bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamics of RNA polymerase II and elongation factor Spt4/5 recruitment during activator-dependent transcription
Authors: Rosen Grace A. , Baek Inwha , Friedman Larry J. , Joo Yoo Jin , Buratowski Stephen , Gelles Jeff 
Published: June 2020

AbstractIn eukaryotes, RNA polymerase II (RNApII) transcribes messenger RNA from template DNA. Decades of experiments have identified the proteins needed for transcription activation, initiation complex assembly, and productive elongation. However, the dynamics of recruitment of these proteins to transcription complexes, and of the transitions between these steps, are poorly understood. We used multi-wavelength single-molecule fluorescence microscopy to directly image and quantitate these dynamics in a budding yeast nuclear extract that reconstitutes activator-dependent transcription in vitro. A strong activator (Gal4-VP16) greatly stimulated reversible binding of individual RNApII molecules to template DNA, with no detectable involvement of RNApII-containing condensates. Binding of labeled elongation factor Spt4/5 to DNA typically followed RNApII binding, was NTP-dependent, and was correlated with association of mRNA-binding protein Hek2, demonstrating specificity of Spt4/5 binding to elongation complexes. Quantitative kinetic modeling shows that only a fraction of RNApII binding events are productive and implies a rate-limiting step, probably associated with recruitment of general transcription factors, needed to assemble a transcription-competent pre-initiation complex at the promoter. Spt4/5 association with transcription complexes was slowly reversible, with DNA-bound RNApII molecules sometimes binding and releasing Spt4/5 multiple times. The average Spt4/5 residence time was of similar magnitude to the time required to transcribe an average length yeast gene. These dynamics suggest that a single Spt4/5 molecule remains associated during a typical transcription event, yet can dissociate from RNApII to allow disassembly of abnormally long-lived (i.e., stalled) elongation complexes.Significance StatementThe synthesis of a eukaryotic messenger RNA molecule involves the association of RNA polymerase and dozens of accessory proteins on DNA. We used differently colored fluorescent dyes to tag DNA, RNA polymerase II, and the elongation factor Spt4/5 in yeast nuclear extract, and then observed the assembly and dynamics of individual molecules of the proteins with single DNA molecules by microscopy. The observations quantitatively define an overall pathway by which transcription complexes form and evolve in response to an activator protein. They suggest how molecular complex dynamics may be tuned to optimize efficient RNA production.
Optimizing model comparison for enzymatic mechanism analysis
Authors: Walsh Ryan , Blain Philippe 
Published: June 2020

ABSTRACTCharacterization of enzyme inhibition in drug development is usually limited to a basic analysis with the classical inhibition models or simply the use of IC50 values. However, a better understanding of enzyme physiology and regulation is seen as key to unraveling and treating the processes associated with stubborn disease targets like Alzheimer’s disease. Recently it has been shown that enzyme regulation, through substrate, inhibitor or activator interactions can be modeled using the summation of binding curves. Here we examine the use of the modular equation permutations, that can be produced through binding curve summation, to fit and evaluate the interactions of abietic acid with protein tyrosine phosphatase nonreceptor type 11. This new sort of analysis will allow for improved insight into the physiological role enzymes play and the consequence their modulation may have in disease progression.
Modeling the Covid-19 Epidemic Using Time Series Econometrics
Authors: Goliński Adam , Spencer Peter 
Published: June 2020

AbstractThe classic ‘logistic’ model has provided a realistic model of the behavior of Covid-19 in China and many East Asian countries. Once these countries passed the peak, the daily case count fell back, mirroring its initial climb in a symmetric way, just as the classic model predicts. However, in Italy and Spain, and now the UK and many other Western countries, the experience has been very different. The daily count has fallen back gradually from the peak but remained stubbornly high. The reason for the divergence from the classical model remain unclear. We take an empirical stance on this issue and develop a model that is based upon the statistical characteristics of the time series. With the possible exception of China, the workhorse logistic model is decisively rejected against more flexible alternatives.
Greater risk of severe COVID-19 in non-White ethnicities is not explained by cardiometabolic, socioeconomic, or behavioural factors, or by 25(OH)-vitamin D status: study of 1,326 cases from the UK Biobank
Authors: Raisi-Estabragh Zahra , McCracken Celeste , Bethell Mae S. , Cooper Jackie , Cooper Cyrus , Caulfield Mark J. , Munroe Patricia B. , Harvey Nicholas C. , Petersen Steffen E. 
Published: June 2020

AbstractBackgroundWe examined whether the greater severity of coronavirus disease 2019 (COVID-19) amongst men and non-White ethnicities is explained by cardiometabolic, socio-economic, or behavioural factors.MethodsWe studied 4,510 UK Biobank participants tested for COVID-19 (positive, n = 1,326). Multivariate logistic regression models including age, sex, and ethnicity were used to test whether addition of: 1)cardiometabolic factors (diabetes, hypertension, high cholesterol, prior myocardial infarction, smoking, BMI); 2)25(OH)-vitamin D; 3)poor diet; 4)Townsend deprivation score; 5)housing (home type, overcrowding); or 6)behavioural factors (sociability, risk taking) attenuated sex/ethnicity associations with COVID-19 status.ResultsThere was over-representation of men and non-White ethnicities in the COVID-19 positive group. Non-Whites had, on average, poorer cardiometabolic profile, lower 25(OH)-vitamin D, greater material deprivation, and were more likely to live in larger households and flats/apartments. Male sex, non-White ethnicity, higher BMI, Townsend deprivation score, and household overcrowding were independently associated with significantly greater odds of COVID-19. The pattern of association was consistent for men and women; cardiometabolic, socio-demographic and behavioural factors did not attenuate sex/ethnicity associations.ConclusionsSex and ethnicity differential pattern of COVID-19 is not adequately explained by variations in cardiometabolic factors, 25(OH)-vitamin D levels, or socio-economic factors. Investigation of alternative biological pathways and different genetic susceptibilities is warranted.
Effects of adiposity on the human plasma proteome: Observational and Mendelian randomization estimates
Authors: Goudswaard Lucy J. , Bell Joshua A. , Hughes David A. , Corbin Laura J. , Walter Klaudia , Smith George Davey , Soranzo Nicole , Danesh John , Di Angelantonio Emanuele , Ouwehand Willem H. , Watkins Nicholas A. , Roberts David J. , Butterworth Adam S. , Hers Ingeborg , Timpson Nicholas J. 
Published: June 2020

AbstractVariation in adiposity is associated with cardiometabolic disease outcomes, but the mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of adiposity, proxied by body mass index (BMI), on 3,622 unique plasma proteins measured by the SomaLogic platform in 2,737 healthy participants from the INTERVAL study of UK blood donors. We conducted both observational and Mendelian randomization analyses where we used a genetic risk score for BMI as an instrument to estimate effects of BMI on protein levels. Our results suggest that BMI has a broad impact on the human plasma proteome, with estimated effects of BMI appearing strongest on proteins including circulating leptin, sex hormone-binding globulin and fatty acid-binding protein-4. We also provide evidence that proteins most altered by BMI are enriched for genes involved in cardiovascular disease. Altogether, these results help to focus attention onto new potential proteomic signatures of obesity-related disease.
Willingness to Accept Tradeoffs among Covid-19 Cases, Social-Distancing Restrictions, and Economic Impact: A Nationwide US Study
Authors: Reed Shelby , Gonzalez Juan Marcos , Johnson F. Reed 
Published: June 2020

AbstractWe designed a discrete-choice experiment to quantify the extent to which US adults would accept greater risk of infection with SARS-CoV-2 in return for lifting social-distancing restrictions and diminishing the economic impact of the COVID-19 pandemic. 5953 adults representing all 50 states had 4 distinctly different preference patterns. About 37% were risk minimizers reluctant to accept any increases in risk of contracting the virus. Another group (26%) was primarily concerned about time required for economic recovery, accepting increases in COVID-19 risk levels up to 16% to shorten recovery from 3 to 2 years. The remaining two groups diverged on the relative importance of reopening nonessential businesses. The larger group (26%) strongly preferred delaying reopening while the smaller group (13%) would accept COVID-19 risks well beyond 20% to avoid a delay in reopening. Political affiliation, race, household income and employment status were predictive of group membership.
Diagnosis of Metabolic Syndrome using Machine Learning, Statistical and Risk Quantification Techniques: A Systematic Literature Review
Authors: Kakudi Habeebah Adamu , Loo Chu Kiong , Moy Foong Ming 
Published: June 2020

AbstractMetabolic syndrome (MetS), known to substantially lower the quality of life is associated with the increased incidence of non-communicable diseases (NCDs) such as type II diabetes mellitus, cardiovascular diseases and cancer. Evidence suggests that MetS accounts for the highest global mortality rate. For the early and accurate diagnosis of MetS, various statistical and ML techniques have been developed to support its clinical diagnosis. We performed a systematic review to investigate the various statistical and machine learning techniques (ML) that have been used to support the clinical diagnoses of MetS from the earliest studies to January 2020. Published literature relating to statistical and ML techniques for the diagnosis of MetS were identified by searching five major scientific databases: PubMed, Science Direct, IEEE Xplore, ACM digital library, and SpringerLink. Fifty-three primary studies that met the inclusion criteria were obtained after screening titles, abstracts and full text. Three main types of techniques were identified: statistical (n = 10), ML (n = 40), and risk quantification (n = 3). Standardized Z-score is the only statistical technique identified while the ML techniques include principal component analysis, confirmatory factory analysis, artificial neural networks, multiple logistics regression, decision trees, support vector machines, random forests, and Bayesian networks. The areal similarity degree risk quantification, framingham risk score and simScore were the three risk quantification techniques identified. Evidence suggests that evaluated ML techniques, with accuracy ranging from 75.5% to 98.9%, can more accurately diagnose MetS than both statistical and risk quantification techniques. The standardised Z-score is the most frequent statistical technique identified. However, highlighted proof based on performance measures indicate that the decision tree and artificial neural network ML techniques have the highest predictive performance for the prediction of MetS. Evidence suggests that more accurate diagnosis of MetS is required to evaluate the predictive performance of the statistical and ML techniques.
Predictors to use mobile apps for monitoring COVID-19 symptoms and contact tracing: A survey among Dutch citizens
Authors: Jansen– Kosterink Stephanie , Hurmuz Marian , den Ouden Marjolein , van Velsen Lex 
Published: June 2020

AbstractIntroductioneHealth applications have been recognized as a valuable tool to reduce COVID-19’s effective reproduction number. In this paper, we report on an online survey among Dutch citizens with the goal to identify antecedents of acceptance of a mobile application for COVID-19 symptom recognition and monitoring, and a mobile application for contact tracing.MethodsNext to the demographics, the online survey contained questions focussing on perceived health, fear of COVID-19 and intention to use. We used snowball sampling via posts on social media and personal connections. To identify antecedents of acceptance of the two mobile applications we conducted multiple linear regression analyses.ResultsIn total, 238 Dutch adults completed the survey. Almost 60% of the responders were female and the average age was 45.6 years (SD±17.4). For the symptom app, the final model included the predictors age, attitude towards technology and fear of COVID-19. The model had an R2 of 0.141. The final model for the tracing app included the same predictors and had an R2 of 0.156. The main reason to use both mobile applications was to control the spread of the COVID-19 virus. Concerns about privacy was mentioned as the main reason not to use the mobile applications.DiscussionAge, attitude towards technology and fear of COVID-19 are important predictors of the acceptance of COVID-19 mobile applications for symptom recognition and monitoring and for contact tracing. These predictors should be taken into account during the development and implementation of these mobile applications to secure acceptance.
Monocyte class switch and hyperinflammation characterise severe COVID-19 in type 2 diabetes
Authors: Alzaid Fawaz , Julla Jean-Baptiste , Diedisheim Marc , Potier Charline , Potier Louis , Velho Gilberto , Gaborit Bénédicte , Manivet Philippe , Germain Stéphane , Vidal-Trecan Tiphaine , Roussel Ronan , Riveline Jean-Pierre , Dalmas Elise , Venteclef Nicolas , Gautier Jean-François 
Published: June 2020

AbstractBackgroundEarly in the COVID-19 pandemic type 2 diabetes (T2D) was marked as a risk factor of severe disease and mortality. Inflammation is central to the aetiology of both conditions where variations in immune responses have the potential to mitigate or aggravate disease course. Identifying at risk groups based on immuno-inflammatory signatures is valuable in directing personalised care and developing potential targets for precision therapy.MethodsThis study characterised immunophenotypic variation associated with COVID-19 severity in type 2 diabetes. Broad-spectrum immunophenotyping quantified 15 leukocyte populations in peripheral circulation from a cohort of 45 hospitalised COVID-19 patients with and without type 2 diabetes.ResultsMorphological anomalies in the monocyte pool, monocytopenia specific to quiescent monocytes, and a decreased frequency of cytotoxic lymphocytes were associated with severe COVID-19 in patients with type 2 diabetes requiring intensive care. An aggravated inflammatory gene expression profile, reminiscent of the type-1 interferon pathway, underlaid the immunophenotype associated with severe disease in T2D.ConclusionShifts in T-cell and monocyte dynamics underpin a maladaptive response to SARSCoV-2. These alterations may impact type-1 interferon signalling which is the likely source of the hyperinflammation that increases voracity of COVID-19. These findings allow the identification of type 2 diabetic patients at risk of severe disease as well as providing evidence that the type-1 interferon pathway may be an actionable therapeutic target for future studies.Trial registrationNCT02671864FundingFrench National Agency of Research (ANR); European Foundation for the study of diabetes (EFSD); European Research Council (ERC); Francophone Society for Diabetes (SFD)Brief summaryMaladapted monocyte responses including class switch, morphological anomalies and systemic hyperinflammation put patients with type 2 diabetes at higher risk of severe COVID-19GRAPHICAL ABSTRACT
Determinants of household income of micro-finance women participants: a quantile regression approach
Authors: Duasa Jarita , Zainal Nur Hidayah 
Published: June 2020

PurposeThe purpose of this study is to adopt quantile regression to investigate the impact of several factors on per capita income of participants of micro-financing scheme (Amanah Ikhtiar Malaysia [AIM]), who are mostly women at different point on the income distributions.Design/methodology/approachThis study uses data collected from a survey on respondents who are the participants of AIM program using convenience sampling in Perak and Kelantan.FindingsThe empirical results show that the value of asset, value of loan, household size, ratio of spending to income and dummy state are consistently giving similar impacts on per capita income of participants at different quantiles.Originality/valueHowever, age negatively and significantly affects per capita income only at middle and lower quantiles but not at higher quantile of per capita income.
Grey portfolio analysis method
Authors: Nowak Marcin , Mierzwiak Rafał , Wojciechowski Hubert , Delcea Camelia 
Published: June 2020

PurposeThe article proposes a new method of strategic analysis. The method was called the grey portfolio analysis method. The presented method is complementary to the popular BCG matrix. The use of the grey portfolio analysis method enables to make a dynamic portfolio analysis for data with a high level of uncertainty.Design/methodology/approachFirst, the article presents current problems related to the application of portfolio methods in strategic management, in particular with reference to the BCG matrix. Second, the basics of grey numbers, operations with them and the way of acting in the grey portfolio analysis method are presented. Finally, the developed method is presented in a case study concerning an IT enterprise, whose portfolio includes cloud computing services.FindingsIn the article, a new method of a strategic analysis based on the BCG matrix was presented. It combines grey methodologies of decision making with a grey prognostic model in the context of a strategic analysis. Due to this fact, a dynamic approach to the issues of portfolio methods is possible.Practical implicationsThe article fits the current need related to the development of new expert systems supporting strategic management in enterprises.Originality/valueAn introduced method is new and innovative in the area of portfolio methods. Its originality results from the fact that it eliminates a static nature of the BCG matrix through the use of grey prognostic models. What is more, when grey numbers are used, a problem of uncertainty of information, which appears, is solved at a methodological level.
Understanding the gendered nature of developing country MSMEs’ access, adoption and use of information and communication technologies for development (ICT4D)
Authors: Mohanty Elisa , Mishra Anindya Jayanta 
Published: June 2020

Purpose
The widespread use of information and communication technologies (ICTs) has had a significant effect on various groups and communities of people including micro, small and medium enterprises (MSMEs) and their owners/managers. The current study aims to analyze recent literature regarding adoption of ICTs by MSMEs. Further, it tries to locate gender within this broader context of diffusion of ICTs among MSMEs.

Design/methodology/approach
Using the thematic analysis approach, the research articles pertaining to six leading journals on ICTs, gender and entrepreneurship published during the time period from 2011 to 2019 are reviewed.

Findings
The literature selected for the study has been discussed under two primary categories, viz. “adoption of information and communication technologies for development (ICT4D) for business purposes” and “insights on gender in ICT4D use by MSMEs.”

Research limitations/implications
The context-dependent nature of ICT use can enable future entrepreneurs to assess the scope of specific ICTs in given areas of operation. The gendered nature of ICTs helps to evaluate as well as question the empowerment potential of ICTs. The study emphasizes the need to account for historical specificities and transnational linkages in understanding access, adoption and use of ICT4D by women MSME entrepreneurs.

Originality/value
The study bridges together literature on ICT4D use by MSMEs and the role of gender in ICT-mediated entrepreneurial environments. While unraveling the interplay of power dynamics in such environments, the scope for future research in terms of tapping into the content of information exchanges and exploring the implications of “dark side of internet” for women MSME entrepreneurs is also indicated.
Investigating the role of disaggregated economic freedom measures and FDI on human development in Africa
Authors: Korle Kofi , Amoah Anthony , Hughes George , Pomeyie Paragon , Ahiabor Godson 
Published: June 2020

PurposeThe purpose of the study is to investigate the role of disaggregated economic freedom measures in the foreign direct investment (FDI) and human development nexus.Design/methodology/approachThe study uses a panel data of 32 selected African countries from 1996 to 2017. A dynamic ordinary least squares (DOLS) with fixed effects and instrumental variable (IV) econometric techniques was used to address issues of endogeneity and serial correlation commonly associated with panel time series data.FindingsThe Results indicate that FDI without accounting for absorptive factors has a positive but insignificant effect on human development for the selected African countries. However, FDI has a positive and significant effect on human development when interacted with measures of economic freedom such as investment freedom, business freedom and financial freedom. In contrast, yet plausible, FDI has a negative influence when interacted with property rights, trade freedom, government integrity and tax burden.Practical implicationsThe study posits that to attract FDI into Africa with the purpose of improving human development, relevant absorptive capacities such as business, investment and financial freedom environment are critical. However, excessive capital flight and government interference through taxation and abuse of property rights should be controlled if the continent seeks to promote human development through FDI.Originality/valueThe novelty and originality of the study, are evident in the use of disaggregated measures of economic freedom as comprehensive absorptive capacities to examine how they complement FDI to impact on human development in Africa.