bluuebunny/crossref_metadata_2025_split huggingface dataset:
Learning from ingroup experiences changes intergroup impressions
Authors: Zhou Yuqing , Lindström Björn , Soutschek Alexander , Kang Pyungwon , Tobler Philippe N. , Hein Grit 
Published: November 2021

AbstractLiving in multicultural societies, humans form impressions towards individuals of their own social groups (ingroup members) and of different social groups (outgroup members). Some psychological theories predict that intergroup impressions are mainly shaped by experiences with outgroup individuals (“outgroup focused theories”), while other theories predict that ingroup experiences play a dominant role (“ingroup focused theories”). Here we test predictions from these two psychological theories by estimating how intergroup impressions are dynamically shaped when people learn from both ingroup and outgroup experiences. Participants expected to receive painful shocks but were saved from pain by different ingroup or outgroup members in 75% of all trials. We measured neural responses using functional magnetic resonance imaging (fMRI), and participants rated their social closeness as well as impressions towards the ingroup and the outgroup. Behavioral results showed an initial ingroup bias in impression ratings which was significantly reduced over the course of learning. Computational learning models revealed that these changes in intergroup impressions were predicted by the weight given to ingroup prediction errors. The weight of the ingroup prediction error and its effect on intergroup impression change was stronger the more individuals identified with their ingroup. On the neural level, the left inferior parietal lobule (IPL) encoded more negative prediction errors for the ingroup compared to the outgroup. Moreover, stronger weight for ingroup prediction errors was related to increased neural coupling between the left IPL and the anterior insula (AI). This coupling further predicted learning-related changes in intergroup impressions. Together, our work provides computational and neural evidence for “ingroup focused theories”, highlighting the importance of ingroup experiences in shaping social impressions in intergroup settings.
Re-expressing coefficients from regression models for inclusion in a meta-analysis
Authors: Linakis Matthew W. , Van Landingham Cynthia , Gasparini Alessandro , Longnecker Matthew P. 
Published: November 2021

AbstractMeta-analysis poses a challenge when original study results have been expressed in a non-uniform manner, such as when regression results from some original studies were based on a log-transformed key independent variable while in others no transformation was used. Methods of re-expressing regression coefficients to generate comparable results across studies regardless of data transformation have recently been developed. We examined the relative bias of three re-expression methods using simulations and 15 real data examples where the independent variable had a skewed distribution.Regression coefficients from models with log-transformed independent variables were re-expressed as though they were based on an untransformed variable. We compared the re-expressed coefficients to those from a model fit to the untransformed variable. In the simulated and real data, all three reexpression methods usually gave biased results, and the skewness of the independent variable predicted the amount of bias. Meta-analyses stratified by whether the key independent variable was log-transformed and synthesis of the stratified results without meta-analysis appear to be preferable to use of the re-expression methods examined.
Sex and Circuit Specific Dopamine Transporter Regulation Underlies Unique Behavioral Trajectories of Functional SLC6A3 Coding Variation
Authors: Stewart Adele , Mayer Felix P. , Gowrishankar Raajaram , Davis Gwynne L. , Areal Lorena B. , Gresch Paul J. , Katamish Rania M. , Peart Rodeania , Stilley Samantha E. , Spiess Keeley , Rabil Maximilian J. , Diljohn Faakhira A. , Wiggins Angelica E. , Vaughan Roxanne A. , Hahn Maureen K. , Blakely Randy D. 
Published: November 2021

AbstractVirtually all neuropsychiatric disorders display sex differences in prevalence, age of onset, and/or clinical symptomology. In sex-biased disorders, one sex is often suggested to harbor protective mechanisms, rendering them resilient to genetic and/or environmental risk factors. Here, we demonstrate sex-biased molecular, pharmacological and behavioral effects induced by the dopamine (DA) transporter (DAT) coding variant Ala559Val, previously identified in subjects diagnosed with the male-biased disorders attention-deficit/hyperactivity disorder and autism spectrum spectrum disorder. In DAT Val559 mice, we identified sex differences in response to psychostimulants, social behavior, and cognitive traits. We reveal a sex by circuit dissociation in D2-type autoreceptor (D2AR) regulation of DAT wherein D2AR-dependent DAT phosphorylation and trafficking, detectable in the male dorsal striatum, does not occur in females but rather is a property of the ventral striatum, predicting sex-specific changes in behavior. Consequently, we found that a subset of altered behaviors can be normalized using the D2R antagonist sulpiride in DAT Val559 mice. Our studies provide a cogent example of how sex shapes the behavioral trajectory of DA signaling perturbations and identify the sex-dependent, locality-selective capacity for D2AR regulation of DAT as an unrecognized determinant of this trajectory. Rather than identifying one sex as resilient, we find that sex can drive alterative behavioral patterns from shared signaling perturbations that may result in females being underreported. Our work underscores the utility of model systems to study the functional intrusions of rare genetic variation to gain insights into pathways underlying normal and perturbed trait domains associated with common neuropsychiatric conditions.
Multiple hybridization events punctuate the evolutionary trajectory of Malassezia furfur
Authors: Theelen Bart , Mixão Verónica , Ianiri Giuseppe , Pei Zhen Joleen Goh , Dijksterhuis Jan , Heitman Joseph , Dawson Thomas L. , Gabaldón Toni , Boekhout Teun 
Published: November 2021

AbstractMalassezia species are important fungal skin commensals and are part of the normal microbiota of humans and other animals. However, under certain circumstances these fungi can also display a pathogenic behaviour. For example, Malassezia furfur is a common commensal of human skin, and yet is often responsible for skin disorders but also systemic infections. Comparative genomics analysis of M. furfur revealed that some isolates have a hybrid origin, similar to several other recently described hybrid fungal pathogens. Because hybrid species exhibit genomic plasticity that can impact phenotypes, we sought to elucidate the genomic evolution and phenotypic characteristics of M. furfur hybrids in comparison to their parental lineages. To this end, we performed a comparative genomics analysis between hybrid strains and their presumptive parental lineages, and assessed phenotypic characteristics. Our results provide evidence that at least two distinct hybridization events occurred between the same parental lineages, and that the parental strains may have originally been hybrids themselves. Analysis of the mating-type locus reveals that M. furfur has a pseudobipolar mating system, and provides evidence that after sexual liaisons of mating compatible cells, hybridization involved cell-cell fusion leading to a diploid/aneuploid state. This study provides new insights into the evolutionary trajectory of M. furfur and contributes with valuable genomic resources for future pathogenicity studies.ImportanceMalassezia furfur is a common commensal member of human/animal microbiota that is also associated with several pathogenic states. Recent studies report involvement of Malassezia species in Crohn’s disease, a type of inflammatory bowel disease, pancreatic cancer progression, and exacerbation of Cystic fibrosis. A recent genomics analysis of M. furfur revealed the existence of hybrid isolates and identified their putative parental lineages. In this study, we explored the genomic and phenotypic features of these hybrids in comparison to their putative parental lineages. Our results revealed the existence of a pseudobipolar mating system in this species and showed evidence for the occurrence of multiple hybridization events in the evolutionary trajectory of M. furfur. These findings significantly advance our understanding of the evolution of this commensal microbe and are relevant for future studies exploring the role of hybridization in the adaptation to new niches or environments, including the emergence of pathogenicity.
Screening for axon regeneration promoting compounds with human iPSC-derived motor neurons
Authors: Ho Tammy Szu-Yu , Hees J. Tabitha , Xu Zhuqiu , Kawaguchi Riki , Biscola Natalia P. , Taub Daniel G , Chen Kuchuan , Chen Xirui , Barrett Lee B. , Cheng Long , Gabel Christopher V. , Havton Leif A. , Geschwind Daniel H. , Woolf Clifford J. 
Published: November 2021

SummaryCNS neurons do not regenerate after injury, leading to permanent functional deficits. Although sensory and motor neuron axons do regrow after peripheral nerve injury, functional outcome is limited due to the incomplete and slow regrowth. The lack of human-relevant assays suitable for large-scale drug screens has limited neuro-repair therapy discovery. To address this we developed a phenotypic screening strategy using human induced pluripotent stem cell-derived motor neurons to identify axon-regeneration promoting compounds and targets. The screens involve both re-plating human motor neurons on chondroitin sulfate proteoglycans and measuring regeneration responses to laser axotomy in spot cultures, and from them we identified multiple hits that promote injured axon regrowth. The top hit blebbistatin, a non-muscle myosin II inhibitor, accelerated axon regeneration and functional recovery after sciatic nerve injury in vivo. Human “injury in a dish” assays are suitable, therefore, to screen for therapeutic interventions that can induce or accelerate axon regeneration.
Time-of-day influences on skill acquisition and consolidation after physical and mental practices
Authors: Truong Charlène , Hilt Pauline M. , Bouguila Fatma , Bove Marco , Lebon Florent , Papaxanthis Charalambos , Ruffino Célia 
Published: November 2021

AbstractTime-of-day influences both physical and mental performance. Its impact on motor learning is, however, not well established yet. Here, using a finger tapping-task, we investigated the time-of-day effect on skill acquisition (i.e., immediately after a physical or mental practice session) and consolidation (i.e., 24 hours later). Two groups (one physical and one mental) were trained in the morning (10 a.m.) and two others (one physical and one mental) in the afternoon (3 p.m.). We found an enhancement of motor skill following both types of practice, whatever the time of the day, with a better acquisition for the physical than the mental group. Interestingly, there was a better consolidation for both groups when the training session was scheduled in the afternoon. Overall, our results indicate that the time-of-day positively influences motor skill consolidation and thus must be considered to optimize training protocols in sport and clinical domains to potentiate motor (re)learning.
In vivo Correlation Tensor MRI reveals microscopic kurtosis in the human brain on a clinical 3T scanner
Authors: Novello Lisa , Henriques Rafael Neto , Ianuş Andrada , Feiweier Thorsten , Shemesh Noam , Jovicich Jorge 
Published: November 2021

AbstractDiffusion MRI (dMRI) has become one of the most important imaging modalities for noninvasively probing tissue microstructure. Diffusion Kurtosis MRI (DKI) quantifies the degree of non-gaussian diffusion, which in turn has been shown to increase sensitivity towards, e.g., disease and orientation mappings in neural tissue. However, the specificity of DKI is limited as different microstructural sources can contribute to the total diffusional kurtosis, including: variance in diffusion tensor magnitudes (Kiso), variance due to intravoxel diffusion anisotropy (Kaniso), and microscopic kurtosis (μK) related to restricted diffusion and/or microstructural disorder. The latter in particular is typically ignored in diffusion MRI signal modeling as it is assumed to be negligible. Recently, Correlation Tensor MRI (CTI) based on Double-Diffusion-Encoding (DDE) was introduced for kurtosis source separation and revealed non negligible μK in preclinical imaging. Here, we implemented CTI for the first time on a clinical 3T scanner and investigated the kurtosis sources in healthy subjects. A robust framework for kurtosis source separation in humans is introduced, followed by estimation of the relative importance of μK in the healthy brain. Using this clinical CTI approach, we find that μK significantly contributes to total diffusional kurtosis both in gray and white matter tissue but, as expected, not in the ventricles. The first μK maps of the human brain are presented. We find that the spatial distribution of μK provides a unique source of contrast, appearing different from isotropic and anisotropic kurtosis counterparts. We further show that ignoring μK - as done by many contemporary methods based on multiple gaussian component approximation for kurtosis source estimation - biases the estimation of other kurtosis sources and, perhaps even worse, compromises their interpretation. Finally, a twofold acceleration of CTI is discussed in the context of potential future clinical applications. We conclude that CTI has much potential for future in vivo microstructural characterizations in healthy and pathological tissue.HighlightsCorrelation Tensor MRI (CTI) was recently proposed to resolve kurtosis sourcesWe implemented CTI on a 3T scanner to study kurtosis sources in the human brainIsotropic, anisotropic, and microscopic kurtosis sources were successfully resolvedMicroscopic kurtosis (μK) significantly contributes to overall kurtosis in human brainμK provides a novel source of contrast in the human brain in vivo
Drug targeting Nsp1-ribosomal complex shows antiviral activity against SARS-CoV-2
Authors: Afsar Mohammad , Narayan Rohan , Akhtar Md Noor , Rahil Huma , Eswarappa Sandeep M , Tripathi Shashank , Hussain Tanweer 
Published: November 2021

AbstractThe SARS-Cov-2 non-structural protein 1 (Nsp1) contains an N-terminal domain and C-terminal helices connected by a short linker region. The C-terminal helices of Nsp1 (Nsp1-C-ter) from SARS-Cov-2 bind in the mRNA entry channel of the 40S ribosomal subunit and block the entry of mRNAs thereby shutting down host protein synthesis. Nsp1 suppresses the host immune function and is vital for viral replication. Hence, Nsp1 appears to be an attractive target for therapeutics. In this study, we have in silico screened Food and Drug Administration (FDA)-approved drugs against Nsp1-C-ter and find that montelukast sodium hydrate binds to Nsp1-C-ter with a binding affinity (KD) of 10.8±0.2 μM in vitro and forms a stable complex with it in simulation runs with a binding energy of −76.71±8.95 kJ/mol. The drug also rescues the inhibitory effect of Nsp1 in host protein synthesis as demonstrated by the expression of firefly luciferase reporter gene in cells. Importantly, montelukast sodium hydrate demonstrates antiviral activity against SARS-CoV-2 with reduced viral replication in HEK cells expressing ACE2 and Vero-E6 cells. We therefore propose montelukast sodium hydrate may help in combatting SARS-CoV-2 infection.
Steady state flux balance analysis game
Authors: Iyengar Garud , Perry Mitch 
Published: November 2021

AbstractFlux balance analysis (FBA) for microbial communities often assumes a global objective function that all species cooperatively maximize in addition to maximizing their own growth. Combining community FBA with dynamic FBA to understand the time course and steady states of communities typically entails discretizing time and solving a community FBA model at each time point, a time-intensive process. We propose a dynamic community FBA model where species compete for metabolites to grow off of without needing to cooperate to maximize a community-level objective. An efficient method for computing steady state community compositions is provided, as well as methods for determining the stability of a steady state community to perturbations in biomass and invasion by species outside the community. The model and methods are applied to a model of four E. coli mutants with elements of competition (for shared metabolites) and cooperation (via mutants being auxotrophic for metabolites exported by other mutants), as well as a nine-species gut microbiome model.
Population genomics analysis with RAD, reprised: Stacks 2
Authors: Rivera-Colón Angel G. , Catchen Julian 
Published: November 2021

AbstractRestriction enzymes have been one of the primary tools in the population genetics toolkit for fifty years, being coupled with each new generation of technology to provide a more detailed view into the genetics of natural populations. Restriction site-Associated DNA protocols, which joined enzymes with short-read sequencing technology have democratized the field of population genomics, providing a means to assay the underlying alleles in scores of populations. More than ten years on, the technique has been widely applied across the tree of life and served as the basis for many different analysis techniques. Here, we provide a detailed protocol to conduct a RAD analysis from experimental design to de novo analysis – including parameter optimization – as well as reference-based analysis, all in Stacks version 2, which is designed to work with paired-end reads to assemble RAD loci up to 1000 nucleotides in length. The protocol focuses on major points of friction in the molecular approaches and downstream analysis, with special attention given to validating experimental analyses. Finally, the protocol provides several points of departure for further analysis.
A flexible method for estimating tip diversification rates across a range of speciation and extinction scenarios
Authors: Vasconcelos Thais , O’Meara Brian C. , Beaulieu Jeremy M. 
Published: November 2021

AbstractEstimates of diversification rates at the tips of a phylogeny provide a flexible approach for correlation analyses with multiple traits and to map diversification rates in space, while also avoiding the uncertainty of deep time rate reconstructions. Available methods for tip rate estimation make different assumptions, and thus their accuracy usually depends on characteristics of the underlying model generating the tree. Here we introduce MiSSE, a trait-free, state-dependent speciation and extinction approach that can be used to estimate varying speciation, extinction, net-diversification, turnover rates, and extinction fraction at the tips of the tree. We compare the accuracy of tip rates inferred by MiSSE against similar methods and demonstrate that, due to certain characteristics of the model, the error is generally low across a broad range of speciation and extinction scenarios. MiSSE can be used alongside regular phylogenetic comparative methods in trait related diversification hypotheses, and we also describe a simple correction to avoid pseudoreplication from sister tips in analyses of independent contrasts. Finally, we demonstrate the capabilities of MiSSE, with a renewed focus on classic comparative methods, to examine correlation between plant height and turnover rates in eucalypts, a species-rich lineage of flowering plants.
Plasticity in Ligand Recognition at Somatostatin Receptors
Authors: Robertson Michael J. , Meyerowitz Justin G. , Panova Ouliana , Borrelli Kenneth , Skiniotis Georgios 
Published: November 2021

AbstractSomatostatin is a signaling peptide that plays a pivotal and wide-ranging role in physiologic processes relating to metabolism and growth through its actions at somatostatin receptors (SSTRs). Members of the somatostatin receptor subfamily, particularly SSTR2, are key drug targets for neuroendocrine neoplasms, with several synthetic peptide agonists currently in clinical use. Here, we show the cryogenic electron microscopy (cryo-EM) structures of active-state SSTR2 in complex with heterotrimeric Gi protein and either the endogenous ligand SST14 or the FDA-approved drug octreotide.Complemented by biochemical assays and molecular dynamics simulations, these structures reveal key details of ligand recognition, receptor activation, and subtype-selectivity at somatostatin receptors. We find that SSTR ligand recognition is highly diverse, as demonstrated by ligand-induced conformational changes in ECL2, substantial sequence divergence across subtypes in extracellular regions, and loss of ligand binding upon several structurally homologous substitutions between subtypes. Despite this complexity, we rationalize several previously described sources of SSTR subtype selectivity and identify an additional key interaction for SSTR2/3/5 specific binding. These results shed light on the basis of ligand recognition by somatostatin receptors and provide valuable insights for structure-based drug discovery at these targets.
Validating the wearable MUSE headset for EEG spectral analysis and Frontal Alpha Asymmetry
Authors: Cannard Cédric , Wahbeh Helané , Delorme Arnaud 
Published: November 2021

AbstractEEG power spectral density (PSD), the individual alpha frequency (IAF) and the frontal alpha asymmetry (FAA) are all EEG spectral measures that have been widely used to evaluate cognitive and attentional processes in experimental and clinical settings, and that can be used for real-world applications (e.g., remote EEG monitoring, brain-computer interfaces, neurofeedback, neuromodulation, etc.). Potential applications remain limited by the high cost, low mobility, and long preparation times associated with high-density EEG recording systems. Low-density wearable systems address these issues and can increase access to larger and diversified samples. The present study tested whether a low-cost, 4-channel wearable EEG system (the MUSE) could be used to quickly measure continuous EEG data, yielding similar frequency components compared to research a grade EEG system (the 64-channel BIOSEMI Active Two). We compare the spectral measures from MUSE EEG data referenced to mastoids to those from BIOSEMI EEG data with two different references for validation. A minimal amount of data was deliberately collected to test the feasibility for real-world applications (EEG setup and data collection being completed in under 5 min). We show that the MUSE can be used to examine power spectral density (PSD) in all frequency bands, the individual alpha frequency (IAF; i.e., peak alpha frequency and alpha center of gravity), and frontal alpha asymmetry. Furthermore, we observed satisfying internal consistency reliability in alpha power and asymmetry measures recorded with the MUSE. Estimating asymmetry on PAF and CoG frequencies did not yield significant advantages relative to the traditional method (whole alpha band). These findings should advance human neurophysiological monitoring using wearable neurotechnologies in large participant samples and increase the feasibility of their implementation in real-world settings.