bluuebunny/crossref_metadata_2025_split huggingface dataset:
Empirical field mapping for gradient nonlinearity correction of multi-site diffusion weighted MRI
Authors: Hansen Colin B. , Rogers Baxter P. , Schilling Kurt G. , Nath Vishwesh , Blaber Justin A. , Irfanoglu Okan , Barnett Alan , Pierpaoli Carlo , Anderson Adam W. , Landman Bennett A. 
Published: May 2020

ABSTRACTBackgroundAchieving inter-site / inter-scanner reproducibility of diffusion weighted magnetic resonance imaging (DW-MRI) metrics has been challenging given differences in acquisition protocols, analysis models, and hardware factors.PurposeMagnetic field gradients impart scanner-dependent spatial variations in the applied diffusion weighting that can be corrected if the gradient nonlinearities are known. However, retrieving manufacturer nonlinearity specifications is not well supported and may introduce errors in interpretation of units or coordinate systems. We propose an empirical approach to mapping the gradient nonlinearities with sequences that are supported across the major scanner vendors.Study TypeProspective observational studySubjectsA spherical isotropic diffusion phantom, and a single human control volunteerField Strength/Sequence3T (two scanners). Stejskal-Tanner spin echo sequence with b-values of 1000, 2000 s/mm2with 12, 32, and 384 diffusion gradient directions per shell.AssessmentWe compare the proposed correction with the prior approach using manufacturer specifications against typical diffusion pre-processing pipelines (i.e., ignoring spatial gradient nonlinearities). In phantom data, we evaluate metrics against the ground truth. In human and phantom data, we evaluate reproducibility across scans, sessions, and hardware.Statistical TestsWilcoxon rank-sum test between uncorrected and corrected data.ResultsIn phantom data, our correction method reduces variation in mean diffusivity across sessions over uncorrected data (p<0.05). In human data, we show that this method can also reduce variation in mean diffusivity across scanners (p<0.05).ConclusionOur method is relatively simple, fast, and can be applied retroactively. We advocate incorporating voxel-specific b-value and b-vector maps should be incorporated in DW-MRI harmonization preprocessing pipelines to improve quantitative accuracy of measured diffusion parameters.
Human es-fMRI Resource: Concurrent deep-brain stimulation and whole-brain functional MRI
Authors: Thompson WH , Nair R , Oya H , Esteban O , Shine JM , Petkov CI , Poldrack RA , Howard M , Adolphs R 
Published: May 2020

AbstractMapping the causal effects of one brain region on another (effective connectivity) is a challenging problem in neuroscience, since it requires invasive direct manipulation of brain function, together with whole-brain measurement of the effects produced. Here we establish a unique resource and present data from 26 human patients who underwent electrical stimulation during functional magnetic resonance imaging (es-fMRI). The patients had medically refractory epilepsy requiring surgically implanted intracranial electrodes in cortical and subcortical locations. One or multiple contacts on these electrodes were stimulated while simultaneously recording BOLD-fMRI activity in a block design. Multiple runs exist for patients with different stimulation sites. We describe the resource, data collection process, preprocessing using the fMRIPrep analysis pipeline and management of artifacts, and provide end-user analyses to visualize distal brain activation produced by site-specific electrical stimulation. The data are organized according to the brain imaging data structure (BIDS) specification, and are available for analysis or future dataset contributions on openneuro.org including both raw and preprocessed data.
Fast and Comprehensive N- and O-glycoproteomics analysis with MSFragger-Glyco
Authors: Polasky Daniel A. , Yu Fengchao , Teo Guo Ci , Nesvizhskii Alexey I. 
Published: May 2020

AbstractGlycosylation is a ubiquitous and heterogeneous post-translational modification (PTM) used to accomplish a wide variety of critical cellular tasks. Recent advances in methods for enrichment and mass spectrometric analysis of intact glycopeptides have produced large-scale, high-quality glycoproteomics datasets, but interpreting this data remains challenging. In addition to being large, complex, and heterogeneous, glycans undergo fragmentation during vibrational activation, making common PTM search strategies ineffective for their identification. We present a computational tool called MSFragger-Glyco for fast and highly sensitive identification of N- and O-linked glycopeptides using open and glycan mass offset search strategies. Reanalysis of recently published N-glycoproteomics data resulted in annotation of 83% more glycopeptide-spectrum matches (glycoPSMs) than in previous results, which translated to substantial increases in the numbers of glycoproteins and glycosites that could be identified. In published O-glycoproteomics data, our method more than doubled the number of glycoPSMs annotated when searching the same peptides as the original search and resulted in up to a 6-fold increase when expanding searches to include large numbers of possible glycan compositions and other modifications. Expanded searches revealed trends in glycan composition and crosstalk with phosphorylation that remained hidden to the original search. With greatly improved spectral annotation, coupled with the fast speed of fragment ion index-based scoring, MSFragger-Glyco makes it possible to comprehensively interrogate glycoproteomics data and illuminate the many roles of glycosylation.
Reads2Resistome: An adaptable and high-throughput whole-genome sequencing pipeline for bacterial resistome characterization
Authors: Woyda Reed , Oladeinde Adelumola , Abdo Zaid 
Published: May 2020

AbstractSummaryThe bacterial resistome is the collection of all the antibiotic resistance genes, virulence genes, and other resistance elements within a bacterial isolate genome including plasmids and bacteriophage regions. Accurately characterizing the resistome is crucial for prevention and mitigation of emerging antibiotic resistance threats to animal and human health. Reads2Resistome is a tool which allows researchers to assemble and annotate bacterial genomes using long or short read sequencing technologies or both in a hybrid approach. Using a massively parallel analysis pipeline, Reads2Resistome performs assembly, annotation and resistome characterization with the goal of producing an accurate and comprehensive description of a bacterial genome and resistome contents. Key features of the Reads2Resistome pipeline include quality control of input sequencing reads, genome assembly, genome annotation, resistome characterization and alignment. All prerequisite dependencies come packaged together in a single suit which can easily be downloaded and run on Linux and Mac operating systems.AvailabilityReads2Resistome is freely available as an open-source package under the MIT license, and can be downloaded via GitHub (https://github.com/BioRRW/Reads2Resistome).
Netome: The Molecular Characterization of Neutrophil Extracellular Traps (NETs)
Authors: Scieszka David , Lin Yi-Han , Li Weizhong , Choudhury Saibyasachi , Yu Yanbao , Freire Marcelo 
Published: May 2020

AbstractNeutrophils are the most abundant type of white blood cells in humans with biological roles relevant to inflammation and fighting infections. The release of neutrophil extracellular DNA aims to control invasion by bacteria, viruses, fungi, and tissue damage. Neutrophil Extracellular Traps (NETs) act as antimicrobial agents triggering immune signaling through the release of the nuclear content into the extracellular space. Although intense investigations have elucidated the pathways preceding NET formation, the exact molecular composition of released NETs has not been mapped. We aimed to decode the sequences of DNA and proteins from NETs. With emerging needs to understand neutrophil functions precisely, we open the field of NETOMIC studies through isolation of NETs in combination with omics approaches including shotgun genomics and proteomics. Our in vitro NET isolation methodology allowed for unprecedented replicability with induction in a sterile inflammation model system. Enrichment of mitochondrial DNA and telomere sequences are significantly expressed in NET genomes. This study revealed that the genomic sequence released in the extracellular milieu is not stochastically serving as a scaffold for a repertoire of proteins involved in neutrophil protective functions. Collectively, we established the gene and protein signatures exclusive to the extracellular NETs in comparison to undifferentiated and differentiated neutrophil states, further guiding future detection of specific regions needed for diagnostics and targeted therapies of NET related conditions.
Effects of age on pre-stimulus neural activity predictive of successful memory encoding: an fMRI study
Authors: Liu E. Song , Koen Joshua D. , Rugg Michael D. 
Published: May 2020

AbstractPre-stimulus subsequent memory effects (SMEs) – differences in neural activity preceding the onset of study items that are predictive of later memory performance – have consistently been reported in young adults. The present fMRI experiment investigated potential age-related differences in pre-stimulus SMEs. During study, healthy young and older participants made one of two semantic judgments on images, with the judgment signaled by a preceding cue. In the test phase, participants first made an item recognition judgment and, for each item judged old, a source memory judgment. Age-invariant pre-stimulus SMEs were observed in left dorsomedial prefrontal cortex, left hippocampus, and right subgenual cortex. In each case, the effects reflected lower BOLD signal for later recognized items, regardless of source accuracy, than unrecognized items. A similar age-invariant pattern was observed in left orbitofrontal cortex, but the effect in this region was specific to items attracting a correct source response compared to unrecognized items. In contrast, the left angular gyrus and fusiform cortex demonstrated negative pre-stimulus SMEs that were exclusive to young participants. The findings indicate that age differences in pre-stimulus SMEs are regionally specific and suggest that pre-stimulus SMEs reflect multiple cognitive processes, only some of which are vulnerable to advancing age.
Ant community potential for pest control in olive groves: management and landscape effects
Authors: Martínez-Núñez Carlos , Rey Pedro J. , Salido Teresa , Manzaneda Antonio J. , Camacho Francisco M. , Isla Jorge 
Published: May 2020

AbstractAnts are important pest control agents in many agroecosystems worldwide. However, little is known about how management, ecological contrast generated by different agricultural practices, and landscape complexity affect their communities and the potential pest control that they can provide.Here, we surveyed ant communities in 40 paired olive groves with different ground-herb cover management across 20 localities spanning a wide range of landscape complexity at the regional scale. We also conducted experiments with dummy plasticine models in 18 of these groves to explore the ant potential to control the two main pests of the olive tree (olive moth and olive fly). In addition, we calculated an index, the Ant-community Predation Function (APF), which informs about the predation pressure exerted by ant communities over these pests.Results show that: a) extensive management at intermediate landscape complexity maximizes the abundance and pest control by ants; b) the ecological contrast affects ant abundance and ant richness but does not impact the predation function; c) APF is a good measure of pest control potential at the community level; and, d)Tapinoma nigerrimumis an important ant species for pest control in our system, which seems little affected by local or landscape heterogeneity.This study advances our knowledge about local management and landscape effects on ants and their potential contribution to pest control in olive groves. Extensive herb cover management and landscape heterogeneity increased ant predation pressure in olive groves.
Cell cycle-gated feedback control mediates desensitization to interferon stimulation
Authors: Mudla Anusorn , Jiang Yanfei , Arimoto Kei-ichiro , Xu Bingxian , Rajesh Adarsh , Ryan Andy P , Wang Wei , Daugherty Matthew D , Zhang Dong-Er , Hao Nan 
Published: May 2020

AbstractCells use sophisticated molecular circuits to interpret and respond to extracellular signal factors, such as hormones and cytokines, which are often released in a temporally varying fashion. In this study, we focus on type I interferon (IFN) signaling in human epithelial cells and combine microfluidics, time-lapse microscopy, and computational modeling to investigate how the IFN-responsive regulatory network operates in single cells to process repetitive IFN stimulation. We found that IFN-α pretreatments lead to opposite effects, priming versus desensitization, depending on the input durations. These effects are governed by a regulatory network composed of a fast-acting positive feedback loop and a delayed negative feedback loop, mediated by upregulation of ubiquitin-specific peptidase 18 (USP18). We further revealed that USP18 upregulation can only be initiated at the G1 and early S phases of cell cycle upon the treatment onset, resulting in heterogeneous and delayed induction kinetics in single cells. This cell cycle gating provides a temporal compartmentalization of feedback control processes, enabling duration-dependent desensitization to repetitive stimulations. Moreover, our results, highlighting the importance of IFN dynamics, may suggest time-based strategies for enhancing the effectiveness of IFN pretreatment in clinical applications against viruses, such as SARS-CoV-2.
In-VivoToxicity Studies andIn-VitroInactivation of SARS-CoV-2 by Povidone-iodineIn-situGel Forming Formulations
Authors: Liang Bo , Yuan Xudong , Wei Gang , Wang Wei , Zhang Ming , Peng Haizhou , Javer Amin , Mendenhall Michelle , Julander Justin , Huang Sammi , Michail Hany , Lu Yong , Zhu Qi , Baldwin John 
Published: May 2020

AbstractTo curb the spread of SARS-CoV-2, the etiologic agent of the COVID-19 pandemic, we characterize the virucidal activity of long-acting Povidone Iodine (PVP-I) compositions developed using anin-situgel forming technology. The PVP-I gel forming nasal spray (IVIEW-1503) and PVP-I gel forming ophthalmic eye drop (IVIEW-1201) rapidly inactivated SARS-CoV-2, inhibiting the viral infection of VERO76 cells. No toxicity was observed for the PVP-I formulations. Significant inactivation was noted with preincubation of the virus with these PVP-I formulations at the lowest concentrations tested. It has been demonstrated that both PVP-I formulations can inactivate SARS-CoV-2 virus efficiently in both a dose-dependent and a time-dependent manner. These results suggest IVIEW-1503 and IVIEW-1201 could be potential agents to reduce or prevent the transmission of the virus through the nasal cavity and the eye, respectively. Further studies are needed to clinically evaluate these formulations in early-stage COVID-19 patients.
The H-NS regulator plays a role in the stress induced by carbapenemase expression inAcinetobacter baumannii
Authors: Huang Fanny , Fitchett Noelle , Razo-Gutierrez Chelsea , Le Casin , Ra Grace , Lopez Carolina , Gonzalez Lisandro J. , Sieira Rodrigo , Vila Alejandro J. , Bonomo Robert A. , Ramirez Maria Soledad 
Published: May 2020

AbstractDisruption of the histone-like nucleoid structuring protein (H-NS) was shown to affect the ability for Gram-negative bacteria to regulate genes associated with virulence, persistence, stress response, quorum sensing, biosynthesis pathways and cell adhesion. Here, we used the expression of metallo-β-lactamases (MBLs) known to elicit envelope stress by the accumulation of toxic species in the periplasm to interrogate the role of H-NS inAcinetobacter baumannii, together with other stressors. Using a multidrug-resistantA. baumannii, we observed that H-NS plays a role in alleviating the stress triggered by MBL toxic precursors and counteract the effect of DNA-damaging agents, supporting its role in stress response.ImportanceCarbapenem-resistantA. baumannii(CRAB) is recognized as one of the most threatening gram-negative bacilli. H-NS is known to play a role in controlling the transcription of a variety of different genes, including those associated with stress response, persistence and virulence. In the present work, we uncovered a link between the role of H-NS in theA. baumanniistress response and its relationship with the envelope stress response and resistance to DNA-damaging agents. Overall, we posit a new role of H-NS, showing that H-NS serves to endure envelope stress that could also be a mechanism that alleviates the stress induced by MBL expression inA. baumannii. This could be an evolutionary advantage to further resist the action of carbapenems.
Risk factors associated with mortality of COVID-19 in 3125 counties of the United States
Authors: Tian Ting , Zhang Jingwen , Hu Liyuan , Jiang Yukang , Duan Congyuan , Li Zhongfei , Wang Xueqin , Zhang Heping 
Published: May 2020

AbstractBackgroundThe number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March 2020. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States.MethodsTo find out the risk factors associated with county-level mortality of COVID-19 with various levels of prevalence, a negative binomial design was applied to the county-level mortality counts of COVID-19 as of August 27, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-varying cumulative confirmed cases from March 1 to August 27, 2020. COVID-19 patients were not analyzed individually but were aggregated at the county-level, where the county-level deaths of COVID-19 confirmed by the local health agencies.Results3125 infected counties were assigned into three classes corresponding to low, median, and high prevalence levels of infection. Several risk factors were significantly associated with the mortality counts of COVID-19, where higher level of air pollution (0.153,P<0.001) increased the mortality in the low prevalence counties and elder individuals were more vulnerable in both the median and high prevalence counties. The segregation between non-Whites and Whites and higher Hispanic population had higher likelihood of risk of the deaths in all infected counties.ConclusionsThe mortality of COVID-19 depended on sex, race/ethnicity, and outdoor environment. The increasing awareness of the impact of these significant factors may lead to the reduction in the mortality of COVID-19.
A Novel Smart City Based Framework on Perspectives for application of Machine Learning in combatting COVID-19
Authors: Ezugwu Absalom E. , Hashem Ibrahim A.T. , Oyelade Olaide N. , Chiroma Haruna , Al-Garadi Mohammed A. , Abdullahi Idris N. , Otegbeye Olumuyiwa , Shukla Amit K. , Almutari Mubarak 
Published: May 2020

AbstractThe spread of COVID-19 across the world continues as efforts are being made from multi-dimension to curtail its spread and provide treatment. The COVID-19 triggered partial and full lockdown across the globe in an effort to prevent its spread. COVID-19 causes serious fatalities with United States of America recording over 3,000 deaths within 24 hours, the highest in the world for a single day and as of October 2020 has recorded a total of 270,642 death toll. In this paper, we present a novel framework which intelligently combines machine learning models and internet of things (IoT) technology specific in combatting COVID-19 in smart cities. The purpose of the study is to promote the interoperability of machine learning algorithms with IoT technology in interacting with a population and its environment with the aim of curtailing COVID-19. Furthermore, the study also investigates and discusses some solution frameworks, which can generate, capture, store and analyze data using machine learning algorithms. These algorithms are able to detect, prevent, and trace the spread of COVID-19, and provide better understanding of the virus in smart cities. Similarly, the study outlined case studies on the application of machine learning to help in the fight against COVID-19 in hospitals across the world. The framework proposed in the study is a comprehensive presentation on the major components needed for an integration of machine learning approach with other AI-based solutions. Finally, the machine learning framework presented in this study has the potential to help national healthcare systems in curtailing the COVID-19 pandemic in smart cities. In addition, the proposed framework is poised as a point for generating research interests which will yield outcomes capable of been integrated to form an improved framework.
Evidence for motility in 3.4 Gyr-old organic-walled microfossils ?
Authors: Delarue F. , Bernard S. , Sugitani K. , Robert F. , Tartèse R. , Albers S.-V. , Duhamel R. , Pont S. , Derenne S. 
Published: May 2020

AbstractThe oldest traces for planktonic lifestyle have been reported in ca. 3.4 billion years old silicified sediments from the Strelley Pool Formation in Western Australia. Observation of flange appendages suggests that Archean life motility was passive and driven by drifting of microorganisms in their surrounding environment. Until now, the oldest traces for active motility are ca. 2.1 billion years old. Whether or not active motility already existed during the Archean eon remains an open question. Here we report the discovery of new 3.4 billion years old tailed microfossils. These microfossils exhibit a lash-like appendage that likely provided them with movement capabilities. This suggests that these microfossils are the oldest remains of active motile life forms. With the ability to move in liquids and on organic and/or mineral surfaces, these microorganisms were capable of escaping from harsh environments and/or colonizing new ecological niches as early as 3.4 billion years ago. The existence of these deep-rooted Archean motile life forms offers a new picture of the Archean biodiversity, with unanticipated evolutionary innovative morphological complexities.
Prediction of the virus incubation period for COVID-19 and future outbreaks
Authors: Gussow Ayal B. , Auslander Noam , Wolf Yuri I. , Koonin Eugene V. 
Published: May 2020

AbstractA crucial factor in mitigating respiratory viral outbreaks is early determination of the duration of the incubation period and, accordingly, the required quarantine time for potentially exposed individuals. Here, we explore different genomic features of RNA viruses that correlate with the incubation times and provide a predictive model that accurately estimates the upper limit incubation time for diverse viruses including SARS-CoV-2, and thus, could help control future outbreaks.