bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting the Peak and COVID-19 trend in six high incidence countries: A study based on Modified SEIRD model
Authors: Bedi Punam , Dhiman Shivani , Gupta Neha , Jindal Vinita , Gole Pushkar 
Published: December 2020

AbstractThe novel Coronavirus (COVID-19) has claimed the lives of almost a million people across the globe and this trend continues to rise rapidly day by day. The fear of getting infected by Corona virus is affecting the people emotionally, psychologically and mentally. They are not able to work to their full capacity and are also worried about the well beings of their near and dear ones. The National governments have taken up several measures like lockdowns, closing of educational institutions, and work from home for employees of companies wherever feasible. Governments are also advising people to take precautions like not to go out if not necessary, use of mask and keep a distance of appx. 6 ft. if you need to go out as the virus spreads from human to human in close proximity. These measures have helped to limit the spread of this virus in the past few months. However, due to rapid increase in the daily confirmed cases, it is becoming tougher for the governments to provide facilities like testing kits, hospitalization facilities, oxygen cylinders etc. to the infected persons. Thus, there is an urgent need to accurately estimate the number of cases in coming future that can help governments in acquiring the required resources. Further, to handle the economic distress caused by this virus, long-term planning is equally important. Focusing on these two aspects, this paper proposes to use the Modified SEIRD (Susceptible-Exposed-Infected-Recovered-Deceased) model to predict the peak and spread trend of COVID-19 in six countries namely USA, India, Brazil, Russia, Peru and Colombia having the highest number of confirmed cases. As in COVID-19, even infected asymptomatic persons can spread the infection, the chosen model is well suited as exposed compartment of SEIRD model includes asymptomatic exposed individuals which are infectious. Epidemiological data till 9th September 2020 has been utilised to perform short-term predictions till 31st December 2020. Long-term predictions have been computed till 31st December 2023, to estimate the end of the virus in the above-mentioned six nations. Small values of MAPE (Mean Absolute Percentage Error) have been obtained for the models fitted to reported data for all the countries. Student t-test has been used for accepting the predictions of the Modified SEIRD model based on the reported data.
Transition from growth to decay of an epidemic due to lockdown
Authors: Khataee H. , Kibble J. , Scheuring I. , Czirok A. , Neufeld Z. 
Published: December 2020

AbstractWe study the transition of an epidemic from growth phase to decay of the active infections in a population when lockdown measures are introduced to reduce the probability of disease transmission. While in the case of uniform lockdown a simple compartmental model would indicate instantaneous transition to decay of the epidemic, this is not the case when partially isolated active clusters remain with the potential to create a series of small outbreaks. We model this using a connected set of stochastic susceptible-infected-removed/recovered (SIR) models representing the locked-down majority population (where the reproduction number is less than one) weakly coupled to a large set of small clusters where the infection may propagate. We find that the presence of such active clusters can lead to slower than expected decay of the epidemic and significantly delayed onset of the decay phase. We study the relative contributions of these changes to the additional total infections caused by the active clusters within the locked-down population. We also demonstrate that limiting the size of the inevitable active clusters can be efficient in reducing their impact on the overall size of the epidemic outbreak.Statement of SignificanceRestricting movement and interaction of individuals has been widely used in trying to limit the spread of COVID-19, however, there is limited understanding of the efficiency of these measures as it is difficult to predict how and when they lead to the decay of an epidemic. In this article, we develop a mathematical framework to investigate the transition to the decay phase of the epidemic taking into account that after lockdown a large number of active groups remain with the potential to produce localised outbreaks affecting the overall decay of infections in the population. Better understanding of the mechanism of transition to the decay of the epidemic can contribute to improving the implementation of public health control strategies.
Genome-wide analysis in 756,646 individuals provides first genetic evidence that ACE2 expression influences COVID-19 risk and yields genetic risk scores predictive of severe disease
Authors: Horowitz J. E. , Kosmicki J. A. , Damask A. , Sharma D. , Roberts G. H. L. , Justice A. E. , Banerjee N. , Coignet M. V. , Yadav A. , Leader J. B. , Marcketta A. , Park D. S. , Lanche R. , Maxwell E. , Knight S. C. , Bai X. , Guturu H. , Sun D. , Baltzell A. , Kury F. S. P. , Backman J. D. , Girshick A. R. , O’Dushlaine C. , McCurdy S. R. , Partha R. , Mansfield A. J. , Turissini D. A. , Li A. H. , Zhang M. , Mbatchou J. , Watanabe K. , Gurski L. , McCarthy S. E. , Kang H. M. , Dobbyn L. , Stahl E. , Verma A. , Sirugo G. ,   Regeneron Genetics Center, Ritchie M. D. , Jones M. , Balasubramanian S. , Siminovitch K. , Salerno W. J. , Shuldiner A. R. , Rader D. J. , Mirshahi T. , Locke A. E. , Marchini J. , Overton J. D. , Carey D. J. , Habegger L. , Cantor M. N. , Rand K. A. , Hong E. L. , Reid J. G. , Ball C. A. , Baras A. , Abecasis G. R. , Ferreira M. A. 
Published: December 2020

ABSTRACTSARS-CoV-2 enters host cells by binding angiotensin-converting enzyme 2 (ACE2). Through a genome-wide association study, we show that a rare variant (MAF = 0.3%, odds ratio 0.60, P=4.5x10-13) that down-regulates ACE2 expression reduces risk of COVID-19 disease, providing human genetics support for the hypothesis that ACE2 levels influence COVID-19 risk. Further, we show that common genetic variants define a risk score that predicts severe disease among COVID-19 cases.
Massively parallel transposon mutagenesis identifies temporally essential genes for biofilm formation inEscherichia coli
Authors: Holden Emma R , Yasir Muhammad , Turner A Keith , Wain John , Charles Ian G. , Webber Mark A 
Published: December 2020

AbstractBiofilms complete a life cycle where cells aggregate, grow and produce a structured community before dispersing to seed biofilms in new environments. Progression through this life cycle requires temporally controlled gene expression to maximise fitness at each stage. Previous studies have largely focused on the essential genome for the formation of a mature biofilm, but here we present an insight into the genes involved at different stages of biofilm formation. We used TraDIS-Xpress; a massively parallel transposon mutagenesis approach using transposon-located promoters to assay the impact of disruption or altered expression of all genes in the genome on biofilm formation. We determined temporal differences in the importance of genes inE. coligrowing as a biofilm on glass beads after 12, 24 and 48 hours. A selection of genes identified as important were then validated independently by assaying biofilm biomass, aggregation, curli production and adhesion ability of defined mutants. We identified 48 genes that affected biofilm fitness including genes with known roles and those not previously implicated in biofilm formation. Regulation of type 1 fimbriae and motility were important at all time points. Adhesion and motility were important for the early biofilm, whereas matrix production and purine biosynthesis were only important as the biofilm matured. We found strong temporal contributions to biofilm fitness for some genes including some where expression changed between being beneficial or detrimental depending on the stage at which they are expressed, includingdksAanddsbA. Novel genes implicated in biofilm formation includedzapEandtruAinvolved in cell division,maoPin DNA housekeeping andyigZandykgJof unknown function. This work provides new insights into the requirements for successful biofilm formation through the biofilm life cycle and demonstrates the importance of understanding expression and fitness through time.
Targeting Scavenger Receptor Type B-1 (SR-B1) and Cholesterol Inhibits Entry of SARS-CoV-2 Pseudovirus in Cell Culture
Authors: Henrich Stephen E. , McMahon Kaylin M. , Palacio Nicole , Bhalla Pankaj , Penaloza-MacMaster Pablo , Thaxton C. Shad 
Published: December 2020

AbstractThe novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in Wuhan, China in late 2019 and has now caused a global pandemic. The disease caused by SARS-CoV-2 is known as COVID-19. To date, few treatments for COVID-19 have proven effective, and the current standard of care is primarily supportive. As a result, novel therapeutic strategies are in high demand. Viral entry into target cells is frequently sensitive to cell membrane lipid composition and membrane organization. Evidence suggests that cell entry of SARS-CoV-2 is most efficient when the target cell plasma membrane is replete with cholesterol; and recent data implicate cholesterol flux through the high-affinity receptor for cholesterol-rich high-density lipoprotein (HDL), called scavenger receptor type B-1 (SR-B1), as critical for SARS-CoV-2 entry. Here, we demonstrate that a cholesterol-poor synthetic biologic high-density lipoprotein (HDL NP) targets SR-B1 and inhibits cell entry of a SARS-CoV-2 spike protein pseudovirus. Human cells expressing SR-B1 are susceptible to SARS-CoV-2 infection, and viral entry can be inhibited by 50-80% using HDL NPs in an SR-B1-dependent manner. These results indicate that HDL NP targeting of SR-B1 is a powerful potential therapy to combat COVID-19 and other viral diseases.
Frequency matters: Up- and Down-Regulation of Dopamine Tone Induces Similar Frequency Shifts in Cortico-Basal Ganglia Beta Oscillations
Authors: Iskhakova L. , Rappel P. , Fonar G. , Marmor O. , Paz R. , Israel Z. , Eitan R. , Bergman H. 
Published: December 2020

AbstractBeta oscillatory activity (13-30Hz) is pervasive within the cortico-basal ganglia (CBG) network. Studies in Parkinson’s disease (PD) patients and animal models suggested that beta-power increases with dopamine depletion. However, the exact relationship between oscillatory power, frequency and dopamine-tone remains unclear. We recorded neural activity in the CBG network of non-human-primates (NHP) while acutely up- and down-modulating dopamine levels. Further, we assessed changes in beta oscillations of PD patients following acute and chronic changes in dopamine-tone. Beta oscillation frequency was strongly coupled with dopamine-tone in both NHPs and human patients. In contrast, power, coherence between single-units and LFP, and spike-LFP phase-locking were not systematically regulated by dopamine levels. These results demonstrate via causal manipulations that frequency, rather than other properties, is the key property of pathological oscillations in the CBG networks. These insights can lead to improvements in understanding of CBG physiology, PD progression tracking and patient care.
PomX, a ParA/MinD ATPase activating protein, is a triple regulator of cell division inMyxococcus xanthus
Authors: Schumacher Dominik , Harms Andrea , Bergeler Silke , Frey Erwin , Søgaard-Andersen Lotte 
Published: December 2020

SummaryCell division is precisely regulated to generate daughter cells of correct size and shape. In the social bacteriumMyxococcus xanthus, the tripartite PomX/Y/Z complex directly stimulates positioning of the cytokinetic FtsZ-ring at midcell to mark the division site. The ∼15 MDa PomX/Y/Z complex associates with the nucleoid in a PomZ-dependent manner, translocates to midcell to stimulate FtsZ-ring formation, and undergoes fission during division. We demonstrate that PomX consists of two functionally distinct domains and has three functions. The N-terminal domain interacts with the ParA/MinD ATPase PomZ and stimulates PomZ ATPase activity. The C-terminal domain mediates PomX self-interaction, interaction to PomY, and serves as a scaffold for PomX/Y/Z complex formation. Moreover, the PomX/PomZ interaction is important for fission. These observations together with previous work support that the architecturally diverse ATPase activating proteins of ParA/MinD ATPases are highly modular and use the same mechanism to activate their cognate ATPase via a short positively charged N-terminal extension.
Multiple Temporal and Semantic Processes During Verbal Fluency Tasks in English-Russian Bilinguals
Authors: Lerner Alan J. , Crough Michelle , Lenio Steven , Woyczynski Wojbor , Lissemore Frances M. 
Published: December 2020

AbstractCategory fluency test (CFT) performance is sensitive to cognitive processes of executive control and memory storage and access, and widely used to measure cognitive performance especially in early Alzheimer’s Disease. Analytical variables have included the number of items named, and various methods to identify and quantify clusters of semantically related words and cluster switches. Also encoded in the response sequence are temporal patterns as shown by “bursts” of responses and pauses between items, that have not been received attention in determining cluster characteristics.We studied a group of 51 adult Russian-English bilinguals and compared CFT responses based on two clustering methodologies: the semantic-based method (SEM) and a novel method based on the time interval between words (TEMP) with 8 different intercall time thresholds from 0.25 sec-15 sec. Each participant performed the task in both languages. Total number of words and cluster count was greater in Russian than English for both scoring methods, but cluster size did not differ between languages. We also studied stochastic modeling characteristics based on detrending of the “exponential exhaustion” effect seen with CFT, with most notable that total recall capacity (N∞) was greater in Russian than English (P<.05). Multiple demographic variables, and recent and lifetime usage of each language, affected both cognitive performance as measured by the Montreal Cognitive Assessment (MOCA; given in English only). Differential performance is driven by differences in demographics, more words stored in memory, and semantic and timing recall strategies.
Pre-departure psychological distress and associated factors among migrant workers of Nepal
Authors: Poudel Om Prakash , Thapa Bijay , Bhandary Shital 
Published: December 2020

AbstractIntroductionForeign employment is the most significant motivation for international migration in Nepal. However, migrant workers are vulnerable to many exploitations that lead to psychological distress during the pre-departure phase and at the destination. The study aimed to identify the prevalence and associated factors for psychological distress among migrant workers during the pre-departure phase.MethodsThis was a cross-sectional study based on the representative sample of 445 migrant workers. A 21-item Depression Anxiety Stress Scale (DASS-21) and Pre-Departure Risk Factors Perception Scale (PD-RFPS) at the workplace were self-administered to migrant workers selected randomly attending the pre-departure orientation program. Bivariate and multivariate logistic regression was performed to identify the associated factors.ResultsPrevalence of psychological distress (Depression, Anxiety and Stress) was identified as 20.9% and female (AOR=2.02, p-value=0.041) and perception of bad working conditions (AOR=2.44, p-value=0.046) were found significantly associated with pre-departure psychological distress.ConclusionData suggests the presence of symptoms of psychological distress among migrant workers during the pre-departure phase and perception of risk factors at the workplace were found significantly associated with pre-departure psychological distress. Concern bodies should provide in-depth orientation on possible risk factors at the destination and coping skills for psychological distress during the pre-departure orientation program.
Dataset-specific thresholds significantly improve detection of low transcribed regulatory genes in polysome profiling experiments
Authors: Deyneko Igor V. , Mustafaev Orkhan N. , А. Tyurin Alexander , Zhukova Ksenya V. , Goldenkova-Pavlova Irina V. 
Published: December 2020

AbstractMotivationPolysome profiling is novel, and yet has proved to be an effective approach to detect mRNAs with differential ribosomal load and explore the regulatory mechanisms driving efficient translation. Genes encoding regulatory proteins, having a great influence of the organism, usually reveal moderate to low transcriptional levels, compared, for example, to genes of house-keeping machinery. This complicates the reliable detection of such genes in the presence of technical and/or biological noise.ResultsIn this work we investigate how cleaning of polysome profiling data onArabidopsis thalianainfluences the ability to detect genes with low level of total mRNA, but with a highly differential ribosomal load, i.e. genes translationally active. Suggested data modelling approach to identify a background level of mRNA counts individually for each dataset, shows higher power in detection of low transcribed genes, compared to the use of thresholds for the minimal required mRNA counts or the use of raw data. The significant increase in detected number of regulation–related genes was demonstrated. The described approach is applicable to a wide variety of RNA-seq data. All identified and classified mRNAs with high and low translation status are made available in supplementary material.
Proteomic characterization of pilot scale hot-water extracts from the industrial carrageenan red seaweedEucheuma denticulatum
Authors: Gregersen Simon , Pertseva Margarita , Marcatili Paolo , Holdt Susan Løvstad , Jacobsen Charlotte , García-Moreno Pedro J. , Hansen Egon Bech , Overgaard Michael Toft 
Published: December 2020

AbstractSeaweeds have a long history as a resource for polysaccharides/hydrocolloids extraction for use in the food industry due to their functionality as stabilizing agents. In addition to the carbohydrate content, seaweeds also contains a significant amount of protein, which may find application in food and feed. Here, we present a novel combination of transcriptomics, proteomics, and bioinformatics to determine the protein composition in two pilot-scale extracts fromEucheuma denticilatum(Spinosum) obtained via hot-water extraction. The extracts were characterized by qualitative and quantitative proteomics using LC-MS/MS and ade-novotranscriptome assembly for construction of a novel proteome. Using label-free, relative quantification, we were able to identify the most abundant proteins in the extracts and determined that the majority of quantified protein in the extracts (>75%) is constituted by merely three previously uncharacterized proteins. Putative subcellular localization for the quantified proteins was determined by bioinformatic prediction, and by correlating with the expected copy number from the transcriptome analysis, we determined that the extracts were highly enriched in extracellular proteins. This implies that the method predominantly extracts extracellular proteins, and thus appear ineffective for cellular disruption and subsequent release of intracellular proteins. Ultimately, this study highlight the power of quantitative proteomics as a novel tool for characterization of alternative protein sources intended for use in foods. Additionally, the study showcases the potential of proteomics for evaluation of protein extraction methods and as powerful tool in the development of an efficient extraction process.
Antibiotics modulate attractive interactions in bacterial colonies affecting survivability under combined treatment
Authors: Cronenberg Tom , Hennes Marc , Wielert Isabelle , Maier Berenike 
Published: December 2020

AbstractBiofilm formation protects bacteria from antibiotics. Very little is known about the response of biofilm-dwelling bacteria to antibiotics at the single cell level. Here, we developed a cell-tracking approach to investigate how antibiotics affect structure and dynamics of colonies formed by the human pathogenNeisseria gonorrhoeae. Antibiotics targeting different cellular functions enlarge the cell volumes and modulate within-colony motility. Focusing on azithromycin and ceftriaxone, we identify changes in type 4 pilus (T4P) mediated cell-to-cell attraction as the molecular mechanism for different effects on motility. By using strongly attractive mutant strains, we reveal that the survivability under ceftriaxone treatment depends on motility. Combining our results, we find that sequential treatment with azithromycin and ceftriaxone is synergistic. Taken together, we demonstrate that antibiotics modulate T4P-mediated attractions and hence cell motility and colony fluidity.Author SummaryAggregation into colonies and biofilms can enhance bacterial survivability under antibiotic treatment. Aggregation requires modulation of attractive forces between neighboring bacteria, yet the link between attraction and survivability is poorly characterized. Here, we quantify these attractive interactions and show that different antibiotics enhance or inhibit them. Live-cell tracking of single cells in spherical colonies enables us to correlate attractive interactions with single cell motility and colony fluidity. Even moderate changes in cell-to-cell attraction caused by antibiotics strongly impact on within-colony motility. Vice versa, we reveal that motility correlates with survivability under antibiotic treatment. In summary, we demonstrate a link between cellular attraction, colony fluidity, and survivability with the potential to optimize the treatment strategy of commonly used drug combinations.
Data-independent Acquisition-based Proteome and Phosphoproteome Profiling across Six Melanoma Cell Lines Reveals Determinants of Proteotypes
Authors: Gao Erli , Li Wenxue , Wu Chongde , Shao Wenguang , Di Yi , Liu Yansheng 
Published: December 2020

ABSTRACTHuman cancer cell lines are widely used in pharmacological and systems biological studies. The rapid documentation of the steady-state gene expression landscape of the cells used in a particular experiment may help to improve the reproducibility of scientific research. Here we applied a data-independent acquisition mass spectrometry (DIA-MS) method, coupled with a peptide spectral-library free data analysis workflow, to measure both proteome and phosphoproteome of a melanoma cell line panel with different metastatic properties. For each cell line, the single-shot DIA-MS detected 8,100 proteins and almost 40,000 phosphopeptides in the respective measurement of two hours. Benchmarking the DIA-MS data towards the RNA-seq data and tandem mass tag (TMT)-MS results from the same set of cell lines demonstrated comparable qualitative coverage and quantitative reproducibility. Our data confirmed the high but complex mRNA~protein and protein~phospsite correlations. The results successfully established DIA-MS as a strong and competitive proteotyping approach for cell lines. The data further showed that all subunits of Glycosylphosphatidylinositol (GPI)-anchor transamidase complex were overexpressed in metastatic melanoma cells and identified altered phosphoprotein modules such as BAF complex and mRNA splicing between metastatic and primary cells. This study provides a high-quality resource for calibrating DIA-MS performance, benchmarking DIA bioinformatic algorithms, and exploring the metastatic proteotypes in melanoma cells.