in operant chambers based on the very focal responses of the subjects (e.g., head entry to the magazine, lever press). These measures are blind to the movement trajectory of the animals and capture only a tiny segment and some-times an idiosyncratic component of the animal’s behavior. In other words, the state of the temporal expectancy is not observable at every time point in the trial. On the other hand, in nature, temporal expectancies guide actions in a much more complex fashion. For instance, an animal might approach a food patch at different degrees as a function of the expected time of food availability (e.g., nectar collection behavior). The current study aimed to investigate interval timing in a more naturalistic fashion by analyzing the movement trajectory of rats infixed time(FT-30s) vs.variable time(VT-30s) schedules in modified open field equipment. We observed a temporally patterned movement inFTbut not in aVTschedule. In theFTschedule, rats moved away from the reward grid after consuming the presented water and were farthest from it for around 15 seconds, after which they started to approach the reward grid again. There was no such temporal patterning of movement trajectory in theVTschedule. Temporal control in theFTschedule was stronger in theWallcompared to theCentercondition. Our results show that movement trajectory may reflect instantaneous temporal expectancy.