bluuebunny/crossref_metadata_2025_split huggingface dataset:
Preceding anti-spike IgG levels predicted risk and severity of COVID-19 during the Omicron-dominant wave in Santa Fe city, Argentina
Authors: Eberhardt Ayelen T. , Simoncini Melina , Piña Carlos , Galoppo Germán , Parachú-Marco Virginia , Racca Andrea , Arce Sofía , Viotto Evangelina , Facelli Florencia , Valli Florencia , Botto Cecilia , Scarpa Leonardo , Junges Celina , Palavecino Cintia , Beccaria Camila , Sklar Diego , Mingo Graciela , Genolet Alicia , de Toro Mónica Muñoz , Aimar Hugo , Marignac Verónica , Bossio Juan Carlos , Armando Gustavo , Fernández Hugo , Beldomenico Pablo M. 
Published: May 2022

AbstractThe SARS-CoV-2 Omicron variant has increased infectivity and immune escape compared with previous variants, and caused massive COVID-19 waves globally. Despite a vast majority (∼90%) of the population of Santa Fe city, Argentina, had been vaccinated and/or had been infected by SARS-CoV-2 by the arrival of Omicron, the epidemic wave that followed was by far the largest one experienced in the city. A serosurvey conducted prior to the arrival of Omicron allowed to assess the acquired humoural defences preceding the wave and to evaluate associations with infection risk and severity during the wave. A very large proportion of the 1455 sampled individuals had immunological memory against COVID-19 at the arrival of Omicron (almost 90%), and about half (48.9%) had high anti-Spike IgG levels (>200 UI/ml). The antibody titres were strongly associated with the number of vaccine shots and the vaccine platform received, and also depended markedly on prior COVID-19 diagnosis and the days elapsed since last antigen exposure (vaccine shot or natural infection). Following-up 514 participants provided real-world data linking antibody levels with protection against COVID-19 during a period of high risk of exposure to an immune-escaping highly transmissible variant. Pre-wave antibody titres were strongly associated with COVID-19 incidence and severity of symptoms during the wave. Also, receiving a vaccine shot during the follow-up period reduced the COVID-19 risk drastically (15-fold). These results highlight the importance of maintaining high defences through vaccination anticipating or during a period of high risk of exposure to immune-escaping variants.
Accelerated Aging Mediates the Associations of Unhealthy Lifestyles with Cardiovascular Disease, Cancer, and Mortality: Two Large Prospective Cohort Studies
Authors: Li Xueqin , Cao Xingqi , Zhang Jingyun , Fu Jinjing , Mohedaner Mayila , Danzengzhuoga  , Sun Xiaoyi , Yang Gan , Yang Zhenqing , Kuo Chia-Ling , Chen Xi , Cohen Alan A , Liu Zuyun 
Published: May 2022

AbstractWith a well-validated aging measure – Phenotypic Age Acceleration (PhenoAgeAccel), this study examined whether and to what extent aging mediates the associations of unhealthy lifestyles with adverse health outcomes. Data were from 405,944 adults (40-69 years) from UK Biobank (UKB) and 9,972 adults (20-84 years) from US National Health and Nutrition Examination Surveys (NHANES). The mediation proportion of PhenoAgeAccel in associations of unhealthy lifestyles with incident cardiovascular disease, incident cancer, and all-cause mortality were 20.0%, 17.8%, and 26.6% (P values <0.001) in UKB, respectively. The mediation proportion of PhenoAgeAccel in associations of lifestyles with cancer mortality, and all-cause mortality were 25.7%, and 35.2% (P values <0.05) in NHANES, respectively. This study demonstrated that accelerated aging partially mediated the associations of lifestyles with adverse health outcomes in UK and US populations. The findings reveal a novel pathway and the potential of geroprotective programs in mitigating health inequality in late-life beyond lifestyle interventions.
A Novel Hybrid Classical- Quantum Network to Detect Epileptic Seizures
Authors: Sameer Mustafa , Gupta Bharat 
Published: May 2022

AbstractBackgroundMachine learning (ML) has paved the way for scientists to develop effective computer-aided diagnostic (CAD) systems. In recent years, epileptic seizure detection using Electroencephalogram (EEG) data and deep learning models has gained much attention. However, in deep learning networks, the bottleneck is a large number of learnable parameters.MethodIn this study, a novel approach comprising a 1D-Convolutional Neural Network (CNN) model for feature extraction followed by classical-quantum hybrid layers for classification purpose has been proposed. The proposed technique has only 745 learning parameters, which is the least reported to date.ResultThe proposed method has achieved a maximum accuracy, sensitivity, and specificity of 100% for binary classification on the Bonn EEG dataset. In addition, the noise robustness of the proposed model has also been checked. To the best of the author’s knowledge, this is the first study to employ quantum machine learning (QML) to detect epileptic seizures.ConclusionThus, the developed hybrid system will help neurologists to detect seizures in online mode.
Temporally dissociable mechanisms of spatial, feature, and motor selection during working memory-guided behavior
Authors: Ester Edward , Weese Rachel 
Published: May 2022

AbstractWorking Memory (WM) is a capacity- and duration-limited system that forms a temporal bridge between fleeting sensory phenomena and possible actions. But how are the contents of WM used to guide behavior? A recent high-profile study reported evidence for simultaneous access to WM content and linked motor plans during WM-guided behavior, challenging serial models where task-relevant WM content is first selected and then mapped on to a task-relevant motor response. However, the task used in that study was not optimized to distinguish the selection of spatial versus non-spatial visual information stored in memory, nor to distinguish whether or how the chronometry of selecting non-spatial visual information stored in memory might differ from the selection of linked motor plans. Here, we revisited the chronometry of spatial, feature, and motor selection during WM-guided behavior using a task optimized to disentangle these processes. Concurrent EEG and eye position recordings revealed clear evidence for temporally dissociable spatial, feature, and motor selection mechanisms during this task, partially replicating yet also extending previous findings. More generally, our data reveal the existence of multiple WM selection mechanisms that belie conceptualizations of WM-guided behavior based on purely serial or parallel visuomotor processing.
Evidence for different greater-persistence strategies under lower and higher challenge for alcohol in female rats
Authors: De Oliveira Sergio Thatiane , Darevsky David , de Paula Soares Vanessa , de Cassia Albino Maryelle , Maulucci Danielle , Wean Sarah , Hopf Frederic W. 
Published: May 2022

ABSTRACTProblem alcohol drinking is a substantial social and economic burden. Studies show that the misuse of alcohol is increasing in women, and that women can face higher consequences from alcohol exposure, but females have historically been understudied. Thus, there is considerable interest in understanding potential sex-different and -similar cognitive/emotional strategies, and underlying mechanisms, for alcohol responding, which would inform more effective, personalized treatments. Here, we used large cohorts of adult Wistar rats (28 females, 30 males) to provide robust assessment of potential sex differences in responding for alcohol-only and under compulsion-like drinking with moderate or higher challenge (since intake despite negative consequences can be a major obstacle to human treatment). Females had similar total licking but higher intake for all drinking conditions. However, females had significantly longer bouts under alcohol-only and moderate challenge, but not higher challenge. Further, under higher challenge, females retained several aspects of responding not seen in males, including more efficient lick volume and earlier onset of longer bouts. In addition, females overall licked slightly faster, but licking speed averaged within-bout showed no sex differences, and female intake level under alcohol-only and moderate challenge was unlinked from licking speed (unlike males, where slower licking predicted lower intake). We interpret these differences as greater persistence-like responding but not vigor per se in females, and with different strategies under lower versus higher challenge. Finally, drinking levels did not differ across the estrous cycle, although ovariectomy reduced alcohol-only and moderate-challenge intake. Together, while many aspects were sex-similar, suggesting some common drinking mechanisms, there was clear evidence for (perhaps more nuanced) sex-different alcohol strategies, which might make an outsized contribution to excessive drinking since women can have more drinking problems. Thus, our studies provide important context for future work examining sex differences in pathological drinking mechanisms.
Narrowband gamma oscillations propagate and synchronize throughout the mouse thalamocortical visual system
Authors: Shin Donghoon , Peelman Kayla , Rosario Joseph Del , Haider Bilal 
Published: May 2022

SummaryRhythmic oscillations of neural activity permeate sensory systems. Studies in the visual system propose that broadband gamma oscillations (30 – 80 Hz) facilitate neuronal communication underlying visual perception. However, broadband gamma oscillations within and across visual areas show widely varying frequency and phase, providing constraints for synchronizing spike timing. Here, we analyzed data from the Allen Brain Observatory and performed new experiments that show narrowband gamma (NBG) oscillations (50 – 70 Hz) propagate and synchronize throughout the awake mouse thalamocortical visual system. Lateral geniculate (LGN) neurons fired with millisecond precision relative to NBG phase in primary visual cortex (V1) and multiple higher visual areas (HVAs). NBG in HVAs depended upon retinotopically aligned V1 activity, and neurons that fired at NBG frequencies showed enhanced functional connectivity within and across visual areas. Remarkably, LGN ON versus OFF neurons showed distinct and reliable spike timing relative to NBG oscillation phase across LGN, V1, and HVAs. Taken together, NBG oscillations may serve as a novel substrate for precise coordination of spike timing in functionally distinct subnetworks of neurons spanning multiple brain areas during awake vision.
Whole-genome scanning reveals selection mechanisms in epipelagic Chaetoceros diatom populations
Authors: Nef Charlotte , Madoui Mohammed-Amin , Pelletier Éric , Bowler Chris 
Published: May 2022

AbstractDiatoms form a diverse and abundant group of photosynthetic protists that are essential players in marine ecosystems. However, the microevolutionary structure of their populations remains poorly understood, particularly in polar regions. Exploring how closely related diatoms adapt to different oceanic ecoregions is essential given their short generation times, which may allow rapid adaptations to different environments; and their prevalence in marine regions dramatically impacted by climate change, such as the Arctic and Southern Oceans. Here, we address genetic diversity patterns in Chaetoceros, the most abundant diatom genus and one of the most diverse, using 11 metagenome-assembled genomes (MAGs) reconstructed from Tara Oceans metagenomes. Genome-resolved metagenomics on these MAGs confirmed a prevalent distribution of Chaetoceros in the Arctic Ocean with lower dispersal in the Pacific and Southern Oceans as well as in the Mediterranean Sea. Single nucleotide variants identified within the different MAG populations allowed us to draw a first landscape of Chaetoceros genetic diversity and to reveal an elevated genetic structure in some Arctic Ocean populations with FST levels ranging up to ≥ 0.2. Genetic differentiation patterns of closely related Chaetoceros populations appear to be correlated with abiotic factors rather than with geographic distance. We found clear positive selection of genes involved in nutrient availability responses, in particular for iron (e.g., ISIP2a, flavodoxin), silicate and phosphate (e.g., polyamine synthase), that were further confirmed in Chaetoceros transcriptomes. Altogether, these results provide new insights and perspectives into diatom metapopulation genomics through the integration of metagenomic and environmental data.
IMPROVE-DD: Integrating Multiple Phenotype Resources Optimises Variant Evaluation in genetically determined Developmental Disorders
Authors: Aitken Stuart , Firth Helen V , Wright Caroline F , Hurles Matthew E , FitzPatrick David R , Semple Colin A. 
Published: May 2022

SummaryDiagnosing rare developmental disorders using genome-wide sequencing data commonly necessitates review of multiple plausible candidate variants, often using ontologies of categorical clinical terms. We show that Integrating Multiple Phenotype Resources Optimises Variant Evaluation in Developmental Disorders (IMPROVE-DD) by incorporating additional classes of data commonly available to clinicians and recorded in health records. In doing so, we quantify the distinct contributions of gender, growth, and development in addition to Human Phenotype Ontology (HPO) terms, and demonstrate added value from these readily-available information sources. We use likelihood ratios for nominal and quantitative data and propose a novel classifier for HPO terms in this framework. This Bayesian framework results in more robust diagnoses. Using data systematically collected in the DDD study, we considered 77 genes with pathogenic/likely pathogenic variants in >10 probands. All genes showed at least a satisfactory prediction by ROC when testing on training data (AUC≥0.6), and HPO terms were the best individual predictor for the majority of genes, though a minority (13/77) of genes were better predicted by other phenotypic data types. Overall, classifiers based upon multiple integrated phenotypic data sources performed better than those based upon any individual source, and importantly, integrated models produced notably fewer false positives. Finally, we show that IMPROVE-DD models with good predictive performance on cross-validation can be constructed from relatively few cases. This suggests new strategies for candidate gene prioritisation, and highlights the value of systematic clinical data collection to support diagnostic programmes.
Optical Genome Mapping Identifies a Novel Pediatric Embryonal Tumor Subtype with a ZNF532-NUTM1 Fusion
Authors: Bornhorst Miriam , Eze Augustine , Bhattacharya Surajit , Putnam Ethan , Almira-Suarez M. Isabel , Rossi Christopher , Kambhampati Madhuri , Almalvez Miguel , Turner Joyce , Myseros John , Vilain Eric , Packer Roger J. , Nazarian Javad , Rood Brian , Barseghyan Hayk 
Published: May 2022

AbstractMolecular characteristics of pediatric brain tumors have not only allowed for tumor subgrouping but have introduced novel treatment options for patients with specific tumor alterations. Therefore, an accurate histologic and molecular diagnosis is critical for optimized management of all pediatric patients with brain tumors, including central nervous system embryonal tumors. We present a case where optical genome mapping identified a ZNF532-NUTM1 fusion in a patient with a unique tumor best characterized histologically as a central nervous system embryonal tumor with rhabdoid features. Additional analyses including immunohistochemistry for NUT protein, methylation array, whole genome, and RNA-sequencing was done to confirm the presence of the fusion in the tumor. This is the first description of a pediatric patient with a ZNF532-NUTM1 fusion, yet the histology of this tumor is similar to that of adult cancers with ZNF-NUTM1 fusions and other NUTM1-fusion positive brain tumors reported in literature. Although rare, the distinct pathology and underlying molecular characteristics of these tumors separate them from other embryonal tumors. Therefore, the NUTM-rearrangement appears to define a novel subgroup of pediatric central nervous system embryonal tumors with rhabdoid/epithelioid features that may have a unique response to treatment. Screening for a NUTM1-rearrangement should be considered for all patients with unclassified central nervous system tumors with rhabdoid features to ensure accurate diagnosis so this can ultimately inform therapeutic management for these patients.
Spatial memory training reverses GirK channels modulation in the transgenic APPSw,Ind Alzheimer’s disease mouse model
Authors: Temprano-Carazo Sara , Contreras Ana , Saura Carlos A. , Navarro-López Juan , Jiménez-Díaz Lydia 
Published: May 2022

AbstractAlzheimer’s disease (AD) is a dementia characterized by progressive memory decline and neurodegeneration caused by the accumulation of amyloid-β (Aβ) peptides. Last findings point to an imbalance between excitatory and inhibitory neurotransmission as the initial impairment in early stages, and the hippocampus as one of the most susceptible brain areas.The G-protein-gated inwardly rectifying potassium (GirK) channel has been proposed as a potential target to restore excitatory/inhibitory balance in amyloidosis models. Moreover, cognitive training may counteract early AD symptoms, although its effect on GirK channels remains unknown.Here, the effect of genotype, age, and training in a hippocampal-dependent memory task on the protein expression of GirK subunits and modulators were studied using APPSw,Ind mice. Results showed a reduction of GirK2 expression as well as an increased expression of SNX27 in the hippocampus of 6-month-old APPSw,Ind mice. Training in a memory task restored GirK2 and SNX27 levels. Thus, the effect of Aβ on GirK2 could account for the excitatory/inhibitory imbalance transmission found in AD models, and training in a cognitive hippocampal-dependent task reverses this effect and lessens early Aβ-dependent AD deficits.Summary statementAβ decreases hippocampal GirK2 expression in APPSw,Ind mice, which could contribute to early hyperexcitability found in Alzheimer’s disease models. Training in spatial memory tasks has shown to counteract this reduction.
Connectivity by the Frontal Aslant Tract (FAT) explains local functional specialization of the superior and inferior frontal gyri in humans while choosing predictive over reactive strategies: a tractography-guided TMS study
Authors: Tagliaferri Marco , Giampiccolo Davide , Parmigiani Sara , Amorosino Gabriele , Avesani Paolo , Cattaneo Luigi 
Published: May 2022

ABSTRACTPredictive and reactive behaviors represent two mutually exclusive strategies for successfully completing a sensorimotor task. It is thought that predictive actions are based on the medial premotor system, in the superior frontal gyrus (SFG) and reactive stimulus-response behaviors rely on a lateral premotor system, in the inferior frontal gyrus (IFG). The frontal aslant tract (FAT), a white matter tract connecting SFG and IFG, is a possible neural substrate of the predictive/reactive interactions. We used diffusion-weighted imaging (DWI) of 17 male and female healthy human volunteers, to dissect 3 sub-bundles of fibers belonging to the left FAT (bundles 1, 2 and 3), arising ventrally from 1) the ventral precentral gyrus, 2) midway between the PCG and pars opercularis (POp) and 3) the POp and terminating dorsally in 3 different parts of the SFG, in a caudal-rostral order. We applied online transcranial magnetic stimulation (TMS) to 6 spots, corresponding to the medial and lateral terminations of bundles 1-3 during the fixed-duration set period of a delayed reaction task, that can be solved using a predictive (anticipatory) strategy or with a reactive strategy. Results showed that TMS changed the frequency of predictive/reactive strategies only when applied over 2 spots, the SFG and IFG terminations of bundle 2. Importantly, the effects of TMS were opposite when applied to the SFG or to the IFG. Our data show that the SFG and the IFG have opposite roles in producing predictive or reactive behavior and that reciprocal integration or competition is probably mediated by the FAT.Significance StatementAs is well-known by athletes at starting blocks, interaction with the world can occur with a predictive strategy (anticipating a GO-signal) or a reactive strategy (waiting for the GO-signal to be manifest) and they are mutually exclusive. Here we showed, by using non-invasive brain stimulation (TMS), that two specific cortical regions in the superior frontal gyrus (SFG) and the inferior frontal gyrus (IFG) have opposite roles in facilitating a predictive or a reactive strategy. Importantly these two very distant regions but with highly interconnected functions are specifically connected by a small white matter bundle, which probably mediates the competition between predictive and reactive strategies. More generally, we show that the implementing anatomical connectivity in TMS studies strongly reduces spatial noise.
Lipid nanoparticle topology regulates endosomal escape and delivery of RNA to the cytoplasm
Authors: Zheng Lining , Bandara Sarith R. , Leal Cecilia 
Published: May 2022

AbstractRNA therapeutics have the potential to resolve a myriad of diseases caused by gene deficiency. Lipid nanoparticles (LNPs) are one of the most successful RNA delivery systems. However, expanding their application hinges on the discovery of next generation LNPs with high potency, cyto-specific targeting, and low side effects. Overcoming the difficulty of releasing cargo from endocytosed LNPs remains a significant hurdle. The endosomal escape of viral and non-viral nanoparticles relies on the topological transformation of membrane fusion pore formation followed by RNA translocation into the cytosol. In this study we show that LNP-RNA nanostructure modulates the energetic cost of LNP fusion with a target membrane. The inclusion of a new class of structurally-active lipids leads to superior LNP endosomal fusion, fast evasion of endosomal entrapment, and efficacious RNA delivery. Specifically, bicontinuous cubic RNA-LNPs, cuboplexes, have significantly higher endosomal escape rates and deliver more RNA compared to regular lamellar LNPs.
Effects of altered cellular ultrastructure on energy metabolism in diabetic cardiomyopathy – an in-silico study
Authors: Ghosh Shouryadipta , Guglielmi Giovanni , Orfanidis Ioannis , Spill Fabian , Hickey Anthony , Hanssen Eric , Rajagopal Vijay 
Published: May 2022

SummaryDiabetic cardiomyopathy is a leading cause of heart failure in diabetes. At the cellular level, diabetic cardiomyopathy leads to altered mitochondrial energy metabolism and cardiomyocyte ultrastructure. We combined electron microscopy and computational modelling to understand the impact of diabetes induced ultrastructural changes on cardiac bioenergetics.We collected transverse micrographs of multiple control and type I diabetic rat cardiomyocytes using electron microscopy. Micrographs were converted to finite element meshes, and bioenergetics was simulated over them using a biophysical model. The simulations also incorporated depressed mitochondrial capacity for oxidative phosphorylation and creatine kinase reactions to simulate diabetes induced mitochondrial dysfunction.Analysis of micrographs revealed a 14% decline in mitochondrial area fraction in diabetic cardiomyocytes, and an irregular arrangement of mitochondria and myofibrils. Simulations predicted that this irregular arrangement, coupled with depressed activity of mitochondrial creatine kinase enzymes, leads to large spatial variation in ADP/ATP profile of diabetic cardiomyocytes. However, when spatially averaged, myofibrillar ADP/ATP ratios of a cardiomyocyte do not change with diabetes. Instead, average concentration of inorganic phosphate rises by 40% due to lower mitochondrial area fraction and dysfunction in oxidative phosphorylation. These simulations indicate that a disorganized cellular ultrastructure negatively impacts metabolite transport in diabetic cardiomyopathy.