bluuebunny/crossref_metadata_2025_split huggingface dataset:
Data-driven machine learning models for decoding speech categorization from evoked brain responses
Authors: Mahmud Md Sultan , Yeasin Mohammed , Bidelman Gavin M. 
Published: August 2020

ABSTRACTCategorical perception (CP) of audio is critical to understand how the human brain perceives speech sounds despite widespread variability in acoustic properties. Here, we investigated the spatiotemporal characteristics of auditory neural activity that reflects CP for speech (i.e., differentiates phonetic prototypes from ambiguous speech sounds). We recorded high density EEGs as listeners rapidly classified vowel sounds along an acoustic-phonetic continuum. We used support vector machine (SVM) classifiers and stability selection to determine when and where in the brain CP was best decoded across space and time via source-level analysis of the event related potentials (ERPs). We found that early (120 ms) whole-brain data decoded speech categories (i.e., prototypical vs. ambiguous speech tokens) with 95.16% accuracy [area under the curve (AUC) 95.14%; F1-score 95.00%]. Separate analyses on left hemisphere (LH) and right hemisphere (RH) responses showed that LH decoding was more robust and earlier than RH (89.03% vs. 86.45% accuracy; 140 ms vs. 200 ms). Stability (feature) selection identified 13 regions of interest (ROIs) out of 68 brain regions (including auditory cortex, supramarginal gyrus, and Brocas area) that showed categorical representation during stimulus encoding (0-260 ms). In contrast, 15 ROIs (including fronto-parietal regions, Broca’s area, motor cortex) were necessary to describe later decision stages (later 300 ms) of categorization but these areas were highly associated with the strength of listeners’ categorical hearing (i.e., slope of behavioral identification functions). Our data-driven multivariate models demonstrate that abstract categories emerge surprisingly early (∼120 ms) in the time course of speech processing and are dominated by engagement of a relatively compact fronto-temporal-parietal brain network.
CSDE1 is a Post-Transcriptional Regulator of the LDL Receptor
Authors: Smith Geoffrey A. , Padmanabhan Arun , Lau Bryan H. , Pampana Akhil , Li Li , Clara Lee Y. , Pelonero Angelo , Nishino Tomohiro , Sadagopan Nandhini , Jain Rajan , Natarajan Pradeep , Wu Roland S. , Black Brian L. , Srivastava Deepak , Shokat Kevan M. , Chorba John S. 
Published: August 2020

AbstractThe low-density lipoprotein receptor (LDLR) controls cellular delivery of cholesterol and clears LDL from the bloodstream, protecting against atherosclerotic heart disease, the leading cause of death in the United States. We therefore sought to identify regulators of the LDLR beyond the targets of current clinical therapies and known causes of familial hypercholesterolemia. We show that Cold Shock Domain-Containing Protein E1 (CSDE1) enhances hepaticLDLRmRNA decay via its 3’ untranslated region to regulate atherogenic lipoproteinsin vivo. Using parallel phenotypic genome-wide CRISPR interference screens, we found 40 specific regulators of the LDLR left unidentified by observational human genetics. Among these, we show that CSDE1 regulates the LDLR at least as strongly as the mechanistically distinct pathways exploited by the best available clinical therapies: statins and PCSK9 inhibitors. Additionally, we show that hepatic gene silencing ofCsde1treats diet-induced dyslipidemia in mice better than that ofPcsk9. Our results reveal the therapeutic potential of manipulating a newly identified key factor in the post-transcriptional regulation of theLDLRmRNA for the prevention of cardiovascular disease. We anticipate that our approach of modelling a clinically relevant phenotype in a forward genetic screen, followed by mechanistic pharmacologic dissection andin vivovalidation, will serve as a generalizable template for the identification of therapeutic targets in other human disease states.One Sentence SummaryA genome-wide CRISPR screen identifies CSDE1 as a key regulator of hepaticLDLRmRNA decayin vivo, making it a promising target for heart disease.Graphical Abstract
L-DOPA dioxygenase of the fly agaric toadstool: revision of thedodAgene sequence and mechanism of enzymatic pigment production
Authors: Soares Douglas M. M. , Gonçalves Letícia C. P. , Machado Caroline O. , Esteves Larissa Cerrato , Stevani Cassius V. , Oliveira Carla C. , Dörr Felipe A. , Pinto Ernani , Adachi Flávia M. M. , Hotta Carlos T. , Bastos Erick L. 
Published: August 2020

ABSTRACTl-DOPA extradiol dioxygenases (DODAs) catalyze the production of betalains and hygroaurins pigments. The sequence of the DODAs found in Caryophyllales and Basidiomycetes are not conserved, although betalains are produced both by plants and fungi. Here we revise the coding region of thedodAgene of fly agaric [Amanita muscaria(L.) Lam.] and describe an alternative start codon downstream that enables the heterologous expression of AmDODA, a promiscuousl-DOPA dioxygenase. AmDODA is 43-amino acid residues shorter than the recombinant DODA previously reported but catalyzes the formation of two isomeric seco-DOPAs that are the biosynthetic precursors of betalains and hygroaurins. The putative active site of AmDODA contains two distinct His-His-Glu motifs that can explain the dual cleavage ofl-DOPA according to the mechanism proposed for non-heme iron-dependent dioxygenases. Upon addition of excessl-DOPA, both the betaxanthin and hygroaurin adducts ofl-DOPA are produced. The kinetic parameters of enzymatic catalysis at pH 8.5 are similar to those reported for otherl-DOPA dioxygenases. The rate constants for the conversion ofl-DOPA into the betalamic acid and muscaflavin were estimated by kinetic modelling allowing the proposal of a mechanism of pigment formation. These results contribute to understanding the biosynthesis of bacterial, fungal and plant pigments, for the biotechnological production of hygroaurins, and for the development of more promiscuous dioxygenases for environmental remediation.
Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs
Authors: Sakurai-Yageta Mika , Kumada Kazuki , Gocho Chinatsu , Makino Satoshi , Uruno Akira , Tadaka Shu , Motoike Ikuko N , Kimura Masae , Ito Shin , Otsuki Akihito , Narita Akira , Kudo Hisaaki , Aoki Yuichi , Danjoh Inaho , Yasuda Jun , Kawame Hiroshi , Minegishi Naoko , Koshiba Seizo , Fuse Nobuo , Tamiya Gen , Yamamoto Masayuki , Kinoshita Kengo 
Published: August 2020

AbstractBackgroundIncreasing the power of genome-wide association studies in diverse populations is important for understanding the genetic determinants of disease risks, and large-scale genotype data are collected by genome cohort and biobank projects all over the world. In particular, ethnic-specific SNP arrays are becoming more important because the use of universal SNP arrays has some limitations in terms of cost-effectiveness and throughput. As part of the Tohoku Medical Megabank Project, which integrates prospective genome cohorts into a biobank, we have been developing a series of Japonica Arrays for genotyping participants based on reference panels constructed from whole-genome sequence data of the Japanese population.ResultsWe designed a novel version of the SNP Array for the Japanese population, called Japonica Array NEO, comprising a total of 666,883 SNPs, including tag SNPs of autosomes and X chromosome with pseudoautosomal regions, SNPs of Y chromosome and mitochondria, and known disease risk SNPs. Among them, 654,246 tag SNPs were selected from an expanded reference panel of 3,552 Japanese using pairwise r2of linkage disequilibrium measures. Moreover, 28,298 SNPs were included for the evaluation of previously identified disease risk SNPs from the literature and databases, and those present in the Japanese population were extracted using the reference panel. The imputation performance of Japonica Array NEO was assessed by genotyping 286 Japanese samples. We found that the imputation quality r2and INFO score in the minor allele frequency bin >2.5%–5% were >0.9 and >0.8, respectively, and >12 million markers were imputed with an INFO score >0.8. After verification, Japonica Arrays were used to efficiently genotype cohort participants from the sample selection to perform a quality assessment of the raw data; approximately 130,000 genotyping data of >150,000 participants has already been obtained.ConclusionsJaponica Array NEO is a promising tool for genotyping the Japanese population with genome-wide coverage, contributing to the development of genetic risk scores for this population and further identifying disease risk alleles among individuals of East Asian ancestry.
TuMV triggers stomatal closure but reduces drought tolerance in Arabidopsis
Authors: Manacorda Carlos Augusto , Gudesblat Gustavo , Sutka Moira , Alemano Sergio , Peluso Franco , Oricchio Patricio , Baroli Irene , Asurmendi Sebastián 
Published: August 2020

i)SummaryIn this work the effects of TuMV infection on stomatal closure and water balance were studied in Arabidopsis. Thermal imaging analyses showed that TuMV-infected plants had consistently higher foliar temperature than mock treated controls. Non-destructive time-course experiments revealed that this differential phenotype was stable during both daytime and nighttime. This effect was due to reduced gas exchange in TuMV-infected plants, as observed through stomatal conductance and stomatal aperture assays in systemic leaves. Measurements of daily water consumption and initial dehydration rate further proved that TuMV infection reduced water loss. Salicylic acid (SA) and abscisic acid (ABA) contents were increased in TuMV-infected plants. In addition, the expression of ABI2, involved in ABA signaling, was enhanced, and ABCG40 (required for ABA transport into guard cells) was highly induced upon TuMV infection. Hypermorficabi2-1mutant plants, but no other ABA or SA biosynthetic, signaling or degradation mutants tested abolished both stomatal closure and low stomatal conductance phenotypes caused by TuMV. Therefore, not overall ABA levels, but localized differences in ABA import and perception in guard cells, are likely to be responsible for stomatal closure observed under TuMV infection. Plants simultaneously subjected to drought and viral stresses showed higher mortality rates than their mock-inoculated drought stressed counterparts, consistent with down-regulation of drought-responsive gene RD29A, both in short and long day conditions. Our findings indicate that in spite of stomatal closure triggered by TuMV, additional phenomena cause compromised drought tolerance of TuMV-infected Arabidopsis plants.ii)Significance statementCharacterization of the physiological responses controlling plant water management under combined stresses and the genes behind them is important in the current climate change scenario, which poses multifaceted challenges to crops. We found that TuMV infection induced ABA and SA accumulation and stomatal closure in Arabidopsis, alongside with overexpression of ABCG40 (the transporter of ABA to guard cells), whereas the dehydration-responsive gene RD29A was downregulated, concomitantly with increased plant susceptibility to drought stress under infection.
Not out of the box: phylogeny of the broadly sampled Buxaceae
Authors: Shipunov Alexey , Lee Hye Ji , Choi Jinhee , Pay Kyle , DeSpiegelaire Sarah , Floden Aaron 
Published: August 2020

AbstractThe Buxaceae constitute a morphologically diverse phylogenetic lineage of six genera, which includes about 140 species. The most well-known genera areBuxus,Sarcococca, andPachysandra.Few species of woodyStylocerasgrow on mid-elevations in the Andes mountains region.Didymeles, with three species endemic to Madagascar, and the monotypicHaptanthusfrom Honduras, are the most unusual members of the group. The infra-familial classification of Buxaceae is controversial, and molecular data about many species, especially Old World, is still lacking. We used broad taxonomic sampling and molecular data from four chloroplast markers, and the nuclear ribosomal ITS to estimate their phylogeny. These data provide phylogenetic placements of 50 species and enabled better estimates of boundaries in Buxaceae. We described two subfamilies, two monotypic genera, twoBuxussubgenera, and one new species ofDidymelesfrom Madagascar.
Human Cytomegalovirus Drives WDR5 to the Virion Assembly Compartment to Facilitate Virion Assembly
Authors: Yang Bo , Yao YongXuan , Wu Hui , Yang Hong , Ma Xue-Hui , Li Dong , Wang Xian-Zhang , Huang Sheng-Nan , Jiang Xuan , Cheng Shuang , Sun Jin-Yan , Huang Zhen-Li , Zhao CongJian , McVoy Michael A. , Ahn Jin-Hyun , Zeng Wen-Bo , Gong Sitang , Britt William J. , Luo Min-Hua 
Published: August 2020

AbstractWe previously reported that human cytomegalovirus (HCMV) utilizes the cellular protein WDR5 to facilitate capsid nuclear egress. Here, we further show that HCMV infection drives WDR5 to the perinuclear region by a mechanism that requires viral replication and intact microtubules. WDR5 accumulated in the virion assembly compartment (vAC) and co-localized with vAC markers of gamma-tubulin (γ-tubulin), early endosomes, and viral vAC marker proteins pp65, pp28, and glycoprotein B (gB). WDR5 interacted with multiple virion proteins, including MCP, pp150, pp65, pIRS1, and pTRS1, which may explain the increasing WDR5 accumulation in the vAC during infection. WDR5 was then incorporated into HCMV virions and localized to the tegument layer, as demonstrated by fractionation and immune-gold electron microscopy. Thus, WDR5 is driven to the vAC and incorporated into virions, suggesting that WDR5 facilitates HCMV replication at later stage of virion assembly besides the capsid nuclear egress stage. These data highlight that WDR5 is a potential target for antiviral therapy.ImportanceHuman cytomegalovirus (HCMV) has a large (~235-kb) genome that contains over 170 ORFs and exploits numerous cellular factors to facilitate its replication. In the late phase of HCMV infection cytoplasmic membranes are profoundly reconfigured to establish the virion assembly compartment (vAC), which is important for efficient assembly of progeny virions. We previously reported that WDR5 promotes HCMV nuclear egress. Here, we show that WDR5 is further driven to the vAC and incorporated into virions, perhaps to facilitate efficient virion maturation. This work identified potential roles for WDR5 in HCMV replication in the cytoplasmic stages of virion assembly. Taken together, WDR5 plays a critical role in HCMV capsid nuclear egress and is important for virion assembly, and thus is a potential target for antiviral treatment of HCMV-associated diseases.
TClustVID: A Novel Machine Learning Classification Model to Investigate Topics and Sentiment in COVID-19 Tweets
Authors: Satu Md. Shahriare , Khan Md. Imran , Mahmud Mufti , Uddin Shahadat , Summers Matthew A. , Quinn Julian M.W. , Moni Mohammad Ali 
Published: August 2020

AbstractCOVID-19, caused by the SARS-Cov2, varies greatly in its severity but represent serious respiratory symptoms with vascular and other complications, particularly in older adults. The disease can be spread by both symptomatic and asymptomatic infected individuals, and remains uncertainty over key aspects of its infectivity, no effective remedy yet exists and this disease causes severe economic effects globally. For these reasons, COVID-19 is the subject of intense and widespread discussion on social media platforms including Facebook and Twitter. These public forums substantially impact on public opinions in some cases and exacerbate widespread panic and misinformation spread during the crisis. Thus, this work aimed to design an intelligent clustering-based classification and topics extracting model (named TClustVID) that analyze COVID-19-related public tweets to extract significant sentiments with high accuracy. We gathered COVID-19 Twitter datasets from the IEEE Dataport repository and employed a range of data preprocessing methods to clean the raw data, then applied tokenization and produced a word-to-index dictionary. Thereafter, different classifications were employed to Twitter datasets which enabled exploration of the performance of traditional and TclustVID classification methods. TClustVID showed higher performance compared to the traditional classifiers determined by clustering criteria. Finally, we extracted significant topic clusters from TClustVID, split them into positive, neutral and negative clusters and implemented latent dirichlet allocation for extraction of popular COVID-19 topics. This approach identified common prevailing public opinions and concerns related to COVID-19, as well as attitudes to infection prevention strategies held by people from different countries concerning the current pandemic situation.
Analysis of COVID-19 and comorbidity co-infection Model with Optimal Control
Authors: Omame A. , Sene N. , Nometa I. , Nwakanma C. I. , Nwafor E. U. , Iheonu N. O. , Okuonghae D. 
Published: August 2020

AbstractThe new coronavirus disease 2019 (COVID-19) infection is a double challenge for people infected with comorbidities such as cardiovascular and cerebrovascular diseases and diabetes. Comorbidities have been reported to be risk factors for the complications of COVID-19. In this work, we develop and analyze a mathematical model for the dynamics of COVID-19 infection in order to assess the impacts of prior comorbidity on COVID-19 complications and COVID-19 re-infection. The model is simulated using data relevant to the dynamics of the diseases in Lagos, Nigeria, making predictions for the attainment of peak periods in the presence or absence of comorbidity. The model is shown to undergo the phenomenon of backward bifurcation caused by the parameter accounting for increased susceptibility to COVID-19 infection by comorbid susceptibles as well as the rate of re-infection by those who have recovered from a previous COVID-19 infection. Sensivity analysis of the model when the population of individuals co-infected with COVID-19 and comorbidity is used as response function revealed that the top ranked parameters that drive the dynamics of the co-infection model are the effective contact rate for COVID-19 transmission, βCV, the parameter accounting for increased sucseptibility to COVID-19 by comorbid susceptibles, χCM, the comorbidity development rate, θCM, the detection rate for singly infected and co-infected individuals, η1 and η2, as well as the recovery rate from COVID-19 for co-infected individuals, φI2. Simulations of the model reveal that the cumulative confirmed cases (without comorbidity) may get up to 180,000 after 200 days, if the hyper susceptibility rate of comorbid susceptibles is as high as 1.2 per day. Also, the cumulative confirmed cases (including those co-infected with comorbidity) may be as high as 1000,000 cases by the end of November, 2020 if the re-infection rates for COVID-19 is 0.1 per day. It may be worse than this if the re-infection rates increase higher. Moreover, if policies are strictly put in place to step down the probability of COVID-19 infection by comorbid susceptibles to as low as 0.4 per day and step up the detection rate for singly infected individuals to 0.7 per day, then the reproduction number can be brought very low below one, and COVID-19 infection eliminated from the population. In addition, optimal control and cost-effectiveness analysis of the model reveal that the the strategy that prevents COVID-19 infection by comorbid susceptibles has the least ICER and is the most cost-effective of all the control strategies for the prevention of COVID-19.
Komenti: A semantic text mining framework
Authors: Slater Luke T , Bradlow William , Hoehndorf Robert , Motti Dino FA , Ball Simon , Gkoutos Georgios V 
Published: August 2020

AbstractSummaryKomenti is a reasoner-enabled semantic query and information extraction framework. It is the only text mining tool that enables querying inferred knowledge from biomedical ontologies. It also contains multiple novel components for vocabulary construction and context disambiguation, which can improve the power of text mining and ontology-based analysis tasks, with a view towards making full use of the semantic provision of biomedical ontologies for text characterisation and analysis. Here, we describe Komenti and its features, and present a use case wherein we automate a clinical audit, extracting medications for hypertrophic cardiomyopathy patients from text, revealing a high precision, and identifying a sub-cohort of patients with atrial fibrillation who are not anti-coagulated, and are therefore at a higher risk of stroke.Availability and ImplementationKomenti is freely available under an open source licence athttp://github.com/reality/komenti.More information concerning the use-case is available in supplementary data.
SARS-CoV-2 genome analysis of strains in Pakistan reveals GH, S and L clade strains at the start of the pandemic
Authors: Ghanchi Najia Karim , Masood Kiran Iqbal , Nasir Asghar , Khan Waqasuddin , Abidi Syed Hani , Shahid Saba , Mahmood Syed Faisal , Kanji Akbar , Razzak Safina , Ansar Zeeshan , Islam Nazneen , Dharejo M. B. , Hasan Zahra , Hasan Rumina 
Published: August 2020

AbstractObjectivesPakistan has a high infectious disease burden with about 265,000 reported cases of COVID-19. We investigated the genomic diversity of SARS-CoV-2 strains and present the first data on viruses circulating in the country.MethodsWe performed whole-genome sequencing and data analysis of SARS-CoV-2 eleven strains isolated in March and May.ResultsStrains from travelers clustered with those from China, Saudi Arabia, India, USA and Australia. Five of eight SARS-CoV-2 strains were GH clade with Spike glycoprotein D614G, Ns3 gene Q57H, and RNA dependent RNA polymerase (RdRp) P4715L mutations. Two were S (ORF8 L84S and N S202N) and three were L clade and one was an I clade strain. One GH and one L strain each displayed Orf1ab L3606F indicating further evolutionary transitions.ConclusionsThis data reveals SARS-CoV-2 strains of L, G, S and I have been circulating in Pakistan from March, at the start of the pandemic. It indicates viral diversity regarding infection in this populous region. Continuing molecular genomic surveillance of SARS-CoV-2 in the context of disease severity will be important to understand virus transmission patterns and host related determinants of COVID-19 in Pakistan.