bluuebunny/crossref_metadata_2025_split huggingface dataset:
TAXON INCOMPLETENESS AND DISCRETE TIME BINS AFFECT CHARACTER CHANGE RATES IN SIMULATED DATA
Authors: Flores Jorge R. 
Published: July 2020

AbstractEstimating how fast or slow morphology evolves through time (phenotypic change rate; PR) has become common in macroevolutionary studies, and has been important for clarifying key evolutionary events. However, the inclusion of incompletely scored taxa (e.g., fossils) could affect PR estimates and potentially mask real PR patterns. This effect being also affected by the usage of arbitrary discrete time bins. Here, the impact of taxon incompleteness (unscored data) on PR estimates is assessed in simulated data. Three different time bin series were likewise evaluated: bins evenly spanning the tree length (i), a shorter middle bin (ii), and a longer middle bin (iii). The results indicate that PR values decrease as taxon incompleteness increases. Statistical significant PR values, and the dispersion among PR values, depended on the time bins. These outcomes imply that taxon incompleteness can undermine our capacity to infer morphology evolutionary dynamics and that these estimates are also influenced by our choice of discrete time bins. More importantly, the present results stress the need for a better approach to deal with taxon incompleteness and arbitrary discrete time bins.
A self-aligning end-effector robot for individual joint training of the human arm
Authors: Balasubramanian Sivakumar , Guguloth Sandeep , Mohammed Javeed Shaikh , Sujatha S. 
Published: July 2020

AbstractCurrent evidence indicates that individual joint training with robotic devices can be as effective as multi-joint training for the arm. This makes a case for developing simpler and more compact robots for training individual joints of the arm. Such robots have the highest potential for clinical translation. To this end, the current work presents the kinematic design and optimization of a six degrees-of-freedom (dof) end-effector robot with three actuateddofand three non-actuated self-aligningdoffor safe assisted training of the individual joints (shoulder or elbow) of the human arm, with relaxed constraints of the relative positioning of the human limb with respect to the robot. Further, we present a simple estimation procedure to automatically identify the kinematic parameters of the human limb essential for control of the human-robot closed kinematic chain.
Multiple parietal pathways are associated with rTMS-induced hippocampal network enhancement and episodic memory changes
Authors: Freedberg Michael , Cunningham Catherine A. , Fioriti Cynthia M. , Murillo Jorge Dorado , Reeves Jack A. , Taylor Paul A. , Sarlls Joelle E. , Wassermann Eric M. 
Published: July 2020

AbstractRepetitive transcranial magnetic stimulation (rTMS) of the inferior parietal cortex (IPC) increases resting-state functional connectivity (rsFC) of the hippocampus with the precuneus and other posterior cortical areas and causes proportional improvement of episodic memory. The anatomical pathway responsible for the propagation of these effects from the IPC is unknown and may not be direct. Using diffusion tensor imaging, we examined whether individual differences in fractional anisotropy (FA), a tensor-derived quantity related to white matter properties, in pathways between the IPC and medial temporal lobe (MTL), via the parahippocampal cortex and the precuneus, accounted for individual differences in hippocampal rsFC and memory change after rTMS. FA in the IPC-parahippocampal pathway was associated with rsFC change in a few small cortical clusters, while FA in the IPC-precuneus pathway was strongly linked to widespread changes in rsFC. FA in both pathways was related to episodic memory, but not to procedural memory. These results implicate pathways to the MTL and to the precuneus in the enhancing effect of parietal rTMS on hippocampal rsFC and memory.
Replication-competent vesicular stomatitis virus vaccine vector protects against SARS-CoV-2-mediated pathogenesis
Authors: Case James Brett , Rothlauf Paul W. , Chen Rita E. , Kafai Natasha M. , Fox Julie M. , Shrihari Swathi , McCune Broc T. , Harvey Ian B. , Smith Brittany , Keeler Shamus P. , Bloyet Louis-Marie , Winkler Emma S. , Holtzman Michael J. , Fremont Daved H. , Whelan Sean P.J. , Diamond Michael S. 
Published: July 2020

SUMMARYSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of human infections and hundreds of thousands of deaths. Accordingly, an effective vaccine is of critical importance in mitigating coronavirus induced disease 2019 (COVID-19) and curtailing the pandemic. We developed a replication-competent vesicular stomatitis virus (VSV)-based vaccine by introducing a modified form of the SARS-CoV-2 spike gene in place of the native glycoprotein gene (VSV-eGFP-SARS-CoV-2). Immunization of mice with VSV-eGFP-SARS-CoV-2 elicits high titers of antibodies that neutralize SARS-CoV-2 infection and target the receptor binding domain that engages human angiotensin converting enzyme-2 (ACE2). Upon challenge with a human isolate of SARS-CoV-2, mice expressing human ACE2 and immunized with VSV-eGFP-SARS-CoV-2 show profoundly reduced viral infection and inflammation in the lung indicating protection against pneumonia. Finally, passive transfer of sera from VSV-eGFP-SARS-CoV-2-immunized animals protects naïve mice from SARS-CoV-2 challenge. These data support development of VSV-eGFP-SARS-CoV-2 as an attenuated, replication-competent vaccine against SARS-CoV-2.
Discriminating Mild from Critical COVID-19 by Innate and Adaptive Immune Single-cell Profiling of Bronchoalveolar Lavages
Authors: Wauters Els , Van Mol Pierre , Garg Abhishek D. , Jansen Sander , Van Herck Yannick , Vanderbeke Lore , Bassez Ayse , Boeckx Bram , Malengier-Devlies Bert , Timmerman Anna , Van Brussel Thomas , Van Buyten Tina , Schepers Rogier , Heylen Elisabeth , Dauwe Dieter , Dooms Christophe , Gunst Jan , Hermans Greet , Meersseman Philippe , Testelmans Dries , Yserbyt Jonas , Matthys Patrick , Tejpar Sabine ,   CONTAGIOUS collaborators, Neyts Johan , Wauters Joost , Qian Junbin , Lambrechts Diether 
Published: July 2020

ABSTRACTHow innate and adaptive lung immune responses to SARS-CoV-2 synchronize during COVID-19 pneumonitis and regulate disease severity is poorly established. To address this, we applied single-cell profiling to bronchoalveolar lavages from 44 patients with mild or critical COVID-19versusnon-COVID-19 pneumonia as control. Viral RNA-tracking delineated the infection phenotype to epithelial cells, but positioned mainly neutrophils at the forefront of viral clearance activity during COVID-19. In mild disease, neutrophils could execute their antiviral function in an immunologically ‘controlled’ fashion, regulated by fully-differentiated T-helper-17 (TH17)-cells, as well as T-helper-1 (TH1)-cells, CD8+resident-memory (TRM) and partially-exhausted (TEX) T-cells with good effector functions. This was paralleled by ‘orderly’ phagocytic disposal of dead/stressed cells by fully-differentiated macrophages, otherwise characterized by anti-inflammatory and antigen-presenting characteristics, hence facilitating lung tissue repair. In critical disease, CD4+TH1- and CD8+TEX-cells were characterized by inflammation-associated stress and metabolic exhaustion, while CD4+TH17- and CD8+TRM-cells failed to differentiate. Consequently, T-cell effector function was largely impaired thereby possibly facilitating excessive neutrophil-based inflammation. This was accompanied by impaired monocyte-to-macrophage differentiation, with monocytes exhibiting an ATP-purinergic signalling-inflammasome footprint, thereby enabling COVID-19 associated fibrosis and worsening disease severity. Our work represents a major resource for understanding the lung-localised immunity and inflammation landscape during COVID-19.
GRIDSS2: comprehensive characterisation of somatic structural variation using single breakend variants and structural variant phasing
Authors: Cameron Daniel L. , Baber Jonathan , Shale Charles , Valle-Inclan Jose Espejo , Besselink Nicolle , Hoeck Arne van , Janssen Roel , Cuppen Edwin , Priestley Peter , Papenfuss Anthony T. 
Published: July 2020

AbstractGRIDSS2 is the first structural variant caller to explicitly report single breakends - breakpoints in which only one side can be unambiguously determined. By treating single breakends as a fundamental genomic rearrangement signal on par with breakpoints, GRIDSS2 can explain 47% of somatic centromeric copy number changes using single breakends to non-centromeric sequence, with chromosome 1 exhibiting a unique centromeric rearrangement signature. On a cohort of 3,782 deeply sequenced metastatic cancers, GRIDSS2 achieved an unprecedented 3.1% false negative rate and identified a novel 32-100bp duplication signature. Somatic structural variants are highly clustered with GRIDSS2 phasing 16% using just paired-end sequencing.
Bioinformatic and Reactivity-Based Discovery of Linaridins
Authors: Georgiou Matthew A. , Dommaraju Shravan R. , Guo Xiaorui , Mitchell Douglas A. 
Published: July 2020

AbstractLinaridins are members of the ribosomally synthesized and post-translationally modified peptide (RiPP) family of natural products. Five linaridins have been reported, which are defined by the presence of dehydrobutyrine, a dehydrated threonine residue. This work describes the development of a linaridin specific scoring module for Rapid ORF Description and Evaluation Online (RODEO), a genome-mining tool tailored towards RiPP discovery. Upon mining publicly accessible genomes available in the NCBI database, RODEO identified 561 (382 non-redundant) linaridin biosynthetic gene clusters (BGCs). Linaridin BGCs with unique gene architectures and precursor sequences markedly different from previous predictions were uncovered during these efforts. To aid in dataset validation, two new linaridins, pegvadin A and B, were detected through reactivity-based screening (RBS) and isolated from Streptomyces noursei and Streptomyces auratus, respectively. RBS involves the use of a reactive chemical probe that chemoselectively modifies a functional group present in the natural product. The dehydrated amino acids present in linaridins as α/β-unsaturated carbonyls were appropriate electrophiles for nucleophilic 1,4 addition using a thiol-functionalized probe. The data presented within significantly expands the number of predicted linaridin BGCs and serves as a road map for future work in the area. The combination of bioinformatics and RBS is a powerful approach to accelerate natural product discovery.
Psychological state and family functioning of University of Ibadan students during the COVID-19 lockdown
Authors: Ojewale Lucia Yetunde 
Published: July 2020

AbstractBackgroundThe curtailment of social gatherings as well as lack of online academic engagement, due to the COVID-19 lockdown, could have potentially damaging effects on the psychological state of university students in Nigeria. This study examined the prevalence of anxiety and depression, including associated factors and coping methods among undergraduate students in a Nigerian university. It also examined the association between psychological state and family functioning.MethodsThe study design was cross sectional and involved 386 undergraduate students across the main faculties. The university’s ethical review board approved the study with approval number UI/EC/20/0242. An online questionnaire, using Google form, was circulated among the students through their faculty representatives. The Hospital Anxiety and Depression scale (HADs) was used in assessing anxiety and depression, while family functioning was assessed using the McMaster Family Assessment Device, (FAD). Data was entered into Statistical Package for Social Sciences (SPSS), and analysis carried out using descriptive statistics, chi-square, independent t-test, Analysis of Variance (ANOVA), Post-Hoc analysis and linear logistics regression, at α 0.05.ResultsThe mean age was 21±2.9 years, with a female population of 60.1%. Prevalence of anxiety and depression were 41.5% and 31.9% respectively. Students in health-related faculties were significantly less anxious than those in other faculties. Inability to afford three square meals, negative family functioning, having a chronic illness and living in a State/Region with a high incidence of COVID-19, was significantly associated with depression. These factors jointly accounted for 14% of depression seen in undergraduate students. Most of the students coped by engaging themselves in social media, watching television/movies and participating in other online skill development programmes.ConclusionThere was a high prevalence of anxiety and depression among university students with poor family functioning, inability to afford three meals/day, living in a state with a high incidence of COVID-19 and having a chronic illness, contributing to depression. Measures need to be taken to support undergraduate students and their families to prevent negative consequences of poor mental health.
A flexible COVID-19 model to assess mitigation, “reopening”, virus mutation and other changes
Authors: Bienstock Sergio 
Published: July 2020

AbstractThe COVID-19 epidemic which began in China last year has expanded worldwide. A flexible SEIRD epidemiological model with time-dependent parameters is applied to modeling the pandemic. The value of the effective reproduction ratio is varied to quantify the impact of quarantines and social distancing on the number of infections and deaths, on their daily changes. and on the maxima in these daily rates expected during the epidemic. The effect of changing Reff is substantial. It ought to inform policy decisions around resource allocation, mitigation strategies and their duration, and economic tradeoffs. The model can also calculate the impact of changes in infectiousness or morbidity as the virus mutates, or the expected effects of a new therapy or vaccine assumed to arrive at a future date. The paper concludes with a discussion of a potential endemic end of COVID-19, which might involve times of about 100 years.
Modeling and Preparedness: The Transmission Dynamics of COVID-19 Outbreak in Provinces of Ecuador
Authors: Bustamante-Orellana Carlos , Cevallos-Chavez Jordy , Montalvo-Clavijo Cesar , Sullivan Jeff , Michael Edwin , Mubayi Anuj 
Published: July 2020

AbstractCoronavirus disease 2019 (COVID-19), a novel infectious disease first identified in December 2019 in the city of Wuhan of China’s Hubei province, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease has become a pandemic in just a few months and spread globally with more than 2.89 million cases and 203,000 deaths across 185 countries, as of April 26th, 2020. Ecuador has reported one of the highest rates of COVID-19 in Latin America, with more than 10K cases and 500 deaths in a country of approximately 17 million people. The dynamics of the outbreak is being observed quite different in different provinces of Ecuador with high reported prevalence in some low population density provinces. In this study, we aim to understand variations in outbreaks between provinces and provide assistance in essential preparedness planning in order to respond effectively to ongoing COVID-19 outbreak. The study estimated the critical level of quarantine rate along with corresponding leakage in order to avoid overwhelming the local health care system. The results suggest that provinces with high population density can avoid a large disease burden provided they initiate early and stricter quarantine measures even under low isolation rate. To best of our knowledge, this study is first from the region to determine which provinces will need much preparation for current outbreak in fall and which might need more help.
The diagnostic accuracy of nucleic acid point-of-care test for human coronavirus: A systematic review and meta-analysis
Authors: Subsoontorn Pakpoom , Lohitnavy Manupat , Kongkaew Chuenjid 
Published: July 2020

AbstractMany recent studies reported coronavirus point of care tests (POCTs) based on isothermal amplification. However, the performances of these tests have not been systematically evaluated. We searched databases for studies that provide data to calculate sensitivity, specificity and diagnostic odds ratio (DOR). We included 43 studies on 5204 specimens. Most studies had high risk of patient selection and index test bias but low risk in other domains. Most studies (n = 21) used reverse transcribed loop mediated isothermal amplification (RT-LAMP) to diagnose Coronavirus disease 2019 (COVID-19). Summary estimated ln(DOR) for RT-LAMP of RNA purified COVID-19 samples is 6.50 (95%CI 5.25-7.76), similar to previously reported value for RT-LAMP of other RNA virus. RT-LAMP from crude samples has significantly lower ln(DOR) at 4.46 (95%CI 3.53-5.38). SAMBA-II has the highest ln(DOR) at 8.00 (95%CI 6.14-9.87). Abbott ID Now performance is similar to RT-LAMP of crude sample. The performances of CRISPR diagnosis and RT-LAMP are not significantly different. Types of coronaviruses and publication status have no significant effect on diagnosis performance. Existing nucleic acid POCTs, particularly RT-LAMP, CRISPR diagnosis and SAMBA-II, have good diagnostic performance. Future work should focus on improving a study design to minimize the risk of biases.
A Bayesian Model for Prediction of Rheumatoid Arthritis from Risk Factors
Authors: Lufkin Leon , Budišić Marko , Mondal Sumona , Sur Shantanu 
Published: July 2020

ABSTRACTRheumatoid arthritis (RA) is a chronic autoimmune disorder that typically manifests as destructive joint inflammation but also affects multiple other organ systems. The pathogenesis of RA is complex where a variety of factors including comorbidities, demographic, and socioeconomic variables are known to influence the incidence and progress of the disease. In this work, we aimed to predict RA from a set of 11 well-known risk factors and their interactions using Bayesian logistic regression. We considered up to third-order interactions between the risk factors and implemented factor analysis of mixed data (FAMD) to account for both the continuous and categorical natures of these variables. The predictive model was further optimized over the area under the receiver operating characteristic curve (AUC) using a genetic algorithm (GA). We use data from the National Health and Nutrition Examination Survey (NHANES). Our optimal predictive model has a smoothed AUC of 0.826 (95% CI: 0.801–0.850) on a validation dataset and 0.805 (95% CI: 0.781–0.829) on a holdout test dataset. Our model identified multiple second- and third-order interactions that demonstrate a strong association with RA, implying the potential role of risk factor interactions in the disease mechanism. Interestingly, we find that the inclusion of higher-order interactions in the model only marginally improves overall predictive ability. Our findings on the contribution of RA risk factors and their interaction on disease prediction could be useful in developing strategies for early diagnosis of RA, thus opening potential avenues for improved patient outcomes and reduced healthcare burden to society.
Genomic Mutations and Changes in Protein Secondary Structure and Solvent Accessibility of SARS-CoV-2 (COVID-19 Virus)
Authors: Nguyen Thanh Thi , Pathirana Pubudu N. , Nguyen Thin , Hung Nguyen Quoc Viet , Bhatti Asim , Nguyen Dinh C. , Nguyen Dung Tien , Nguyen Ngoc Duy , Creighton Douglas , Abdelrazek Mohamed 
Published: July 2020

ABSTRACTSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly pathogenic virus that has caused the global COVID-19 pandemic. Tracing the evolution and transmission of the virus is crucial to respond to and control the pandemic through appropriate intervention strategies. This paper reports and analyses genomic mutations in the coding regions of SARS-CoV-2 and their probable protein secondary structure and solvent accessibility changes, which are predicted using deep learning models. Prediction results suggest that mutation D614G in the virus spike protein, which has attracted much attention from researchers, is unlikely to make changes in protein secondary structure and relative solvent accessibility. Based on 6,324 viral genome sequences, we create a spreadsheet dataset of point mutations that can facilitate the investigation of SARS-CoV-2 in many perspectives, especially in tracing the evolution and worldwide spread of the virus. Our analysis results also show that coding genes E, M, ORF6, ORF7a, ORF7b and ORF10 are most stable, potentially suitable to be targeted for vaccine and drug development.
Influence of plant host and organ, management strategy, and spore traits on microbiome composition
Authors: Gdanetz Kristi , Noel Zachary , Trail Frances 
Published: July 2020

ABSTRACTMicrobiomes from maize and soybean were characterized in a long-term three-crop rotation research site, under four different land management strategies, to begin unraveling the effects of common farming practices on microbial communities. The fungal and bacterial communities of leaves, stems, and roots in host species were characterized across the growing season using amplicon sequencing and compared with the results of a similar study on wheat. Communities differed across hosts, and among plant growth stages and organs, and these effects were most pronounced in the bacterial communities of the wheat and maize phyllosphere. Roots consistently showed the highest number of bacterial OTUs compared to above-ground organs, whereas the alpha diversity of fungi was similar between above- and below-ground organs. Network analyses identified putatively influential members of the microbial communities of the three host plant species. The fungal taxa specific to roots, stems, or leaves were examined to determine if the specificity reflected their life histories based on previous studies. The analysis suggests that fungal spore traits are drivers of organ specificity in the fungal community. Identification of influential taxa in the microbial community and understanding how community structure of specific crop organs is formed, will provide a critical resource for manipulations of microbial communities. The ability to predict how organ specific communities are influenced by spore traits will enhance our ability to introduce them sustainably.
dMSCC: A microfluidic platform for microbial single-cell cultivation under dynamic environmental medium conditions
Authors: Täuber Sarah , Golze Corinna , Ho Phuong , von Lieres Eric , Grünberger Alexander 
Published: July 2020

AbstractIn nature and in technical systems, microbial cells are often exposed to rapidly fluctuating environmental conditions. These conditions can vary in quality, e.g., existence of a starvation zone, and quantity, e.g., average residence time in this zone. For strain development and process design, cellular response to such fluctuations needs to be systematically analysed. However, the existing methods for physically emulating rapidly changing environmental conditions are limited in spatio-temporal resolution. Hence, we present a novel microfluidic system for cultivation of single cells and small cell clusters under dynamic environmental conditions (dynamic microfluidic single-cell cultivation (dMSCC)). This system enables to control nutrient availability and composition between two media with second to minute resolution. We validate our technology using the industrially relevant model organismCorynebacterium glutamicum. The organism was exposed to different oscillation frequencies between nutrient excess (feasts) and scarcity (famine). Resulting changes in cellular physiology, such as the colony growth rate and cell morphology were analysed and revealed significant differences with growth rate and cell length between the different conditions. dMSCC also allows to apply defined but randomly changing nutrient conditions, which is important for reproducing more complex conditions from natural habitats and large-scale bioreactors. The presented system lays the foundation for the cultivation of cells under complex changing environmental conditions.