bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fully resolved assembly of Cryptosporidium parvum
Authors: Menon Vipin K. , Okhuysen Pablo C. , Chappell Cynthia L. , Mahmoud Medhat , Mahmoud Medhat , Meng Qingchang , Doddapaneni Harsha , Vee Vanesa , Han Yi , Salvi Sejal , Bhamidipati Sravya , Kottapalli Kavya , Weissenberger George , Shen Hua , Ross Matthew C. , Hoffman Kristi L. , Cregeen Sara Javornik , Muzny Donna M. , Metcalf Ginger A. , Gibbs Richard A. , Petrosino Joseph F. , Sedlazeck Fritz J. 
Published: July 2021

AbstractBackgroundCryptosporidium parvum is an apicomplexan parasite commonly found across many host species with a global infection prevalence in human populations of 7.6%. As such, it is important to understand the diversity and genomic makeup of this prevalent parasite to fight established infections and prohibit further transmission. The basis of every genomic study is a high quality reference genome that has continuity and completeness, thus enabling comprehensive comparative studies.FindingsHere, we provide a highly accurate and complete reference genome of Cryptosporidium parvum. The assembly is based on Oxford Nanopore reads and was improved using Illumina reads for error correction. We also outline how to evaluate and choose from different assembly methods based on two main approaches that can be applied to other Cryptosporidium species. The assembly encompasses 8 chromosomes and includes 13 telomeres that were resolved. Overall, the assembly shows a high completion rate with 98.4% single copy BUSCO genes.ConclusionsThis high quality reference genome of a zoonotic IIaA17G2R1 C. parvum subtype isolate provides the basis for subsequent comparative genomic studies across the Cryptosporidium clade. This will enable improved understanding of diversity, functional and association studies.
Age-associated changes to neuronal dynamics involve a disruption of excitatory/inhibitory balance in C. elegans
Authors: Wirak Gregory S , Florman Jeremy , Alkema Mark J , Connor Christopher W , Gabel Christopher V 
Published: July 2021

ABSTRACTIn the aging brain, many of the alterations underlying cognitive and behavioral decline remain opaque. C. elegans offers a powerful model for aging research, with a simple, well-studied nervous system to further our understanding of the cellular modifications and functional alterations accompanying senescence. We perform multi-neuronal functional imaging across the aged C. elegans nervous system, measuring an age-associated breakdown in system-wide functional organization. At single-cell resolution, we detect shifts in activity dynamics toward higher frequencies. In addition, we measure a specific loss of inhibitory signaling that occurs early in the aging process and alters the systems critical excitatory/inhibitory balance. These effects are recapitulated with mutation of the calcium channel subunit UNC-2/CaV2α,. We find that manipulation of inhibitory GABA signaling can partially ameliorate or accelerate the effects of aging. The effects of aging are also partially mitigated by disruption of the insulin signaling pathway, known to increase longevity, or by a reduction of caspase activation. Data from mammals are consistent with our findings, suggesting a conserved shift in the balance of excitatory/inhibitory signaling with age that leads to breakdown in global neuronal dynamics and functional decline.
Decoding Images from Multi-Region, High Resolution, Electrode Recordings In the Mouse Visual System
Authors: Fritz Chris 
Published: July 2021

1AbstractWe hypothesize that deep networks are superior to linear decoders at recovering visual stimuli from neural activity. Using high-resolution, multielectrode Neuropixels recordings, we verify this is the case for a simple feed-forward deep neural network having just 7 layers. These results suggest that these feed-forward neural networks and perhaps more complex deep architectures will give superior performance in a visual brain-machine interface.
Epidemiological inference for emerging viruses using segregating sites
Authors: Park Yeongseon , Martin Michael , Koelle Katia 
Published: July 2021

AbstractEpidemiological models are commonly fit to case data to estimate model parameters and to infer unobserved disease dynamics. Epidemiological models have also been fit to viral sequence data using phylodynamic inference approaches that rely on the reconstruction of viral phylogenies. However, especially early on in an expanding viral population, phylogenetic uncertainty can be substantial and methods that require integration over this uncertainty can be computationally intensive. Moreover, these approaches require estimation of parameters associated with models of sequence evolution in addition to the estimation of epidemiological parameters that are of primary interest. Here, we present an alternative approach to phylodynamic inference that can be used early on during the expansion of a viral lineage that circumvents the need for phylogenetic tree reconstruction. Our “tree-free” approach instead relies on quantifying the number of segregating sites observed in sets of sequences over time and using this trajectory of segregating sites to infer epidemiological parameters within a Sequential Monte Carlo (SMC) framework. Using forward simulations, we first show that epidemiological parameters and processes leave characteristic signatures in segregating site trajectories, demonstrating that these trajectories have the potential to be used for interfacing epidemiological models with sequence data. We then show that our proposed approach accurately recovers key epidemiological quantities such as the basic reproduction number and the timing of the index case from mock data simulated under a single-introduction scenario. Finally, we apply our approach to SARS-CoV-2 sequence data from France, estimating a reproductive number of approximately 2.5 to 2.7 under an epidemiological model structure that allows for multiple introductions, consistent with estimates from epidemiological surveillance data. Our findings indicate that “tree-free” statistical inference approaches that rely on simple population genetic summary statistics can be informative of epidemiological parameters and can be used for reconstructing infectious disease dynamics early on in an epidemic or during the expansion of a viral lineage.
MuscleNET: mapping electromyography to kinematic and dynamic biomechanical variables by machine learning
Authors: Nasr Ali , Bell Sydney , He Jiayuan , Whittaker Rachel L. , Jiang Ning , Dickerson Clark R. , McPhee John 
Published: July 2021

AbstractObjectiveThis paper proposes machine learning models for mapping surface electromyography (sEMG) signals to regression of joint angle, joint velocity, joint acceleration, joint torque, and activation torque.ApproachThe regression models, collectively known as MuscleNET, take one of four forms: ANN (Forward Artificial Neural Network), RNN (Recurrent Neural Network), CNN (Convolutional Neural Network), and RCNN (Recurrent Convolutional Neural Network). Inspired by conventional biomechanical muscle models, delayed kinematic signals were used along with sEMG signals as the machine learning model’s input; specifically, the CNN and RCNN were modeled with novel configurations for these input conditions. The models’ inputs contain either raw or filtered sEMG signals, which allowed evaluation of the filtering capabilities of the models. The models were trained using human experimental data and evaluated with different individual data.Main resultsResults were compared in terms of regression error (using the root-mean-square) and model computation delay. The results indicate that the RNN (with filtered sEMG signals) and RCNN (with raw sEMG signals) models, both with delayed kinematic data, can extract underlying motor control information (such as joint activation torque or joint angle) from sEMG signals in pick-and-place tasks. The CNNs and RCNNs were able to filter raw sEMG signals.SignificanceAll forms of MuscleNET were found to map sEMG signals within 2 ms, fast enough for real-time applications such as the control of exoskeletons or active prostheses. The RNN model with filtered sEMG and delayed kinematic signals is particularly appropriate for applications in musculoskeletal simulation and biomechatronic device control.
The characteristics of the HIV-1 Env glycoprotein contribute to viral pathogenesis
Authors: Pérez-Yanes Silvia , Pernas Maria , Marfil Silvia , Cabrera-Rodríguez Romina , Ortiz Raquel , Rovirosa Carla , Estévez-Herrera Judith , Olivares Isabel , Casado Concepción , Lopez-Galindez Cecilio , Blanco Julià , Valenzuela-Fernández Agustin 
Published: July 2021

AbstractThe understanding of HIV-1 pathogenesis and clinical progression is incomplete because of the variable contribution of host, immune and viral factors. The involvement of viral factors has been investigated in extreme clinical phenotypes from rapid progressors to long-term non-progressors (LTNPs). Among HIV-1 proteins, the envelope glycoprotein complex (Env) has concentrated many studies for its important role in the immune response and in the first steps of viral replication. In this study, we analyzed the contribution of 41 Envs from 24 patients with different clinical progression rates and viral loads (VLs), LTNP-Elite Controllers (LTNP-ECs); Viremic LTNPs (vLTNPs), and non-controller’s individuals contemporary to LTNPs or recent, named Old and Modern progressors. We analyzed the Env expression, the fusion and cell-to-cell transfer capacities as well as viral infectivity. The sequence and phylogenetic analysis of Envs were also performed. In every functional characteristic, the Envs from subjects with viral control (LTNP-ECs and vLTNPs) showed significant lower performance compared to those from the progressor individuals (Old and Modern). Regarding sequence analysis, the variable loops of the gp120 subunit of the Env (i.e., V2, V4 and mainly V5) of the progressor individuals showed longer and more glycosylated sequences than controller subjects. Therefore, HIV-1 Envs presenting poor viral functions and shorter sequences were associated with viremic control and the non-progressor clinical phenotype, whereas functional Envs were associated with the lack of virological control and progressor clinical phenotypes. These correlations support the central role of Env genotypic and phenotypic characteristics in the in vivo HIV-1 infection and pathogenesis.IMPORTANCEThe role of the virus in the pathogenesis of HIV-1 infection has not been investigated in isolates from individuals with different progression rates. In this work, we studied the properties of the envelope glycoprotein complex (Env) in individuals with different progression rates to elucidate its role in pathogenesis. We estimated the Env expression, the CD4 binding, the fusion and cell-to-cell viral transfer capacities that affect the infectivity of the viral Envs in recombinant viruses. The Envs from individuals which control viral replication and lack clinical progression (LTNP-ECs and vLTNPs) showed lower functional capacities than from subjects with clinical progression (Old and Modern). The functional increase of the Envs characteristics was associated with an increase in viral infectivity and in increased length of variable loops and the number of glycosylation sites of the Env (gp120/SU). These results support the concept that viral characteristics contribute to viral infection and pathogenesis.
Genome-Wide Association Meta-Analysis Using a Recessive Model Illuminates Genetic Architecture of Type 2 Diabetes
Authors: O’Connor Mark J. , Huerta-Chagoya Alicia , Cortés-Sánchez Paula , Bonàs-Guarch Silvía , Guindo-Martínez Marta , Cole Joanne B. , Torrents David , Veerapen Kumar , Grarup Niels , Kurki Mitja , Rundsten Carsten F. , Pedersen Oluf , Brandslund Ivan , Linneberg Allan , Hansen Torben , Leong Aaron , Florez Jose C. , Mercader Josep M. 
Published: July 2021

ABSTRACTObjectiveMost genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered.Research Design and MethodsWe conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 cases and 279,507 controls from seven European-ancestry cohorts including the UK Biobank. We then used two additional cohorts, FinnGen and a Danish cohort, for replication. For the most significant recessive signal, we conducted a phenome-wide association study across hundreds of traits to make inferences about the pathophysiology underlying the increased risk seen in homozygous carriers.ResultsWe identified 51 loci associated with type 2 diabetes, including five variants with recessive effects undetected by prior additive analyses. Two of the five had minor allele frequency less than 5% and were each associated with more than doubled risk. We replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19, P=1×10−16) and a stronger effect in men than in women (interaction P=7×10−7). Colocalization analysis linked this signal to reduced expression of the nearby PELO gene, and the signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL and a 20% increase in triglycerides.ConclusionsOur results demonstrate that recessive models, when compared to GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes.
Heparin for Moderately Ill Patients with Covid-19
Authors: Sholzberg Michelle , Tang Grace H. , Rahhal Hassan , AlHamzah Musaad , Kreuziger Lisa Baumann , Ní Áinle Fionnuala , Alomran Faris , Alayed Khalid , Alsheef Mohammed , AlSumait Fahad , Pompilio Carlos Eduardo , Sperlich Catherine , Tangri Sabrena , Tang Terence , Jaksa Peter , Suryanarayan Deepa , Almarshoodi Mozah , Castellucci Lana , James Paula D. , Lillicrap David , Carrier Marc , Beckett Andrew , Colovos Christos , Jayakar Jai , Arsenault Marie-Pier , Wu Cynthia , Doyon Karine , Andreou E. Roseann , Dounaevskaia Vera , Tseng Eric K. , Lim Gloria , Fralick Michael , Middeldorp Saskia , Lee Agnes Y.Y. , Zuo Fei , da Costa Bruno R. , Thorpe Kevin E. , Negri Elnara Márcia , Cushman Mary , Jüni Peter ,   the RAPID Trial investigators
Published: July 2021

AbstractBackgroundHeparin, in addition to its anticoagulant properties, has anti-inflammatory and potential anti-viral effects, and may improve endothelial function in patients with Covid-19. Early initiation of therapeutic heparin could decrease the thrombo-inflammatory process, and reduce the risk of critical illness or death.MethodsWe randomly assigned moderately ill hospitalized ward patients admitted for Covid-19 with elevated D-dimer level to therapeutic or prophylactic heparin. The primary outcome was a composite of death, invasive mechanical ventilation, non-invasive mechanical ventilation or ICU admission. Safety outcomes included major bleeding. Analysis was by intention-to-treat.ResultsAt 28 days, the primary composite outcome occurred in 37 of 228 patients (16.2%) assigned to therapeutic heparin, and 52 of 237 patients (21.9%) assigned to prophylactic heparin (odds ratio, 0.69; 95% confidence interval [CI], 0.43 to 1.10; p=0.12). Four patients (1.8%) assigned to therapeutic heparin died compared with 18 patients (7.6%) assigned to prophylactic heparin (odds ratio, 0.22; 95%-CI, 0.07 to 0.65). The composite of all-cause mortality or any mechanical ventilation occurred in 23 (10.1%) in the therapeutic heparin group and 38 (16.0%) in the prophylactic heparin group (odds ratio, 0.59; 95%-CI, 0.34 to 1.02). Major bleeding occurred in 2 patients (0.9%) with therapeutic heparin and 4 patients (1.7%) with prophylactic heparin (odds ratio, 0.52; 95%-CI, 0.09 to 2.85).ConclusionsIn moderately ill ward patients with Covid-19 and elevated D-dimer level, therapeutic heparin did not significantly reduce the primary outcome but decreased the odds of death at 28 days.Trial registration numbers: NCT04362085; NCT04444700
Automated lung sound analysis using the LungPass platform: A sensitive and specific tool for identifying lower respiratory tract involvement in COVID-19
Authors: Lapteva Elena A. , Kharevich Olga N. , Khatsko Victoria V. , Voronova Natalia A. , Chamko Maksim V. , Bezruchko Irina V. , Katibnikova Elena I. , Loban Elena I. , Mouawie Mostafa M. , Binetskaya Helena , Aleshkevich Sergey , Karankevich Aleksey , Dubinetski Vitaly , Vestbo Jørgen , Mathioudakis Alexander G. 
Published: July 2021

AbstractBackgroundLower respiratory tract (LRT) involvement, observed in about 20% of patients suffering from coronavirus disease 2019 (COVID-19) is associated with a more severe clinical course, adverse outcomes and long-term sequelae. Early identification of LRT involvement could facilitated targeted and timely interventions that could alter the short- and long-term disease outcomes. The LungPass is an automated lung sound analysis platform developed using neural network technology and previously trained. We hypothesised that the LungPass could be used as a screening tool for LRT involvement in patients with COVID-19.MethodsIn a prospective observational study involving 282 individuals with presenting in the emergency department with a strong clinical suspicion of COVID-19 and imaging findings consistent with COVID-19 LRT involvement (25.5% had concomitant hypoxia), and 32 healthy controls, we assessed the sensitivity and specificity of the LungPass in identifying LRT involvement in COVID-19. We also compared the auscultatory findings of the LungPass compared to a chest physician using a traditional, high-quality stethoscope.ResultsAmong individuals with COVID-19 LRT involvement, the LungPass identified crackles in at least one auscultation site in 93.6% and in two or more points in 84%. Moreover, the LungPass identified any abnormal lung sound (crackles or wheeze) in at least one auscultation site in 98.6% and in at least two points in 94% of the participants. The respective percentages for the respiratory physicians were lower.Considering the presence of any added abnormal sound (crackles or wheeze) in at least two auscultation points as evidence of LRT involvement, LungPass demonstrated a sensitivity of 98.6% (95% confidence intervals [CI]: 96.4%-99.6%) and a specificity of 96.9% (95% CI: 83.8%-99.9%) in identifying COVID-19 LRT involvement.ConclusionThis exploratory study suggests the LungPass is a sensitive and specific platform for identifying LRT involvement due to COVID-19, even before the development of hypoxia.
REACT-1 round 13 interim report: acceleration of SARS-CoV-2 Delta epidemic in the community in England during late June and early July 2021
Authors: Riley Steven , Eales Oliver , Haw David , Wang Haowei , Walters Caroline E. , Ainslie Kylie E. C. , Atchison Christina , Fronterre Claudio , Diggle Peter J. , Ashby Deborah , Donnelly Christl A. , Barclay Wendy , Cooke Graham , Ward Helen , Darzi Ara , Elliott Paul 
Published: July 2021

AbstractBackgroundDespite high levels of vaccination in the adult population, cases of COVID-19 have risen exponentially in England since the start of May 2021 driven by the Delta variant. However, with far fewer hospitalisations and deaths per case during the recent growth in cases compared with 2020, it is intended that all remaining social distancing legislation in England will be removed from 19 July 2021.MethodsWe report interim results from round 13 of the REal-time Assessment of Community Transmission-1 (REACT-1) study in which a cross-sectional sample of the population of England was asked to provide a throat and nose swab for RT-PCR and to answer a questionnaire. Data collection for this report (round 13 interim) was from 24 June to 5 July 2021.ResultsIn round 13 interim, we found 237 positives from 47,729 swabs giving a weighted prevalence of 0.59% (0.51%, 0.68%) which was approximately four-fold higher compared with round 12 at 0.15% (0.12%, 0.18%). This resulted from continued exponential growth in prevalence with an average doubling time of 15 (13, 17) days between round 12 and round 13. However, during the recent period of round 13 interim only, we observed a shorter doubling time of 6.1 (4.0, 12) days with a corresponding R number of 1.87 (1.40, 2.45). There were substantial increases in all age groups under the age of 75 years, and especially at younger ages, with the highest prevalence in 13 to 17 year olds at 1.33% (0.97%, 1.82%) and in 18 to 24 years olds at 1.40% (0.89%, 2.18%). Infections have increased in all regions with the largest increase in London where prevalence increased more than eight-fold from 0.13% (0.08%, 0.20%) in round 12 to 1.08% (0.79%, 1.47%) in round 13 interim. Overall, prevalence was over 3 times higher in the unvaccinated compared with those reporting two doses of vaccine in both round 12 and round 13 interim, although there was a similar proportional increase in prevalence in vaccinated and unvaccinated individuals between the two rounds.DiscussionWe are entering a critical period with a number of important competing processes: continued vaccination rollout to the whole adult population in England, increased natural immunity through infection, reduced social mixing of children during school holidays, increased proportion of mixing occurring outdoors during summer, the intended full opening of hospitality and entertainment and cessation of mandated social distancing and mask wearing. Surveillance programmes are essential during this next phase of the epidemic to provide clear evidence to the government and the public on the levels and trends in prevalence of infections and their relationship to vaccine coverage, hospitalisations, deaths and Long COVID.
Intracellular phase separation of globular proteins facilitated by short cationic peptides
Authors: Yeong Vivian , Wang Jou-wen , Horn Justin M. , Obermeyer Allie C. 
Published: July 2021

ABSTRACTPhase separation provides intracellular organization and underlies a variety of cellular processes. These biomolecular condensates exhibit distinct physical and material properties. Current strategies for engineering condensate formation include using intrinsically disordered domains and altering protein surface charge by chemical supercharging or site-specific mutagenesis. We add to this toolbox by designing short, highly charged peptide tags that provide several key advantages for engineering protein phase separation. Herein, we report the use of short cationic peptide tags for sequestration of proteins of interest into bacterial condensates. Using a panel of GFP variants, we demonstrate how cationic tag and globular domain charge contribute to intracellular phase separation in E. coli and observe that the tag can affect condensate disassembly at a given net charge near the phase separation boundary. We showcase the broad applicability of these tags by appending them onto enzymes and demonstrating that the sequestered enzymes remain catalytically active.Abstract Figure