bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revealing the relevant spatiotemporal scale underlying whole-brain dynamics
Authors: Kobeleva Xenia , López-González Ane , Kringelbach Morten L. , Deco Gustavo 
Published: September 2020

AbstractThe brain rapidly processes and adapts to new information by dynamically switching between activity in whole-brain functional networks. In this whole-brain modelling study we investigate the relevance of spatiotemporal scale in whole-brain functional networks. This is achieved through estimating brain parcellations at different spatial scales (100-900 regions) and time series at different temporal scales (from milliseconds to seconds) generated by a whole-brain model fitted to fMRI data. We quantify a fingerprint of healthy dynamics quantifying the richness of the dynamical repertoire at each spatiotemporal scale by computing the entropy of switching activity between whole-brain functional networks. The results show that the optimal relevant spatial scale is around 300 regions and a temporal scale of around 150 milliseconds. Overall, this study provides much needed evidence for the relevant spatiotemporal scales needed to make sense of neuroimaging data.
Discovery of a Novel Inhibitor of Coronavirus 3CL Protease for the Potential Treatment of COVID-19
Authors: Boras Britton , Jones Rhys M. , Anson Brandon J. , Arenson Dan , Aschenbrenner Lisa , Bakowski Malina A. , Beutler Nathan , Binder Joseph , Chen Emily , Eng Heather , Hammond Holly , Hammond Jennifer , Haupt Robert E. , Hoffman Robert , Kadar Eugene P. , Kania Rob , Kimoto Emi , Kirkpatrick Melanie G. , Lanyon Lorraine , Lendy Emma K. , Lillis Jonathan R. , Logue James , Luthra Suman A. , Ma Chunlong , Mason Stephen W. , McGrath Marisa E. , Noell Stephen , Obach R. Scott , O’Brien Matthew N. , O’Connor Rebecca , Ogilvie Kevin , Owen Dafydd , Pettersson Martin , Reese Matthew R , Rogers Thomas F. , Rossulek Michelle I. , Sathish Jean G. , Shirai Norimitsu , Steppan Claire , Ticehurst Martyn , Updyke Lawrence W. , Weston Stuart , Zhu Yuao , Wang Jun , Chatterjee Arnab K. , Mesecar Andrew D. , Frieman Matthew B. , Anderson Annaliesa S. , Allerton Charlotte 
Published: September 2020

AbstractCOVID-19 caused by the SARS-CoV-2 virus has become a global pandemic. 3CL protease is a virally encoded protein that is essential across a broad spectrum of coronaviruses with no close human analogs. The designed phosphate prodrug PF-07304814 is metabolized to PF-00835321 which is a potent inhibitorin vitroof the coronavirus family 3CL pro, with selectivity over human host protease targets. Furthermore, PF-00835231 exhibits potentin vitroantiviral activity against SARS-CoV-2 as a single agent and it is additive/synergistic in combination with remdesivir. We present the ADME, safety,in vitro, andin vivoantiviral activity data that supports the clinical evaluation of this compound as a potential COVID-19 treatment.
SARS-CoV-2 infection severity is linked to superior humoral immunity against the spike
Authors: Guthmiller Jenna J. , Stovicek Olivia , Wang Jiaolong , Changrob Siriruk , Li Lei , Halfmann Peter , Zheng Nai-Ying , Utset Henry , Stamper Christopher T. , Dugan Haley L. , Miller William D. , Huang Min , Dai Ya-Nan , Nelson Christopher A. , Hall Paige D. , Jansen Maud , Shanmugarajah Kumaran , Donington Jessica S. , Krammer Florian , Fremont Daved H. , Joachimiak Andrzej , Kawaoka Yoshihiro , Tesic Vera , Madariaga Maria Lucia , Wilson Patrick C. 
Published: September 2020

ABSTRACTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a global pandemic. The antigen specificity and kinetics of the antibody response mounted against this novel virus are not understood in detail. Here, we report that subjects with a more severe SARS-CoV-2 infection exhibit a larger antibody response against the spike and nucleocapsid protein and epitope spreading to subdominant viral antigens, such as open reading frame 8 and non-structural proteins. Subjects with a greater antibody response mounted a larger memory B cell response against the spike, but not the nucleocapsid protein. Additionally, we revealed that antibodies against the spike are still capable of binding the D614G spike mutant and cross-react with the SARS-CoV-1 receptor binding domain. Together, this study reveals that subjects with a more severe SARS-CoV-2 infection exhibit a greater overall antibody response to the spike and nucleocapsid protein and a larger memory B cell response against the spike.
High performance machine learning models can fully automate labeling of camera trap images for ecological analyses
Authors: Whytock Robin , Świeżewski Jędrzej , Zwerts Joeri A. , Bara-Słupski Tadeusz , Pambo Aurélie Flore Koumba , Rogala Marek , Bahaa-el-din Laila , Boekee Kelly , Brittain Stephanie , Cardoso Anabelle W. , Henschel Philipp , Lehmann David , Momboua Brice , Opepa Cisquet Kiebou , Orbell Christopher , Pitman Ross T. , Robinson Hugh S. , Abernethy Katharine A. 
Published: September 2020

AbstractEcological data are increasingly collected over vast geographic areas using arrays of digital sensors. Camera trap arrays have become the ‘gold standard’ method for surveying many terrestrial mammals and birds, but these arrays often generate millions of images that are challenging to process. This causes significant latency between data collection and subsequent inference, which can impede conservation at a time of ecological crisis. Machine learning algorithms have been developed to improve camera trap data processing speeds, but these models are not considered accurate enough for fully automated labeling of images.Here, we present a new approach to building and testing a high performance machine learning model for fully automated labeling of camera trap images. As a case-study, the model classifies 26 Central African forest mammal and bird species (or groups). The model was trained on a relatively small dataset (c.300,000 images) but generalizes to fully independent data and outperforms humans in several respects (e.g. detecting ‘invisible’ animals). We show how the model’s precision and accuracy can be evaluated in an ecological modeling context by comparing species richness, activity patterns (n= 4 species tested) and occupancy (n =4 species tested) derived from machine learning labels with the same estimates derived from expert labels.Results show that fully automated labels can be equivalent to expert labels when calculating species richness, activity patterns (n= 4 species tested) and estimating occupancy (n= 3 of 4 species tested) in completely out-of-sample test data (n= 227 camera stations,n= 23868 images). Simple thresholding (discarding uncertain labels) improved the model’s performance when calculating activity patterns and estimating occupancy, but did not improve estimates of species richness.We provide the user-community with a multi-platform, multi-language user interface for running the model offline, and conclude that high performance machine learning models can fully automate labeling of camera trap data.
SpineS: An interactive time-series analysis software for dendritic spines
Authors: Argunşah Ali Özgür , Erdil Ertunç , Ghani Muhammad Usman , Cortés Yazmín Ramiro , Hobbiss Anna Felicity , Karayannis Theofanis , Çetin Müjdat , Israely Inbal , Ünay Devrim 
Published: September 2020

ABSTRACTLive fluorescence imaging has shown the dynamic nature of dendritic spines, with changes in shape occurring both during development and in response to activity. The structure of a dendritic spine positively correlates with its functional efficacy. Learning and memory studies have shown that great deal of the information stored by a neuron is contained in the synapses. High precision tracking of synaptic structures can give hints about the dynamic nature of memory and help us to understand how memories evolve both in biological and artificial neural networks. Experiments that aim to investigate the dynamics behind the structural changes of dendritic spines require the collection and analysis of large time-series datasets. In this paper, we present an open-source software called SpineS for the automatic longitudinal structural analysis of dendritic spines with additional features for manual intervention to ensure optimal analysis. Our extensive experimental analyses on multiple datasets demonstrate that SpineS can achieve a high-level performance on samples collected both by two-photon and confocal imaging systems.
Causality Mapping Using Resting-State fMRI reveals Suppressed Functional Connectivity in Schizophrenia Patients
Authors: Ahmed Fayyaz , Saghir Zunira , Aamir Namra , Abualait Turki , Chaudhary Safee Ullah , Bashir Shahid 
Published: September 2020

ABSTRACTSchizophrenia is a psychotic brain disorder in which patients exhibit aberrant connectivity between different regions of the brain. Neuroimaging is a state-of-the-art technique that is now increasingly been employed in clinical investigation of Schizophrenia. In the present study, we have used resting-state functional magnetic resonance neuroimaging (rsfMRI) to elucidate the cause-and-effect relationships among four regions of the brain including occipital, temporal, and frontal lobes and hippocampus in Schizophrenia. For that, we have employed independent component analysis, a seed-based temporal correlation analysis, and Granger causality analysis for measuring causal relationships amongst four regions of the brain in schizophrenia patients. Eighteen subjects with nine patients and nine controls were evaluated in the study. Our results show that Schizophrenia patients exhibit significantly different activation patterns across the selected regions of the brain in comparison with the control. In addition to that, we also observed an aberrant causal relationship between these four regions of the brain. In particular, the temporal and frontal lobes of patients with schizophrenia had a significantly lowered causal relationship with the other areas of the brain. Taken together, the study elucidates the dysregulated brain activity in Schizophrenia patients, decodes its causal mapping and provides novel insights towards employment in clinical evaluation of Schizophrenia.
Role of Weather Factors in COVID-19 Deaths in Tropical Climate: A Data-Driven Study Focused on Brazil Manuscript
Authors: Moozhipurath Rahul Kalippurayil 
Published: September 2020

AbstractBackgroundBrazil reported 123,780 deaths across 27 administrative regions, making it the second-worst affected country after the US in terms of COVID-19 deaths as of 3 September 2020. Understanding the role of weather factors in COVID-19 in Brazil is helpful in the longterm mitigation strategy of COVID-19 in other tropical countries because Brazil experienced early large-scale outbreak among tropical countries. Recent COVID-19 studies indicate that relevant weather factors such as temperature, humidity, UV Index (UVI), precipitation, ozone, pollution and cloud cover may influence the spread of COVID-19. Yet, the magnitude and direction of those associations remain inconclusive. Furthermore, there is only limited research exploring the impact of these weather factors in a tropical country like Brazil. In this observational study, we outline the roles of 7 relevant weather factors including temperature, humidity, UVI, precipitation, ozone, pollution (visibility) and cloud cover in COVID-19 deaths in Brazil.MethodsWe use a log-linear fixed-effects model to a panel dataset of 27 administrative regions in Brazil across 182 days (n=3882) and analyze the role of relevant weather factors by using daily cumulative COVID-19 deaths in Brazil as the dependent variable. We carry out robustness checks using case-fatality-rate (CFR) as the dependent variable.FindingsWe control for all time-fixed and various time-varying region-specific factors confounding factors. We observe a significant negative association of COVID-19 daily deaths growth rate in Brazil with weather factors – UVI, temperature, ozone and cloud cover. Specifically, a unit increase in UVI, maximum temperature, and ozone independently associate with 6.0 percentage points [p<0.001], 1.8 percentage points [p<0.01] and 0.3 percentage points [p<0. 1] decline in COVID-19 deaths growth rate. Further, a unit percentage increase in cloud cover associates with a decline of 0.148 percentage points [p<0.05] in COVID-19 deaths growth rate. Surprisingly, contrary to other studies, we do not find evidence of any association between COVID-19 daily deaths growth rate and humidity, visibility and precipitation. We find our results to be consistent even when we use the CFR as the dependent variable.InterpretationWe find independent protective roles of UVI, temperature, ozone and cloud cover in mitigating COVID-19 deaths, even in a tropical country like Brazil. We observe these results to be consistent across various model specifications, especially for UVI and cloud cover, even after incorporating additional time-varying weather parameters such as dewpoint, pressure, wind speed and wind gust. These results could guide health-related policy decision making in Brazil as well as similar tropical countries.
Rapid, accurate, nucleobase detection using FnCas9
Authors: Azhar Mohd. , Phutela Rhythm , Kumar Manoj , Ansari Asgar Hussain , Rauthan Riya , Gulati Sneha , Sharma Namrata , Sinha Dipanjali , Sharma Saumya , Singh Sunaina , Acharya Sundaram , Paul Deepanjan , Kathpalia Poorti , Aich Meghali , Sehgal Paras , Ranjan Gyan , Bhoyar Rahul C. ,   Indian CoV2 Genomics & Genetic Epidemiology (IndiCovGEN) Consortium, Singhal Khushboo , Lad Harsha , Patra Pradeep Kumar , Makharia Govind , Chandak Giriraj Ratan , Pesala Bala , Chakraborty Debojyoti , Maiti Souvik 
Published: September 2020

ABSTRACTRapid detection of pathogenic sequences or variants in DNA and RNA through a point-of-care diagnostic approach is valuable for accelerated clinical prognosis as has been witnessed during the recent COVID-19 outbreak. Traditional methods relying on qPCR or sequencing are difficult to implement in settings with limited resources necessitating the development of accurate alternative testing strategies that perform robustly. Here, we present FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that employs a direct Cas9 based enzymatic readout for detecting nucleotide sequences and identifying nucleobase identity without the requirement of trans-cleavage activity of reporter molecules. We demonstrate that FELUDA is 100% accurate in detecting single nucleotide variants (SNVs) including heterozygous carriers of a mutation and present a simple design strategy in the form of a web-tool, JATAYU, for its implementation. FELUDA is semi quantitative, can be adapted to multiple signal detection platforms and can be quickly designed and deployed for versatile applications such as infectious disease outbreaks like COVID-19. Using a lateral flow readout within 1h, FELUDA shows 100% sensitivity and 97% specificity across all range of viral loads in clinical samples. In combination with RT-RPA and a smartphone application True Outcome Predicted via Strip Evaluation (TOPSE), we present a prototype for FELUDA for CoV-2 detection at home.Single sentence summaryA method to identify nucleotide sequence or nucleobase identity using FnCas9 and its implementation in the rapid and accurate diagnosis of SARS-CoV-2
Cross-Population Genetic Variation of Loci Identified by Genome-Wide Association Studies conducted in British participants of European-descent from the UK Biobank
Authors: De Lillo Antonella , D’Antona Salvatore , Fuciarelli Maria , Polimanti Renato 
Published: September 2020

AbstractTo provide novel insight regarding the inter-population diversity of loci associated with complex traits, we integrated genome-wide data from UK Biobank (UKB) and 1,000 Genomes Project (1KG) data representative of the genetic diversity among worldwide populations. We investigated genome-wide data of 4,359 traits from 361,194 UKB participants of European descent. Using 1KG data, we explored the allele frequency differences and linkage disequilibrium (LD) structure of UKB genome-wide significant (GWS) loci across worldwide populations. Functional annotation data were used to identify regulatory elements and evaluate the tagging properties of GWS variants. No significant difference was observed in allele frequency between UKB and 1KG GBR (British in England and Scotland). Considering other population groups, we identified genome-wide significant alleles with frequencies different from what expected by chance: UKB vs. 1KG Europeans without GBR (rs74945666; allele=T [0.908 vs. 0.03], standing height pGWAS=1.48×10-17), UKB vs. 1KG African (rs556562; allele=A [0.942 vs. 0.083], platelet count pGWAS=4.84×10-15), UKB vs. 1KG Admixed Americans (rs1812378; allele=T [0.931 vs. 0.089], standing height pGWAS=4.23×10-12), UKB vs. 1KG East Asian (rs55881864; allele=T [0.911 vs. 0.001], monocyte count pGWAS=7.29×10-13), and UKB vs. South Asian (rs74945666; allele=T [0.908 vs. 0.061], standing height pGWAS=1.48×10-17). LD-structure analysis and computational prediction showed differences in how these alleles tag functional elements across human populations. In conclusion, the human diversity of certain GWS loci appear to be affected by local adaptation while in other cases the associations may be biased by residual population stratification.
Thrombolysis in Acute Pulmonary Embolism: are we over – doing it?
Authors: Showkathali Refai , Yalamanchi Radhapriya , Ramakrishnan Balasubramaniam , Oomman Abraham , Sivaprakash Aruna , Kumar Pramod 
Published: September 2020

ABSTRACTAim and MethodWe aimed to study the clinical data and outcome of patients admitted in our centre with acute pulmonary embolism (PE) over a five year period from May 2013 to April 2018. The main outcome data included were- in-hospital bleeding, in hospital RV function improvement, PAH improvement, duration of hospital stay, 30 and 90 day mortality.ResultsA total of 114 (69 m, 55 f) patients with the mean age of 55+/− 15 yrs were included. Patients who had involvement of central pulmonary trunk- called as “Central PE” group (n = 82) and others as “Peripheral PE” group (n = 32). There were more women in the peripheral PE group (53.1% vs 34.1%, p 0.05), while RBBB (22% vs 3.1%, p 0.02) and RV dysfunction (59.8% vs 25%, p 0.002) were noted more in the central PE group. Systemic thrombolysis was done in 53 patients (49 central, 4 peripheral), of which only 3 had hypotension and 28 patients were in the Intermediate-high risk group. The overall in-hospital, 30 day and 90 day mortality were 3.6, 13.2 and 22.8% respectively. Bleeding was significantly higher in thrombolysed group compared to the non- thrombolysed group (18.9% vs 0, p 0.0003). However, improvement in pulmonary hypertension was noted more in thrombolysis group compared to non-thrombolytic group. (49% vs 21.2%, p 0.01).ConclusionThis retrospective data from a tertiary centre in South India showed that short and mid-term mortality of patients with PE still remains high. The high non-guideline use of thrombolysis has reflected in the increased bleeding noted in our study.
Sleep-related traits and attention-deficit/hyperactivity disorder comorbidity: shared genetic risk factors, molecular mechanisms, and causal effects
Authors: Carpena Marina Xavier , Bonilla Carolina , Matijasevich Alicia , Martins-Silva Thais , Genro Julia P. , Hutz Mara Helena , Rohde Luis Augusto , Tovo-Rodrigues Luciana 
Published: September 2020

AbstractStudy ObjectivesTo evaluate the level of shared genetic components between attention-deficit/hyperactivity disorder (ADHD) and sleep phenotype, common pathways between them and a possible causal relationship between traits.MethodsWe used summary statistics of the largest genome-wide association studies available for ADHD and sleep-related phenotypes including insomnia, napping, daytime dozing, snoring, ease getting up, daytime sleepiness, sleep duration and chronotype. We estimated the genomic correlation between ADHD and sleep-related traits using cross-trait LD-score regression and investigated potential common mechanisms using gene-based cross-trait metanalyses and functional enrichment analyses. The causal effect between the sleep related traits and ADHD was estimated with two sample Mendelian randomization (TSMR), using the Inverse Variance Weighted method as the main estimator.ResultsPositive genomic correlation between insomnia, daytime napping, daytime dozing, snoring, daytime sleepiness, short and long sleep duration, and ADHD were observed. Insomnia, sleep duration, daytime sleepiness, and snoring shared genes with ADHD, which were involved in neurobiological functions and regulatory signaling pathways. The TSMR approach supported a causal effect of insomnia, daytime napping, and short sleep duration on ADHD, and of ADHD on long sleep duration and chronotype.ConclusionOur findings suggest that the comorbidity between sleep phenotypes and ADHD may be mediated by common genetic factors with an important role on neuronal signaling pathways. In addition, it may also exist a causal effect of sleep disturbances and short sleep duration on ADHD, reinforcing the role of these sleep phenotypes as predictors or early markers of ADHD.Statement of SignificanceOur findings suggest that the comorbidity between sleep phenotypes and ADHD may be linked to common genetic factors with an important role on neuronal signaling pathways. They also show that a causal effect of sleep disturbances and short sleep duration on ADHD may exist, reinforcing the role of these sleep phenotypes as ADHD early markers, being able to predict the disorder. This study adds important information about the relationship between sleep, circadian rhythm, and ADHD since it raises new questions about the complexity of the phenomenon involving them and may also provide new treatment insights in this research field.
Subtype Heterogeneity and Epigenetic Convergence in Neuroendocrine Prostate Cancer
Authors: Cejas Paloma , Xie Yingtian , Font-Tello Alba , Lim Klothilda , Syamala Sudeepa , Qiu Xintao , Tewari Alok K. , Shah Neel , Nguyen Holly M , Patel Radhika A. , Brown Lisha , Coleman Ilsa , Hackeng Wenzel M. , Brosens Lodewijk , Dreijerink Koen M.A. , Ellis Leigh , Abou Alaiwi Sarah , Seo Ji-Heui , Pomerantz Mark , Dall’Agnese Alessandra , Crowdis Jett , Van Allen Eliezer M. , Bellmunt Joaquim , Morrisey Colm , Nelson Peter S. , DeCaprio James , Farago Anna , Dyson Nicholas , Drapkin Benjamin , Liu X. Shirley , Freedman Matthew , Haffner Michael C. , Corey Eva , Brown Myles , Long Henry W. 
Published: September 2020

AbstractNeuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyzed cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single cell analysis of human clinical samples exhibit a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy.