bluuebunny/crossref_metadata_2025_split huggingface dataset:
Discrete Time Modeling of Stock-Recruit Relationships with Life-History Stanzas
Authors: Frank Anna-Simone , Schaarschmidt Ute , Nash Richard D. M. , Subbey Sam 
Published: March 2024

AbstractThe stock-recruit relationship is a foundational concept in fisheries science, bridging the connection between parental populations (stock) and progeny (recruits). Traditional approaches describe this relationship using closedform analytical functions, which represent only a restricted subset of the broader class of possibilities. This paper advocates for a novel approach that integrates discrete time modeling with a life-history cycle framework, incorporating distinct stanzas and developmental processes. By breaking down the life cycle into identifiable stages, we capture the step-wise progression of life history traits and the factors influencing recruitment outcomes. Through numerical simulations, we explore the advantages of this approach, including complexity handling, dynamic behavior modeling, and scenario exploration. Our simulation results show that we are able to generate a broad spectrum of stock-recruit relationships (including the traditional ones), which best reflect variability observed in nature. We demonstrate how this framework allows for the identification of critical stages, and integration of various factors that influence recruitment. This holistic approach enhances our comprehension of the intricate interactions shaping stock-recruit relationships and advances our understanding of sustainable population dynamics.HighlightsA novel multi-stage life-cycle model is presented.Model simulations reveal three different Stock-Recruitment (SR) patterns.Our approach contributes to enhanced understanding of SR relationships.
A Systematic Assessment of Robustness in CNS Safety Pharmacology
Authors: Reiber Maria , Stirling Helen , Ahuis Tim P. , Arias Washington , Aulehner Katharina , Dreßler Ute , Kas Martien J.H. , Kela Johanna , Kerker Kimberly , Kuosmanen Tarja , Lorenz Helga , Pennington Alexander T. , von Rüden Eva-Lotta , Schauerte Heike , Seiffert Isabel , Talbot Steven R. , Torturo Christina , Virtanen Sami , Waldron Ann-Marie , Ramboz Sylvie , Potschka Heidrun 
Published: March 2024

AbstractIrwin tests are key preclinical study elements for characterizing drug-induced neurological side effects. This multicenter study aimed to assess the robustness of Irwin tests across multinational sites during three stages of protocol harmonization. The projects were part of the EQIPD framework (EnhancedQuality inPreclinicalData,https://quality-preclinical-data.eu/), aiming to increase success rates in transition from preclinical testing to clinical application. Female and male NMRI mice were assigned to one of three groups (vehicle, 0.1 mg/kg MK-801, 0.3 mg/kg MK-801). Irwin scores were assessed at baseline and multiple times following injection of MK-801, a non-competitive NMDA antagonist, using local protocols (stage 1), a shared protocol with harmonized environmental design (stage 2), and fully harmonized Irwin scoring protocols (stage 3). The analysis based on the four functional domains (motor, autonomic, sedation, and excitation) revealed substantial data variability in stages 1 and 2. Although there was still marked overall heterogeneity between sites in stage 3 after complete harmonization of the Irwin scoring scheme, heterogeneity was only moderate within functional domains. When comparing treatment groups vs. vehicle, we found large effect sizes in the motor domain and subtle to moderate effects in the excitation-related and autonomic domain. The pronounced interlaboratory variability in Irwin datasets for the CNS-active compound MK-801 needs to be carefully considered by companies and experimenters when making decisions during drug development. While environmental and general study design had a minor impact, the study suggests that harmonization of parameters and their scoring can limit variability and increase robustness.
Role of Posterior Medial Thalamus in the Modulation of Striatal Circuitry and Choice Behavior
Authors: Yonk Alex J. , Linares-García Ivan , Pasternak Logan , Juliani Sofia E. , Gradwell Mark A. , George Arlene J. , Margolis David J. 
Published: March 2024

SummaryThe posterior medial (POm) thalamus is heavily interconnected with sensory and motor circuitry and is likely involved in behavioral modulation and sensorimotor integration. POm provides axonal projections to the dorsal striatum, a hotspot of sensorimotor processing, yet the role of POm-striatal projections has remained undetermined. Using optogenetics with slice electrophysiology, we found that POm provides robust synaptic input to direct and indirect pathway striatal spiny projection neurons (D1- and D2-SPNs, respectively) and parvalbumin-expressing fast spiking interneurons (PVs). During the performance of a whisker-based tactile discrimination task, POm-striatal projections displayed learning-related activation correlating with anticipatory, but not reward-related, pupil dilation. Inhibition of POm-striatal axons across learning caused slower reaction times and an increase in the number of training sessions for expert performance. Our data indicate that POm-striatal inputs provide a behaviorally relevant arousal-related signal, which may prime striatal circuitry for efficient integration of subsequent choice-related inputs.
A basic framework governing splice-site choice in eukaryotes
Authors: Dent Craig I , Prodic Stefan , Balakrishnan Aiswarya , Georges James , Chhabra Aaryan , Mukherjee Sourav , Coutts Jordyn , Gitonobel Michael , Sarwade Rucha D , Rosenbluh Joseph , D’Amato Mauro , Das Partha P , Guo Ya-Long , Fournier-Level Alexandre , Burke Richard , Sureshkumar Sridevi , Powell David , Balasubramanian Sureshkumar 
Published: March 2024

SUMMARYChanges in splicing are observed between cells, tissues, organs, individuals, and species. These changes can mediate phenotypic variation ranging from flowering time differences in plants to genetic diseases in humans. However, the genomic determinants of splicing variation are largely unknown. Here, we quantified the usage of individual splice-sites and uncover extensive variation between individuals (genotypes) in Arabidopsis, Drosophila and Humans. We used this robust quantitative measure as a phenotype and mapped variation in splice-site usage using Genome-Wide Association Studies (GWAS). By carrying out more than 130,000 GWAS with splice-site usage phenotypes, we reveal genetic variants associated with differential usage of specific splice-sites. Our analysis conclusively shows that most of the common, genetically controlled variation in splicing iscisand there are no majortranshotspots in any of the three analyzed species. High-resolution mapping allowed us to determine genome-wide patterns that govern splice-site choice. We reveal that the variability in the intronic hexamer sequence (GT[N]4or [N]4AG) differentiates intrinsic splice-site strength and is among the primary determinants of splice-site choice. Experimental analysis validates the primary role for intronic hexamer sequences in conferring splice-site decisions. Transcriptome analyses in diverse species across the tree of life reveals that hexamer rankings explains splice-site choices from yeast to plants to humans, forming the basic framework of the splicing code in eukaryotes.
Broad therapeutic benefit of myosin inhibition in hypertrophic cardiomyopathy
Authors: Sen-Martín Laura , Fernández-Trasancos Ángel , López-Unzu Miguel Á. , Pathak Divya , Ferrarini Alessia , Labrador-Cantarero Verónica , Sánchez-Ortiz David , Pricolo María Rosaria , Vicente Natalia , Velázquez-Carreras Diana , Sánchez-García Lucía , Nicolás-Ávila Jose Ángel , Sánchez-Díaz María , Schlossarek Saskia , Cussó Lorena , Desco Manuel , Villalba-Orero María , Guzmán-Martínez Gabriela , Calvo Enrique , Barriales-Villa Roberto , Vázquez Jesús , Sánchez-Cabo Fátima , Hidalgo Andrés , Carrier Lucie , Spudich James A. , Ruppel Kathleen M. , Alegre-Cebollada Jorge 
Published: March 2024

ABSTRACTMyosin inhibitor mavacamten is the only targeted treatment available for hypertrophic cardiomyopathy (HCM), a disease caused by hundreds of genetic variants that affect mainly sarcomeric myosin and its negative regulator cardiac myosin-binding protein C (cMyBP-C, encoded byMYBPC3). Here, we have examined whether the reported limited efficacy of mavacamten in a fraction of HCM patients can result from dissimilar HCM pathomechanisms triggered by different genetic variants, a scenario particularly relevant forMYBPC3-associated HCM. To this aim, we have generated knock-in mice including missense pathogenic variant cMyBP-C p.R502W, which, different from patients who carry truncations in the protein, develop progressive pathogenic myocardial remodeling in the absence of alterations of cMyBP-C levels and localization. Mechanistically, we find that mutation R502W reduces the binding affinity of cMyBP-C for myosin without inducing a shift towards more active myosin conformations as observed when cMyBP-C levels are reduced. Despite these diverging molecular alterations, we show that mavacamten blunts myocardial remodeling both in R502W and cMyBP-C-deficient, knock-out hearts. These beneficial effects are accompanied by improved tolerance to exercise only in R502W animals. Hence, our results indicate that myosin inhibition is effective to treat HCM caused by both truncating and missense variants inMYBPC3regardless of the primary pathomechanisms they elicit.
Primate V2 Receptive Fields Derived from Anatomically Identified Large-Scale V1 Inputs
Authors: Hassanpour Mahlega S , Merlin Sam , Federer Frederick , Zaidi Qasim , Angelucci Alessandra 
Published: March 2024

ABSTRACTIn the primate visual system, visual object recognition involves a series of cortical areas arranged hierarchically along the ventral visual pathway. As information flows through this hierarchy, neurons become progressively tuned to more complex image features. The circuit mechanisms and computations underlying the increasing complexity of these receptive fields (RFs) remain unidentified. To understand how this complexity emerges in the secondary visual area (V2), we investigated the functional organization of inputs from the primary visual cortex (V1) to V2 by combining retrograde anatomical tracing of these inputs with functional imaging of feature maps in macaque monkey V1 and V2. We found that V1 neurons sending inputs to single V2 orientation columns have a broad range of preferred orientations, but are strongly biased towards the orientation represented at the injected V2 site. For each V2 site, we then constructed a feedforward model based on the linear combination of its anatomically-identified large-scale V1 inputs, and studied the response proprieties of the generated V2 RFs. We found that V2 RFs derived from the linear feedforward model were either elongated versions of V1 filters or had spatially complex structures. These modeled RFs predicted V2 neuron responses to oriented grating stimuli with high accuracy. Remarkably, this simple model also explained the greater selectivity to naturalistic textures of V2 cells compared to their V1 input cells. Our results demonstrate that simple linear combinations of feedforward inputs can account for the orientation selectivity and texture sensitivity of V2 RFs.
QuartPlotR: A quarternary phase diagram tool
Authors: Veluchamy Alaguraj , Bowler Chris 
Published: March 2024

AbstractMotivationLarge scale studies involving exploratory data analysis and important key discoveries require platform that provides comprehensive visualization. Density distribution analysis across multiple datasets is intuitive and summarization, visualization could reveal several biological information. Integration and visualization of sequence and annotation features in the context of composition of genomic mutation, microbiota, population are significantly challenging.ResultsWe propose a simple, novel strategy of visualization of multidimensional datasets involving multiple layers of data distribution which are interconnected. Also, we have implemented this phase diagram in an easy-to-use tool QuartPlotR, a resource for plotting charts from different genomic datasets. A generic data access and plotting framework has been designed and this is implemented as an R package.Availabilityhttps://github.com/AlagurajVeluchamy/QuartPlotR.Contactalaguraj.veluchamy@stjude.orgSupplementary informationSupplementary data are available atBioinformaticsonline.
Toxin-glycolipid interactions measured by imaging surface plasmon resonance on artificial membranes predicts diffusion behavior and lipid dependence of binding to cells
Authors: Lehnert Sarah , Yildiz Umit Hakan , Haustein Natalie , Li Enlin , Matysik Artur , Oglęcka Kamila , Rashid Rafi , Boschke Elke , Liedberg Bo , Wohland Thorsten , Kraut Rachel 
Published: March 2024

AbstractMembrane-protein interactions mediate cellular invasion by toxins, and are thought to involve organized plasma membrane lipid domains, often containing glycolipids, other sphingolipids, and/or cholesterol. Here, we characterize an isolated glycolipid-interacting domain of the tetanus toxin heavy chain (Hc) as a fluorescently labelled peptide, TeNT46, and describe its membrane dynamics and binding characteristics on artificial bilayers and cellular membranes. We show that this novel ganglioside-interacting probe TeNT46 retains the glycolipid binding preferences of the parent toxin, using imaging-SPR (iSPR) on a micro-patterned hybrid bilayer surface. On live cell membranes, using fluorescence correlation spectroscopic (FCS) diffusion measurements to compare TeNT46 to the well-studied GM1-binding toxin CTxB, we find that both probes display ordered domain-binding characteristics, but distinct cholesterol and sphingolipid dependencies. Strikingly, the contrasting lipid requirements of TeNT46 from those of CTxB in cells are predicted by their iSPR binding preferences on hybrid synthetic membranes. Based on the combined findings from iSPR and FCS, we propose a model for toxin-membrane interaction whereby a unique lipid constellation determines optimum binding for each probe independently of lateral confinement, which is more generally imposed by cholesterol. Our resulting understanding of the specific lipid requirements of these toxin targets and their dynamics in cell membranes could be important for the future design of preventive membrane-based nano-decoys and cell-delivery tools.
Unusual lineage plasticity revealed by YY1 knockout in pro-B cells
Authors: Banerjee Sarmistha , Sanyal Sulagna , Hodawadekar Suchita , Naiyer Sarah , Bano Nasreen , Banerjee Anupam , Rhoades Joshua , Dong Dawei , Allman David , Atchison Michael L. 
Published: March 2024

AbstractDuring B cell development, cells progress through multiple developmental stages with the pro-B cell stage defining commitment to the B cell lineage. YY1 is a ubiquitous transcription factor that is capable of both activation and repression functions. We find here that knockout of YY1 at the pro-B cell stage eliminates B lineage commitment. YY1 knockout pro-B cells can generate T lineage cellsin vitrousing the OP9- DL4 feeder system, as well asin vivoafter injection into sub-lethally irradiated Rag1-/-mice. These T lineage-like cells lose their B lineage transcript profile and gain a T cell lineage profile. Single cell-RNA-seq experiments showed that as YY1 knockout pro-B cells transition into T lineage cells, various cell clusters adopt transcript profiles representing a multiplicity of hematopoietic lineages indicating unusual lineage plasticity. Given the ubiquitous nature of YY1 and its dual activation and repression functions, YY1 likely regulates commitment in multiple cell lineages.
Providing Insights into Health Data Science Education through Artificial Intelligence
Authors: Rohani Narjes , Gal Kobi , Gallagher Michael , Manataki Areti 
Published: March 2024

AbstractBackgroundHealth Data Science (HDS) is a novel interdisciplinary field that integrates biological, clinical, and computational sciences with the aim of analysing clinical and biological data through the utilisation of computational methods. Training healthcare specialists who are knowledgeable in both health and data sciences is highly required, important, and challenging. Therefore, it is essential to analyse students’ learning experiences through artificial intelligence techniques in order to provide both teachers and learners with insights about effective learning strategies and to improve existing HDS course designs.MethodsWe applied artificial intelligence methods to uncover learning tactics and strategies employed by students in an HDS massive open online course with over 3,000 students enrolled. We also used statistical tests to explore students’ engagement with different resources (such as reading materials and lecture videos) and their level of engagement with various HDS topics.ResultsWe found that students in HDS employed four learning tactics, such as actively connecting new information to their prior knowledge, taking assessments and practising programming to evaluate their understanding, collaborating with their classmates, and repeating information to memorise. Based on the employed tactics, we also found three types of learning strategies, including low engagement (Surface learners), moderate engagement (Strategic learners), and high engagement (Deep learners), which are in line with well-known educational theories. The results indicate that successful students allocate more time to practical topics, such as projects and discussions, make connections among concepts, and employ peer learning.ConclusionsWe applied artificial intelligence techniques to provide new insights into HDS education. Based on the findings, we provide pedagogical suggestions not only for course designers but also for teachers and learners that have the potential to improve the learning experience of HDS students.
Mobile EEG for Neurourbanism Research - What Could Possibly Go Wrong? A Critical Review with Guidelines
Authors: Gramann Klaus 
Published: March 2024

AbstractBased on increasing incidents of mental ill-health associated with living in dense urban environments, the field of Neurourbanism developed rapidly, aiming at identifying and improving urban factors that impact the health of city dwellers. Neurourbanism and the closely related field of Neuro-Architecture have seen a surge in studies using mobile electroencephalography (EEG) to investigate the impact of the built and natural environment on human brain activity moving from the laboratory into the real world. This trend predominantly arises from the ready availability of affordable and portable consumer hardware, which not only guarantees operational simplicity but also frequently incorporates automated data analysis functions. This significantly streamlines the process of EEG data acquisition, analysis, and interpretation, seemingly challenging the necessity of specialized expertise in the method of EEG or neurosciences in general. As a consequence, numerous studies in the field of Neurourbanism have used such off-the-shelf systems in laboratory and real-world experimental protocols including active movement of participants through the environment. However, the recording and analysis of EEG data entails numerous requisites, the disregard of which may culminate in errors during data acquisition, processing, and subsequent interpretation, potentially compromising the scientific validity of the outcomes. The often relatively low number of electrodes offered by affordable and portable consumer EEG systems further restricts specific analyses approaches to the low-dimensional EEG data. Crucially, a large part of Neurourbanism studies used black-box analyses provided by such consumer systems or incorrectly applied complex data-driven analyses methods that are incompatible with the recorded low-dimensional data. The current manuscript delineates the prerequisites concerning EEG hardware and analytical methodologies applicable to stationary and mobile EEG protocols, whether conducted within a controlled laboratory environment or in real-world settings. It conducts a comprehensive review of EEG studies within the domain of Neurourbanism and Neuro-Architecture, assessing their adherence to these prerequisites. The findings reveal severe deficiencies in the utilization of hardware and data processing methods, thereby rendering these studies unsuitable for scientific scrutiny. Consequently, the present paper provides guidelines for the selection of EEG hardware and analytical strategies for researchers engaged in mobile EEG recordings, be it within a laboratory or real-world context, aimed at steering future investigations in the field of Neurourbanism and Neuro-Architecture.
Overexpression of Sirohydrochlorin Ferrochelatase Boosts Nitrogen Sulfur and Carbon Utilization inArabidopsis thaliana
Authors: Joshi Naveen C. , Tripathy Baishnab C. 
Published: March 2024

AbstractNitrogen deficiency in the soil is a significant agronomic problem, and the application of nitrogenous fertilizers to the soil has environmental concerns, such as sodic soil and the emission of greenhouse gases. To increase the nutrient use efficiency, the cDNA ofAtSirBcoding for sirohydrochlorin ferrochelatase, responsible for Fe insertion to the tetrapyrrole moiety of sirohydrochlorin, was overexpressed inArabidopsis thalianaunder the control of 35S promoter for increased synthesis of siroheme. The siroheme is a cofactor for the plastidic enzymes nitrite reductase (NiR) and sulfite reductase (SiR), which reduces nitrite and sulfite to ammonium and sulfide, respectively. A three-step process including methylation, oxidation, and ferro-chelation produces siroheme from uroporphyrinogen III, an intermediate of chlorophyll (Chl) biosynthesis. TheNiRandSiRgene expression and protein abundance increased in the over-expressers due to the increased AtSirB protein level. It resulted in an increase in N and S assimilation and enhanced protein content of over-expressers. Conversely, the total protein content decreased in antisense plants due to reduced NR and NiR activities.AtSirBover-expressers had higher protein and Chl contents and increased photosynthetic rate and biomass. Under N and S limitation, the protein, Chl, and photosynthetic electron transport rates inAtSirBover-expressers were higher than in WT. Results demonstrate that theSirBthat hijacks uroporphyrinogen from the chlorophyll biosynthesis pathway is a crucial player in N and S assimilation. The siroheme is limiting for efficient nitrate and sulfate reduction and utilization. SirB could be genetically manipulated to increase crop productivity for sustainable agriculture.