bluuebunny/crossref_metadata_2025_split huggingface dataset:
Temporal increase in D614G mutation of SARS-CoV-2 in the Middle East and North Africa: Phylogenetic and mutation analysis study
Authors: Sallam Malik , Ababneh Nidaa A. , Dababseh Deema , Bakri Faris G. , Mahafzah Azmi 
Published: August 2020

AbstractPhylogeny construction can help to reveal evolutionary relatedness among molecular sequences. The spike (S) gene of SARS-CoV-2 is the subject of an immune selective pressure which increases the variability in such region. This study aimed to identify mutations in theSgene among SARS-CoV-2 sequences collected in the Middle East and North Africa (MENA), focusing on the D614G mutation, that has a presumed fitness advantage. Another aim was to analyze theSgene sequences phylogenetically. The SARS-CoV-2Sgene sequences collected in the MENA were retrieved from the GISAID public database, together with its metadata. Mutation analysis was conducted in Molecular Evolutionary Genetics Analysis software. Phylogenetic analysis was done using maximum likelihood (ML) and Bayesian methods. A total of 553 MENA sequences were analyzed and the most frequentSgene mutations included: D614G = 435, Q677H = 8, and V6F = 5. A significant increase in the proportion of D614G was noticed from (63.0%) in February 2020, to (98.5%) in June 2020 (p< 0.001). Two large phylogenetic clusters were identified via ML analysis, which showed an evidence of inter-country mixing of sequences, which dated back to February 8, 2020 and March 15, 2020 (median estimates). The mean evolutionary rate for SARS-CoV-2 was about 6.5 × 10−3substitutions/site/year based on large clusters’ Bayesian analyses. The D614G mutation appeared to be taking over the COVID-19 infections in the MENA. Bayesian analysis suggested that SARS-CoV-2 might have been circulating in MENA earlier than previously reported.
Three-dimensional convolutional autoencoder extracts features of structural brain images with a “diagnostic label-free” approach: Application to schizophrenia datasets
Authors: Yamaguchi Hiroyuki , Hashimoto Yuki , Sugihara Genichi , Miyata Jun , Murai Toshiya , Takahashi Hidehiko , Honda Manabu , Hishimoto Akitoyo , Yamashita Yuichi 
Published: August 2020

ABSTRACTThere has been increasing interest in performing psychiatric brain imaging studies using deep learning. However, most studies in this field disregard three-dimensional (3D) spatial information and targeted disease discrimination, without considering the genetic and clinical heterogeneity of psychiatric disorders. The purpose of this study was to investigate the efficacy of a 3D convolutional autoencoder (CAE) for extracting features related to psychiatric disorders without diagnostic labels. The network was trained using a Kyoto University dataset including 82 patients with schizophrenia (SZ) and 90 healthy subjects (HS), and was evaluated using Center for Biomedical Research Excellence (COBRE) datasets including 71 SZ patients and 71 HS. The proposed 3D-CAEs were successfully reconstructed into high-resolution 3D structural magnetic resonance imaging (MRI) scans with sufficiently low errors. In addition, the features extracted using 3D-CAE retained the relevant clinical information. We explored the appropriate hyper parameter range of 3D-CAE, and it was suggested that a model with eight convolution layers might be relevant to extract features for predicting the dose of medication and symptom severity in schizophrenia.
Estimating encounter location distributions from animal tracking data
Authors: Noonan Michael J. , Martinez-Garcia Ricardo , Davis Grace H. , Crofoot Margaret C. , Kays Roland , Hirsch Ben T. , Caillaud Damien , Payne Eric , Sih Andrew , Sinn David L. , Spiegel Orr , Fagan William F. , Fleming Christen H. , Calabrese Justin M. 
Published: August 2020

AbstractEcologists have long been interested in linking individual behavior with higher-level processes. For motile species, this ‘upscaling’ is governed by how well any given movement strategy maximizes encounters with positive factors, and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modeling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounterrateswhile no theoretical framework exists for directly relating individual movement with the spatiallocationsof encounter events in the environment.Here, we bridge this gap by introducing a new theoretical concept describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open source software, and demonstrate the broad ecological relevance of this novel concept.We first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: i) a population of individuals with home ranges that overlap with neighbors; ii) a pair of individuals with a hard territorial border between their home ranges; and iii) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins (Cebus capucinus) tracked on Barro Colorado Island, Panama, and sleepy lizards (Tiliqua rugosa) tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the location-specific potential for competition, and/or identify any changes in behaviour that directly result from location-specific encounter probability.This novel target distribution enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialised data collection protocols. This method is now openly available via the ctmm R package.
Elements and Evolutionary Determinants of Genomic Divergence Between Paired Primary and Metastatic Tumors
Authors: Sun Ruping , Nikolakopoulos Athanasios N. 
Published: August 2020

ABSTRACTCan metastatic-primary (M-P) genomic divergence measured from next generation sequencing reveal the natural history of metastatic dissemination? This remains an open question of utmost importance in facilitating a deeper understanding of metastatic progression, and thereby, improving its prevention. Here, we utilize mathematical and computational modeling to tackle this question as well as to provide a framework that illuminates the fundamental elements and evolutionary determinants of M-P divergence. Our framework facilitates the integration of sequencing detectability of somatic variants, and hence, paves the way towards bridging the measurable between-tumor heterogeneity with analytical modeling and interpretability. We show that the number of somatic variants of the metastatic seeding cell that are experimentally undetectable in the primary tumor, can be characterized as the path of the phylogenetic tree from the last appearing variant of the seeding cell back to the most recent detectable variant. We find that the expected length of this path is principally determined by the decay in detectability of the variants along the seeding cell’s lineage; and thus, exhibits a significant dependence on the underlying tumor growth dynamics. A striking implication of this fact, is that dissemination from an advanced detectable subclone of the primary tumor can lead to an abrupt drop in the expected measurable M-P divergence, thereby breaking the previously assumed monotonic relation between seeding time and M-P divergence. This is emphatically verified by our single cell-based spatial tumor growth simulation, where we find that M-P divergence exhibits a non-monotonic relationship with seeding time when the primary tumor grows under branched and linear evolution. On the other hand, a monotonic relationship holds when we condition on the dynamics of progressive diversification, or by restricting the seeding cells to always originate from undetectable subclones. Our results highlight the fact that a precise understanding of tumor growth dynamics is thesine qua nonfor exploiting M-P divergence to reconstruct the chronology of metastatic dissemination. The quantitative models presented here enable further careful evaluation of M-P divergence in association with crucial evolutionary and sequencing parameters.Graphical AbstractHighlightsDepth of most recent detectable variant characterizes Metastatic-Primary divergenceDecay in variant detectability determines the expected M-P divergenceDissemination from late detectable subclone leads to an abrupt drop in M-P divergenceSpatial model verifies growth mode governs M-P divergence dependency on seeding time
Genome-wide diversity and differentiation of two novel multidrug-resistant populations ofPasteurella multocidatype B:2 from fowl cholera
Authors: Saha Otun , Islam M. Rafiul , Rahman M. Shaminur , Hoque M. Nazmul , Hossain M. Anwar , Sultana Munawar 
Published: August 2020

ABSTRACTPasteurella multocidais the etiologic agent of fowl cholera (FC), a highly contagious and severe disease in poultry with higher mortality and morbidity. Twenty-twoP. multocidastrains isolated from the FC outbreaks were subjected to phenotypic and genotypic characterization. The isolates were grouped into two distinct RAPD biotypes harboring a range of pathogenic genes;exbB,ompH,ptfA,nanB,sodC, andhgbA. Among these strains, 90.90% and 36.37% were multidrug-resistant and strong biofilm formers, respectively. Whole genome sequencing of the two representative RAPD isolates confirmed asP. multocida typeB:L2:ST122 harboring a number of virulence factors, and antimicrobial resistance genes. Pan-genome analysis revealed 90 unique genes in these genomes associated with versatile metabolic functions, pathogenicity, virulence, and antimicrobial resistance. This study for the first time reports the association ofP. multocidagenotype B:L2:ST122 in the pathogenesis of FC, and provides a genetic context for future researches onP. multocidastrains.
Frequency shapes the quality of tactile percepts evoked through electrical stimulation of the nerves
Authors: Graczyk Emily L. , Christie Breanne P. , He Qinpu , Tyler Dustin J. , Bensmaia Sliman J. 
Published: August 2020

AbstractTouch is critical for our ability to manipulate objects, as evidenced by the deficits incurred when touch is absent. To restore the sense of touch via electrical stimulation of the peripheral nerves requires that we understand how the parameters of stimulation shape the evoked sensation. To this end, we investigated the sensory consequences of changing the frequency of pulse trains (PF) delivered to the peripheral nerves of humans chronically implanted with multi-channel nerve cuff electrodes. We found that increases in PF led to systematic increases in perceived frequency, up to about 50 Hz, at which point further changes in PF had little to no impact on sensory quality. Above this transition frequency, ratings of perceived frequency levelled off, the ability to discriminate changes in PF was abolished, and verbal descriptors selected to characterize the sensation changed abruptly. We conclude that the quality of electrically evoked tactile sensations can be shaped by imposing temporal patterns on a fixed neural population, but this temporal patterning can only be resolved up to about 50 Hz. These findings highlight the importance of spike timing in shaping the quality of a sensation and will contribute to the development of encoding strategies for conveying touch feedback through bionic hands and feet.
Human ACE2 peptide mimics block SARS-CoV-2 Pulmonary Cells Infection
Authors: Karoyan Philippe , Vieillard Vincent , Odile Estelle , Denis Alexis , Guihot Amélie , Luyt Charles-Edouard , Gómez-Morales Luis , Grondin Pascal , Lequin Olivier 
Published: August 2020

AbstractIn the light of the recent accumulated knowledge on SARS-CoV-2 and its mode of human cells invasion, the binding of viral spike glycoprotein to human Angiotensin Converting Enzyme 2 (hACE2) receptor plays a central role in cell entry. We designed a series of peptides mimicking the N-terminal helix of hACE2 protein which contains most of the contacting residues at the binding site and have a high helical folding propensity in aqueous solution. Our best peptide mimics bind to the virus spike protein with high affinity and are able to block SARS-CoV-2 human pulmonary cell infection with an inhibitory concentration (IC50) in the nanomolar range. These first in class blocking peptide mimics represent powerful tools that might be used in prophylactic and therapeutic approaches to fight the coronavirus disease 2019 (COVID-19).
Binary decision between asymmetric and symmetric cell division is defined by the balance of PAR proteins inC. elegansembryos
Authors: Lim Yen Wei , Wen Fu-Lai , Shankar Prabhat , Shibata Tatsuo , Motegi Fumio 
Published: August 2020

ABSTRACTCoordination between cell differentiation and proliferation during development requires the balance between asymmetric and symmetric modes of cell division. However, the cellular intrinsic cue underlying the binary choice between these two division modes remains elusive. Here we show evidence inCaenorhabditis elegansthat the invariable lineage of the division modes is programmed by the balance between antagonizing complexes of partitioning-defective (PAR) proteins. By uncoupling unequal inheritance of PAR proteins from that of fate determinants during zygote division, we demonstrated that changes in the balance between PAR-2 and PAR-6 are sufficient to re-program the division modes from symmetric to asymmetric andvice versain two-cell stage embryos. The division mode adopted occurs independently of asymmetry in cytoplasmic fate determinants, cell-size asymmetry, and cell-cycle asynchrony between the sister cells. We propose that the balance between antagonizing PAR proteins represents an intrinsic self-organizing cue for binary specification of the division modes during development.
StackPDB: predicting DNA-binding proteins based on XGB-RFE feature optimization and stacked ensemble classifier
Authors: Zhang Qingmei , Liu Peishun , Han Yu , Zhang Yaqun , Wang Xue , Yu Bin 
Published: August 2020

ABSTRACTDNA binding proteins (DBPs) not only play an important role in all aspects of genetic activities such as DNA replication, recombination, repair, and modification but also are used as key components of antibiotics, steroids, and anticancer drugs in the field of drug discovery. Identifying DBPs becomes one of the most challenging problems in the domain of proteomics research. Considering the high-priced and inefficient of the experimental method, constructing a detailed DBPs prediction model becomes an urgent problem for researchers. In this paper, we propose a stacked ensemble classifier based method for predicting DBPs called StackPDB. Firstly, pseudo amino acid composition (PseAAC), pseudo position-specific scoring matrix (PsePSSM), position-specific scoring matrix-transition probability composition (PSSM-TPC), evolutionary distance transformation (EDT), and residue probing transformation (RPT) are applied to extract protein sequence features. Secondly, extreme gradient boosting-recursive feature elimination (XGB-RFE) is employed to gain an excellent feature subset. Finally, the best features are applied to the stacked ensemble classifier composed of XGBoost, LightGBM, and SVM to construct StackPDB. After applying leave-one-out cross-validation (LOOCV), StackPDB obtains high ACC and MCC on PDB1075, 93.44% and 0.8687, respectively. Besides, the ACC of the independent test datasets PDB186 and PDB180 are 84.41% and 90.00%, respectively. The MCC of the independent test datasets PDB186 and PDB180 are 0.6882 and 0.7997, respectively. The results on the training dataset and the independent test dataset show that StackPDB has a great predictive ability to predict DBPs.
Causal Understanding of the Stone Dropping Task in Two Species of Macaw
Authors: O’Neill Laurie , Picaud Anthony , Hastings Ronan , Buffenoir Nina , Gahr Manfred , von Bayern Auguste M.P. 
Published: August 2020

AbstractCausal understanding in animal cognition can be divided into two broad categories (Woodward, 2011): learned associations between cause and effect (Le Pelley et al., 2017) and understanding based on underlying mechanisms (Johnson and Ahn, 2017). One experiment that gives insight to animals’ use of causal mechanisms is the stone-dropping task. In this, subjects are given an opportunity to push a platform to make it collapse and are then required to innovate dropping a stone tool to recreate the platform collapsing (von Bayern et al., 2009). We describe how 16/18 subjects of two species of macaw (n=18; Ara ambiguus (n=9) & Ara glaucogularis (n=9)) were able to innovate the solution in this task. Many of the subjects were able to innovate the behaviour through exploratory object combination, but it is also possible that a mechanistic understanding of the necessity for contact with the platform influenced some subjects’ behaviour. All the successful subjects were able to recreate their novel stone-dropping behaviour in the first or second trial after innovation (and all trials thereafter) and they were also able to do the behaviour increasingly faster. This suggests they also rely on learned associations of cause and effect. However, in a transfer task in which subjects had to guide a stick tool to make it touch a differently positioned platform, all but one of the subjects failed. This would suggest that the majority of the subjects were not using an understanding of platform contact to solve the task, although the subjects’ difficulty with using stick tools may have also affected their performance in this transfer.
Methods for detecting PER2::LUCIFERASE bioluminescence rhythms in freely moving mice
Authors: Martin-Burgos B. , Wang W. , William I. , Tir S. , Mohammad I. , Javed R. , Smith S. , Cui Y. , Smith C.B. , van der Vinne V. , Molyneux P.C. , Miller S.C. , Weaver D. R. , Leise T.L. , Harrington M.E. 
Published: August 2020

AbstractCircadian rhythms are driven by daily oscillations of gene expression. An important tool for studying cellular and tissue rhythms is the use of a gene reporter, such as bioluminescence from the reporter gene luciferase controlled by a rhythmically expressed gene of interest. Here we describe methods that allow measurement of bioluminescence from a freely-moving mouse housed in a standard cage. Using a LumiCycleIn Vivo(Actimetrics), we determined conditions that allow detection of circadian rhythms of bioluminescence from the PER2 reporter, PER2::LUC, in freely behaving mice. We tested delivery of D-luciferin via a subcutaneous minipump and in the drinking water. Further, we demonstrate that a synthetic luciferase substrate, CycLuc1, can support circadian rhythms of bioluminescence, even when delivered at a lower concentration than D-luciferin. We share our analysis scripts and suggestions for further improvements in this method. This approach will be straightforward to apply to mice with tissue-specific reporters, allowing insights into responses of specific peripheral clocks to perturbations such as environmental or pharmacological manipulations.
SARS-CoV-2 neutralizing human antibodies protect against lower respiratory tract disease in a hamster model
Authors: Haagmans Bart L. , Noack Danny , Okba Nisreen M.A. , Li Wentao , Wang Chunyan , Bestebroer Theo , de Vries Rory , Herfst Sander , de Meulder Dennis , van Run Peter , Lamers Mart M. , Rijnders Bart , Rokx Casper , van Kuppeveld Frank , Grosveld Frank , Drabek Dubravka , GeurtsvanKessel Corine , Koopmans Marion , Bosch Berend Jan , Kuiken Thijs , Rockx Barry 
Published: August 2020

ABSTRACTEffective clinical intervention strategies for COVID-19 are urgently needed. Although several clinical trials have evaluated the use of convalescent plasma containing virus-neutralizing antibodies, the effectiveness has not been proven. We show that hamsters treated with a high dose of human convalescent plasma or a monoclonal antibody were protected against weight loss showing reduced pneumonia and pulmonary virus replication compared to control animals. However, a ten-fold lower dose of convalescent plasma showed no protective effect. Thus, variable and relatively low levels of virus neutralizing antibodies in convalescent plasma may limit their use for effective antiviral therapy, favouring concentrated, purified (monoclonal) antibodies.
Synchrony between daily rhythms of malaria parasites and hosts is driven by an essential amino acid
Authors: Prior Kimberley F. , Middleton Benita , T.Y. Owolabi Alíz , Westwood Mary L. , Holland Jacob , O’Donnell Aidan J. , Blackman Mike , Skene Debra J. , Reece Sarah E. 
Published: August 2020

AbstractRapid asexual replication of blood stage malaria parasites is responsible for the severity of disease symptoms and fuels the production of transmission forms. That malaria parasite species coordinate their cycles of asexual replication with daily rhythms of their host was discovered in the Hippocratic era, but how and why this occurs is enigmatic. Here, we demonstrate that thePlasmodium chabaudi’sschedule for asexual replication can be orchestrated by a isoleucine, metabolite provided to the parasite in periodic manner due to the host’s rhythmic intake of food. First, we identify nutrients with daily rhythms in the blood that match the timing of rhythms in both host feeding and the developmental schedule of asexually replicating parasites. We hypothesise that if parasites set their own developmental schedule, they should use a time-of-day cue that is a factor they cannot generate endogenously at any time-of-day, or scavenge in a round-the-clock manner. Our large-scale metabolomics experiment reveals that only one metabolite - the amino acid isoleucine – fits these criteria. Second, further experiments reveal that parasites alter the developmental schedule of asexual stages in response to isoleucine provision and withdrawal in the manner consistent with it acting as a time-cue. Specifically, parasites respond to isoleucine loss by slowing development. This is a parasite strategy rather than the consequences of an imposed constraint, because unlike when parasites are deprived of other essential nutrients, they suffer no apparent costs in the absence of isoleucine. Overall, our data suggest parasites can use the daily rhythmicity of blood-isoleucine concentration to synchronise asexual development with the availability of isoleucine, and potentially other resources, that arrive in the blood in a periodic manner due to the host’s daily feeding-fasting cycle. Identifying both how and why parasites keep time opens avenues for interventions; interfering with the parasite’s time-keeping mechanism may stall replication, increasing the efficacy of drugs and immune responses, and could also prevent parasites from entering dormancy to tolerate drugs.