bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of kinship composition on social structure
Authors: Pereira André S. , Pavez-Fox Melissa A. , Hart Jordan D. A. , Negron-Del Valle Josué E. , Phillips Daniel , Casanova Catarina , De Moor Delphine , Brent Lauren J. N. 
Published: January 2024

AbstractThe relatedness between group members is a potential driver of variation in social structure. Relatedness predicts biases in partner choice and formation of strong relationships among group members. As such, groups that differ in their percentage of non-kin dyads, i.e., in their kinship composition, should therefore differ in the structure of their social networks. Yet the relationship between kinship composition and social structure remains unclear. Here, we used long-term social and pedigree data from a population of rhesus macaques to investigate the relationship between kinship composition and the connectivity, cohesion, potential for transmission and social differentiation of the social networks of adult female macaques. We found no evidence that the social structure of groups composed of greater proportion of unrelated females differ from that of groups with a lower proportion of non-kin. To investigate this unexpected finding, we built agent-based models parameterised with the empirical data to further explore (1) the expected relationship between kinship composition and social structure and (2) why we did not find such a relationship in the empirical data. Agent-based models showed that kinship composition can influence social structure in populations similar to the one studied, but that this effect may only be detectable with a sample size even larger than ours (19 group-years) and with greater variance in kinship composition (proportion of non-kin varied between 0.830-0.922 in the empirical data). The relationship between kinship composition and social structure might be more apparent when comparing data from species that differ strongly in their social organisation, translating into marked differences in kinship composition. This further emphasises the importance of reporting existing and future kinship composition data to deepen our understanding of the evolution of sociality and highlights the potential of agent-based models to better understand empirical results.
Comparative analysis of multiplexed in situ gene expression profiling technologies
Authors: Hartman Austin , Satija Rahul 
Published: January 2024

AbstractThe burgeoning interest in in situ multiplexed gene expression profiling technologies has opened new avenues for understanding cellular behavior and interactions. In this study, we present a comparative benchmark analysis of six in situ gene expression profiling methods, including both commercially available and academically developed methods, using publicly accessible mouse brain datasets. We find that standard sensitivity metrics, such as the number of unique molecules detected per cell, are not directly comparable across datasets due to substantial differences in the incidence of off-target molecular artifacts impacting specificity. To address these challenges, we explored various potential sources of molecular artifacts, developed novel metrics to control for them, and utilized these metrics to evaluate and compare different in situ technologies. Finally, we demonstrate how molecular false positives can seriously confound spatially-aware differential expression analysis, requiring caution in the interpretation of downstream results. Our analysis provides guidance for the selection, processing, and interpretation of in situ spatial technologies.
Synaptic Theory of Working Memory for Serial Order
Authors: Mongillo Gianluigi , Tsodyks Misha 
Published: January 2024

AbstractPeople effortlessly remember short, but otherwise arbitrary, sequences of familiar stimuli over a brief period of time. This deceptively mundane ability is core for purposeful behavior and cognition. Surprisingly, however, it remains largely unexplained. Here, we propose that both the stimuli and their order of occurrence are encoded by transient synaptic enhancement over multiple time scales. To substantiate this proposal, we extend our previously-proposed synaptic theory of Working Memory (WM) to include synaptic augmentation besides short-term depression and facilitation, consistently with experimental observations. Like facilitation, augmentation builds up with repetitive activation but persists for much longer. We find that the long time scales associated with augmentation naturally lead to the emergence of a “primacy gradient” in the synaptic efficacies that can be used to reconstruct the order of presentation at recall. The novel theory accounts for prominent features of the behavior of humans recalling lists of items, makes testable predictions and, intriguingly, suggests that WM capacity limitations result from a failure in retrieving, rather than storing, information. Taken together, our results advance the understanding of the neuronal mechanisms underpinning the encoding of serial order and offer novel insights into the origin of WM capacity.
Targeting thePlasmodium falciparumUCHL3 ubiquitin hydrolase using chemically constrained peptides
Authors: King Harry R. , Bycroft Mark , Nguyen Thanh-Binh , Kelly Geoff , Vinogradov Alexander A. , Rowling Pamela J. E. , Stott Katherine , Ascher David B. , Suga Hiroaki , Itzhaki Laura S. , Artavanis-Tsakonas Katerina 
Published: January 2024

AbstractThe ubiquitin-proteasome system is essential to all eukaryotes and has been shown to be critical to parasite survival as well, includingPlasmodium falciparum, the causative agent of the deadliest form of malarial disease. Despite the central role of the ubiquitin-proteasome pathway to parasite viability across its entire life-cycle, specific inhibitors targeting the individual enzymes mediating ubiquitin attachment and removal do not currently exist. The ability to disruptP. falciparumgrowth at multiple developmental stages is particularly attractive as this could potentially prevent both disease pathology, caused by asexually dividing parasites, as well as transmission which is mediated by sexually differentiated parasites. The deubiquitinating enzyme PfUCHL3 is an essential protein, transcribed across both human and mosquito developmental stages. PfUCHL3 is considered hard to drug by conventional methods given the high level of homology of its active site to human UCHL3 as well as to other UCH domain enzymes. Here, we apply the RaPID mRNA display technology and identify constrained peptides capable of binding to PfUCHL3 with nanomolar affinities. The two lead peptides were found to selectively inhibit the deubiquitinase activity of PfUCHL3 versus HsUCHL3. NMR spectroscopy revealed that the peptides do not act by binding to the active site but instead block binding of the ubiquitin substrate. We demonstrate that this approach can be used to target essential protein-protein interactions within thePlasmodiumubiquitin pathway, enabling the application of chemically constrained peptides as a novel class of anti-malarial therapeutics.
Distinct alterations in white matter properties and organization related to maternal treatment initiation in neonates exposed to HIV but uninfected
Authors: Magondo Ndivhuwo , Meintjes Ernesta M. , Warton Fleur L. , Little Francesca , van der Kouwe Andre J.W. , Laughton Barbara , Jankiewicz Marcin , Holmes Martha J. 
Published: January 2024

AbstractHIV exposed-uninfected (HEU) infants and children are at risk of developmental delays as compared to uninfected unexposed (HUU) populations. The effects of exposure toin uteroHIV and ART regimens on the HEU the developing brain are not well understood.In a cohort of 2-week-old newborns, we used diffusion tensor imaging (DTI) tractography and graph theory to examine the influence of HIV and ART exposurein uteroon neonate white matter integrity and organisation. The cohort included HEU infants born to mothers who started ART before conception (HEUpre) and after conception (HEUpost), as well as HUU infants from the same community. We investigated HIV exposure and ART duration group differences in DTI metrics (fractional anisotropy (FA) and mean diffusivity (MD)) and graph measures across white matter.We found increased MD in white matter connections involving the thalamus and limbic system in the HEUpregroup compared to HUU. We further identified reduced nodal efficiency in the basal ganglia. Within the HEUpostgroup, we observed reduced FA in cortical-subcortical and cerebellar connections as well as decreased transitivity in the hindbrain area compared to HUU.Overall, our analysis demonstrated distinct alterations in white matter integrity related to the timing of maternal ART initiation that influence regional brain network properties.
Activity-dependent expression ofFezf2regulates inhibitory synapse formation in pyramidal cells
Authors: Kroon Tim , Sanalidou Stella , Maeso Patricia , Garces Teresa , Yang Han , Rico Beatriz 
Published: January 2024

AbstractThe function of the cerebral cortex relies on the precise integration of diverse neuronal populations during development, which is regulated by dynamic fine-tuning mechanisms maintaining the balance between excitation and inhibition. For instance, the development of excitatory pyramidal cells is simultaneously and precisely counterbalanced by the formation of inhibitory synapses during the maturation of neuronal circuits. Although this process relies on neuronal activity, different types of pyramidal cells likely respond to changes in activity through the expression of cell-specific genes. However, the molecular programs underlying the activity-dependent recruitment of inhibition by distinct types of pyramidal cells in the neocortex are unknown. Here, we combined neuronal activity manipulation with ribosome-associated mRNA profiling of layer 5 (L5) extra-telencephalic (ET) cells to address this question in mice. We unveiled a novel function for the selector geneFezf2as an activity-dependent transcription factor controlling the parvalbumin inputs onto L5 ET neurons. One of the downstream effectors of FEZF2 shaping the formation of inhibitory synapses onto L5 ET pyramidal cells is the cell-surface molecule cadherin 22. Our study identifies activity-dependent factors regulating the cell type-specific assembly of inhibitory synapses onto pyramidal cells.
Node centrality in MEG resting-state networks co-varies with neurotransmitter receptor and transporter density
Authors: Siebenhühner Felix , Palva J. Matias , Palva Satu 
Published: January 2024

SummaryNeuronal oscillations are central mechanisms in the regulation of neuronal processing and communication (Deco et al., 2011; Fries, 2015; S. Palva & Palva, 2012; Siegel et al., 2012; Singer, 1999), but the relationship between the emergent inter-areal synchronization of oscillations and their underlying synaptic and neuromodulatory mechanisms - the dynome - has remained poorly understood (Kopell et al., 2014).While oscillations are largely generated by fast synaptic neurotransmission among pyramidal cells and interneurons (Traub et al., 2004), these microcircuits are subject to slower neuromodulation in a frequency- and region-specific manner (Batista-Brito et al., 2018; Roopun et al., 2010). While the efferent connections, receptor densities, and neurotransmitter reuptake regulation of neuromodulatory systems are highly heterogeneous across the cortical mantle (Avery & Krichmar, 2017; Deco et al., 2017; Hansen et al., 2022), it has remained unresolved how this variability shapes inter-areal connectivity of neuronal oscillations.Here, we used source-reconstructed human magnetoencephalography (MEG) data to assess how the centrality of brain areas (nodes) in large-scale networks of phase synchrony and amplitude correlations covaries with neurotransmitter receptor and transporter densities. Node centrality strongly covaried with receptor and transporter densities in a coupling- and frequency-specific manner both at the level of individual receptors and transporters and that of principal components.In delta, theta, and gamma frequencies, node centrality in phase-synchronization networks covaried positively, and in high-alpha and beta bands negatively, with dopaminergic, GABA, NMDA, muscarinic, and most serotonergic receptor densities. In amplitude-correlation networks, node centrality in delta and gamma bands covaried positively, and in theta to beta bands negatively, with most receptor and transporter densities. These results establish the contribution of neurotransmitter receptor and transporter densities for shaping connectivity of neuronal oscillations in the human brain and demonstrate a link between coupling of neuronal oscillations with the underlying biological details.
The relationship between gut and nasopharyngeal microbiome composition can predict the severity of COVID-19
Authors: Martin-Castaño Benita , Diez-Echave Patricia , García-García Jorge , Hidalgo-García Laura , Ruiz-Malagon Antonio Jesús , Molina-Tijeras José Alberto , Rodríguez-Sojo Maria Jesús , Redruello Anaïs , Martínez-Zaldívar Margarita , Mota Emilio , Cobo Fernando , Alvarez-Estevez Marta , García Federico , Morales-García Concepción , Merlos Silvia , García-Flores Paula , Colmenero-Ruiz Manuel , Hernandez-Quero José , Nuñez María , Rodríguez-Cabezas Maria Elena , Carazo Ángel , Martín Javier , Morón Rocío , Rodríguez-Nogales Alba , Gálvez Julio 
Published: January 2024

ABSTRACTCoronavirus disease 2019 (COVID-19) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that displays great variability in clinical phenotype. Many factors have been described to be correlated with its severity, and microbiota could play a key role in the infection, progression, and outcome of the disease. SARS-CoV-2 infection has been associated with nasopharyngeal and gut dysbiosis and higher abundance of opportunistic pathogens. To identify new prognostic markers for the disease, a multicenter prospective observational cohort study was carried out in COVID-19 patients divided into three cohorts based on symptomatology: mild (n=24), moderate (n=51), and severe/critical (n=31). Faecal and nasopharyngeal samples were taken, and the microbiota was analyzed. Linear discriminant analysis identifiedM. salivarium,P. dentalis, andH. parainfluenzaeas biomarkers of severe COVID-19 in nasopharyngeal microbiota, whileP. biviaandP. timonensiswere defined in faecal microbiota. Additionally, a connection between faecal and nasopharyngeal microbiota was identified, with a significant ratio betweenP. timonensis(faeces) andP. dentalisandM. salivarium(nasopharyngeal) abundances found in critically ill patients. This ratio could serve as a novel prognostic tool for identifying severe COVID-19 cases.
Neuronal microstructural changes in the human brain are associated with neurocognitive aging
Authors: Singh Kavita , Barsoum Stephanie , Schilling Kurt G , An Yang , Ferrucci Luigi , Benjamini Dan 
Published: January 2024

AbstractGray matter (GM) alterations play a role in aging-related disorders like Alzheimer’s disease and related dementias, yet MRI studies mainly focus on macroscopic changes. Although reliable indicators of atrophy, morphological metrics like cortical thickness lack the sensitivity to detect early changes preceding visible atrophy. Our study aimed at exploring the potential of diffusion MRI in unveiling sensitive markers of cortical and subcortical age-related microstructural changes and assessing their associations with cognitive and behavioral deficits. We leveraged the Human Connectome Project-Aging cohort that included 707 unimpaired participants (394 female; median age = 58, range = 36–90 years) and applied the powerful mean apparent diffusion propagator model to measure microstructural parameters, along with comprehensive behavioral and cognitive test scores. Both macro- and microstructural GM characteristics were strongly associated with age, with widespread significant microstructural correlations reflective of cellular morphological changes, reduced cellular density, increased extracellular volume, and increased membrane permeability. Importantly, when correlating MRI and cognitive test scores, our findings revealed no link between macrostructural volumetric changes and neurobehavioral performance. However, we found that cellular and extracellular alterations in cortical and subcortical GM regions were associated with neurobehavioral performance. Based on these findings, it is hypothesized that increased microstructural heterogeneity and decreased neurite orientation dispersion precede macrostructural changes, and that they play an important role in subsequent cognitive decline. These alterations are suggested to be early markers of neurocognitive performance that may distinctly aid in identifying the mechanisms underlying phenotypic aging and subsequent age-related functional decline.
Through the lens of causal inference: Decisions and pitfalls of covariate selection
Authors: Chen Gang , Cai Zhengchen , Taylor Paul A. 
Published: January 2024

AbstractThe critical importance of justifying the inclusion of covariates is a facet often overlooked in data analysis. While the incorporation of covariates typically follows informal guidelines, we argue for a comprehensive exploration of underlying principles to avoid significant statistical and interpretational challenges. Our focus is on addressing three common yet problematic practices: the indiscriminate lumping of covariates, the lack of rationale for covariate inclusion, and the oversight of potential issues in result reporting. These challenges, prevalent in neuroimaging models involving covariates such as reaction time, demographics, and morphometric measures, can introduce biases, including overestimation, underestimation, masking, sign flipping, or spurious effects.Our exploration of causal inference principles underscores the pivotal role of domain knowledge in guiding co-variate selection, challenging the common reliance on statistical measures. This understanding carries implications for experimental design, model-building, and result interpretation. We draw connections between these insights and reproducibility concerns, specifically addressing the selection bias resulting from the widespread practice of strict thresholding, akin to the logical pitfall associated with “double dipping.” Recommendations for robust data analysis involving covariates encompass explicit research question statements, justified covariate inclusions/exclusions, centering quantitative variables for interpretability, appropriate reporting of effect estimates, and advocating a “highlight, don’t hide” approach in result reporting. These suggestions are intended to enhance the robustness, transparency, and reproducibility of covariate-driven analyses, encompassing investigations involving consortium datasets such as ABCD and UK Biobank. We discuss how researchers can use a transparent depiction of the covariate relationships to enhance the ethos of open science and promote research reproducibility.
Measuring the Stoichiometry of Microbial Parasite Infrapopulations One Cell at a Time using Energy Dispersive Spectroscopy
Authors: Narr Charlotte F , Binger Scott , Sedlacek Erin , Anderson Bianca , Shoemaker Grace , Stanley Adrienne , Stokoski Madison , Hall Ed 
Published: January 2024

AbstractProgress in the field of ecological stoichiometry has demonstrated that the outcome of ecological interactions can often be predicteda prioribased on the nutrient ratios (e.g., carbon: nitrogen: phosphorus, C:N:P) of interacting organisms. However, the challenges of accurately measuring the nutrient content of active parasites within hosts has limited our ability to rigorously apply ecological stoichiometry to host-parasite systems. Traditional nutrient analyses require high parasite biomasses, often preventing individual-level analyses. This prevents researchers from estimating variation in the nutrient content of individual parasites within a single host infrapopulation, a critical factor that could define how the ecology of the parasite affects the host-parasite interaction.Here, we explain how energy dispersive technology, a technique currently used to measure the elemental content of free-living microbes, can be adapted for parasitic microbial infrapopulations. We demonstrate the power of accurately quantifying the biomass stoichiometry of individual microbial parasites sampled directly from individual hosts.Using this approach we show that the stoichiometric composition of two microbial parasites capable of infecting the same host are stoichiometrically distinct and respond to host diet quality differently. We also demonstrate that characteristics of the stoichiometric trait distributions of these infrapopulations were important predictors of host fecundity, a proxy for virulence in this system, and better predictors of parasite load than the mean parasite stoichiometry or our parasite and diet treatments alone.EDS provides a rigorous tool for applying ecological stoichiometry to host-parasite systems and enables researchers to explore the nutritional physiology of host-parasite interactions at a scale that is more relevant to the ecology and evolution of the system than traditional nutrient analyses. Here we demonstrate that this level of resolution provides useful insights into the diet-dependent physiology of microbial parasites and their hosts. We anticipate that this improved level of resolution has the potential to elucidate a range of eco-evo interactions in host-parasite systems that were previously unobservable.
Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study
Authors: Coffman Christian , Feczko Eric , Larsen Bart , Tervo-Clemmens Brenden , Conan Gregory , Lundquist Jacob T. , Houghton Audrey , Moore Lucille A. , Weldon Kimberly , McCollum Rae , Perrone Anders J. , Fayzullobekova Begim , Madison Thomas J. , Earl Eric , Dominguez Oscar Miranda , Fair Damien A. , Basu Saonli 
Published: January 2024

AbstractHeritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (>50%).