bluuebunny/crossref_metadata_2025_split huggingface dataset:
COVID-19 in Portugal: predictability of hospitalization, ICU and respiratory-assistance needs
Authors: Patricio Andre , Costa Rafael S. , Henriques Rui 
Published: September 2020

AbstractThe current SARS-COV-2 epidemic is associated with nearly 1 million estimated deaths and responsible for multiple disturbances around the world, including the overload of health care systems. The timely prediction of the medical needs of infected individuals enables a better and quicker care provision for the necessary cases, supporting the management of available resources.This work ascertains the predictability of medical needs (as hospitalization, respiratory support, and admission to intensive care units) and the survivability of individuals testing SARS-CoV-2 positive considering a cohort with all infected individuals in Portugal as per June 30, 2020. Predictions are performed at the various stages of a patient’s cycle, namely: pre-hospitalization (testing time), pos-hospitalization, and pos-intensive care. A thorough optimization of state-of-the-art predictors is undertaken to assess the ability to anticipate medical needs and infection outcomes using demographic and comorbidity variables, as well as onset date of symptoms, test and hospitalization.
Causal Analysis of Health Interventions and Environments for Influencing the Spread of COVID-19 in the United States of America
Authors: Li Zhouxuan , Xu Tao , Zhang Kai , Deng Hong-Wen , Boerwinkle Eric , Xiong Momiao 
Published: September 2020

AbstractAs of August 27, 2020, the number of cumulative cases of COVID-19 in the US exceeded 5,863,363 and included 180,595 deaths, thus causing a serious public health crisis. Curbing the spread of Covid-19 is still urgently needed. Given the lack of potential vaccines and effective medications, non-pharmaceutical interventions are the major option to curtail the spread of COVID-19. An accurate estimate of the potential impact of different non-pharmaceutical measures on containing, and identify risk factors influencing the spread of COVID-19 is crucial for planning the most effective interventions to curb the spread of COVID-19 and to reduce the deaths. Additive model-based bivariate causal discovery for scalar factors and multivariate Granger causality tests for time series factors are applied to the surveillance data of lab-confirmed Covid-19 cases in the US, University of Maryland Data (UMD) data, and Google mobility data from March 5, 2020 to August 25, 2020 in order to evaluate the contributions of social-biological factors, economics, the Google mobility indexes, and the rate of the virus test to the number of the new cases and number of deaths from COVID-19. We found that active cases/1000 people, workplaces, tests done/1000 people, imported COVID-19 cases, unemployment rate and unemployment claims/1000 people, mobility trends for places of residence (residential), retail and test capacity were the most significant risk factor for the new cases of COVID-19 in 23, 7, 6, 5, 4, 2, 1 and 1 states, respectively, and that active cases/1000 people, workplaces, residential, unemployment rate, imported COVID cases, unemployment claims/1000 people, transit stations, mobility trends (transit), tests done/1000 people, grocery, testing capacity, retail, percentage of change in consumption, percentage of working from home were the most significant risk factor for the deaths of COVID-19 in 17, 10, 4, 4, 3, 2, 2, 2, 1, 1, 1, 1 states, respectively. We observed that no metrics showed significant evidence in mitigating the COVID-19 epidemic in FL and only a few metrics showed evidence in reducing the number of new cases of COVID-19 in AZ, NY and TX. Our results showed that the majority of non-pharmaceutical interventions had a large effect on slowing the transmission and reducing deaths, and that health interventions were still needed to contain COVID-19.
Probabilistic analysis of COVID-19 patients’ individual length of stay in Swiss intensive care units
Authors: Henzi Alexander , Kleger Gian-Reto , Hilty Matthias P. , Garcia Pedro D. Wendel , Ziegel Johanna F. 
Published: September 2020

AbstractRationaleThe COVID-19 pandemic induces considerable strain on intensive care unit resources.ObjectivesWe aim to provide early predictions of individual patients’ intensive care unit length of stay, which might improve resource allocation and patient care during the on-going pandemic.MethodsWe developed a new semiparametric distributional index model depending on covariates which are available within 24h after intensive care unit admission. The model was trained on a large cohort of acute respiratory distress syndrome patients out of the Minimal Dataset of the Swiss Society of Intensive Care Medicine. Then, we predict individual length of stay of patients in the RISC-19-ICU registry.MeasurementsThe RISC-19-ICU Investigators for Switzerland collected data of 557 critically ill patients with COVID-19.Main ResultsThe model gives probabilistically and marginally calibrated predictions which are more informative than the empirical length of stay distribution of the training data. However, marginal calibration was worse after approximately 20 days in the whole cohort and in different subgroups. Long staying COVID-19 patients have shorter length of stay than regular acute respiratory distress syndrome patients. We found differences in LoS with respect to age categories and gender but not in regions of Switzerland with different stress of intensive care unit resources.ConclusionA new probabilistic model permits calibrated and informative probabilistic prediction of LoS of individual patients with COVID-19. Long staying patients could be discovered early. The model may be the basis to simulate stochastic models for bed occupation in intensive care units under different casemix scenarios.
Changes to the sebum lipidome upon COVID-19 infection observed via non-invasive and rapid sampling from the skin
Authors: Spick Matt , Longman Katie , Frampas Cecile , Costa Catia , Walters Deborah Dunn , Stewart Alex , Wilde Mike , Greener Danni , Evetts George , Trivedi Drupad , Barran Perdita , Pitt Andy , Bailey Melanie 
Published: September 2020

ABSTRACTThe COVID-19 pandemic has led to an urgent and unprecedented demand for testing – both for diagnosis and prognosis. Here we explore the potential for using sebum, collected via swabbing of a patient’s skin, as a novel sampling matrix to fulfil these requirements. In this pilot study, sebum samples were collected from 67 hospitalised patients (30 PCR positive and 37 PCR negative). Lipidomics analysis was carried out using liquid chromatography mass spectrometry. Total fatty acid derivative levels were found to be depressed in COVID-19 positive participants, indicative of dyslipidemia. Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) modelling showed promising separation of COVID-19 positive and negative participants when comorbidities and medication were controlled for. Given that sebum sampling is rapid and non-invasive, this work may offer the potential for diagnostic and prognostic testing for COVID-19.
Waist-to-height ratio is a more accurate screening tool for hypertension than waist-to-hip circumference and BMI in type 2 diabetes: A prospective study
Authors: Moosaie Fatemeh , Fatemi Abhari Seyede Marzie , Deravi Niloofar , Behnagh Arman Karimi , Esteghamati Sadaf , Firouzabadi Fatemeh Dehghani , Rabizadeh Soghra , Nakhjavani Manouchehr , Esteghamati Alireza 
Published: September 2020

AbstractBackgroundTo date, anthropometric measures (i.e. body mass index (BMI), waist to hip ratio (WHR) and waist to height ratio (WHtR) have shown to be associated with prediction of incident hypertension. However, the difference in accuracy of these measures has been of controversy. We aimed to determine whether WHtR is a more accurate tool for HTN than WHR and BMI in patients with type 2 diabetes.Material and MethodsThe study population consisted of 1685 normotensive patients with T2DM. They were followed up for hypertension incidence for a mean of 4.8 years from April 2002 to January 2020. Cox regression was performed to assess the association between anthropometric measures (i.e., BMI, WHR, and WHtR) and incident hypertension during the follow-up period. Area under the ROC curve analysis was performed and optimal cutoff values were calculated using Youden index.ResultsWHtR and BMI were significantly associated with an increased risk of hypertension (HR=3.296(0.936-12.857), P < 0.001 and HR:1.050 (1.030-1.070), P < 0.001, respectively). The discriminative powers of each anthropometric index for HTN were 0.571 (0.540–0.602) for BMI, 0.518 (0.486–0.550) for WHR, and 0.609 (0.578–0.639) for WHtR. The optimal cutoff points for predicting HTN in patients with T2DM were 26.94 (sensitivity=0.739, specificity=0.380) for BMI, 0.90 (sensitivity=0.718, specificity=0.279) for WHR and 0.59 (sensitivity=0.676, specificity=0.517) for WHtR.ConclusionIn the current study WHtR was a more accurate screening tool for HTN compared to WHR and BMI in patients with type 2 diabetes.
The UK Biobank submaximal cycle ergometer test for assessment of cardiorespiratory fitness: Validity, reliability, and association with disease outcomes
Authors: Gonzales Tomas I. , Westgate Kate , Strain Tessa , Hollidge Stefanie , Jeon Justin , Christensen Dirk L. , Jensen Jorgen , Wareham Nicholas J. , Brage Søren 
Published: September 2020

AbstractBackgroundCardiorespiratory fitness (CRF) was assessed in UK Biobank (UKB) using heart rate response to a submaximal ramped cycle ergometer test that was individualised for participant characteristics including cardiovascular disease risk. Studies have since explored health associations with CRF by estimating maximal oxygen consumption (VO2max) from UKB test data using interpretation methods that have not accounted for this individualisation procedure. Thus, dose-response relationships reported in these studies may be inaccurate. We developed and validated a novel VO2max estimation approach that accounts for the UKB test individualisation procedure and compared dose-response relationships with health outcomes between the novel and previous methods.MethodsIn a cross-over study (n=189), participants completed several UKB tests and VO2max was measured. A multilevel modelling framework was developed that combines heart rate response features from the UKB test to estimate VO2max. Estimates were compared within participants across UKB test protocols, and with directly measured VO2max. Short-term test-retest reliability was assessed in a subsample of participants (n=87). In UKB, we examined associations between estimated CRF and disease endpoints (n=80,259) and compared associations obtained with an unvalidated method. Long-term test-retest reliability was examined (n = 2877).ResultsEstimated and directly measured VO2max were strongly correlated (Pearson’srrange: 0.68 to 0.74) with no mean bias (women bias: −0.8 to 0.4; men bias range: −0.3 to 0.3), outperforming a previous approach for interpreting UKB test data. Agreement between estimated VO2max across different test protocols was strong (Pearson’srrange: 0.94 to 0.99). Short- and long-term reliability was also high (lambda=0.91 and 0.80, respectively). All-cause mortality was 7% (95%CI 4-10%, 2686 deaths) lower and CVD mortality 9% (95%CI 3-14%, 858 deaths) lower for every 1-MET difference in fitness, associations twice as strong as determined by previous methods.ConclusionsWe present a valid and reliable method for estimating CRF in UKB and demonstrate its utility in characterising dose-response relationships with health outcomes. Accounting for the individualisation procedure strengthens observed relationships between CRF and disease and enhances the case for promoting improved fitness in the general population.
Systematic review and meta-analysis of randomized trials of hydroxychloroquine for the prevention of COVID-19
Authors: García-Albéniz Xabier , Amo Julia del , Polo Rosa , Morales-Asencio José Miguel , Hernán Miguel A 
Published: September 2020

AbstractBackgroundRecruitment into randomized trials of hydroxychloroquine (HCQ) for prevention of COVID-19 has been adversely affected by a widespread conviction that HCQ is not effective for prevention. In the absence of an updated systematic review, we conducted a meta-analysis of randomized trials that study the effectiveness of HCQ to prevent COVID-19.MethodsA search of PubMed and medRxiv with expert consultation found ten completed randomized trials: seven pre-exposure prophylaxis trials and three post-exposure prophylaxis trials. We obtained or calculated the risk ratio of COVID-19 diagnosis for assignment to HCQ versus no HCQ (either placebo or usual care) for each trial, and then pooled the risk ratio estimates.ResultsThe pooled risk ratio estimate of the pre-exposure prophylaxis trials was 0.72 (95% CI: 0.58-0.91) when using either a fixed effect or a standard random effects approach, and 0.72 (95% CI: 0.52-1.00) when using a conservative modification of the Hartung-Knapp random effects approach. The corresponding estimates for the post-exposure prophylaxis trials were 0.91 (95% CI: 0.71-1.16) and 0.91 (95% CI: 0.54-1.55). All trials found a similar rate of serious adverse effects in the HCQ and no HCQ groups.DiscussionA benefit of HCQ as prophylaxis for COVID-19 cannot be ruled out based on the available evidence from randomized trials. However, the “not statistically significant” findings from early prophylaxis trials were widely interpreted as definite evidence of lack of effectiveness of HCQ. This interpretation disrupted the timely completion of the remaining trials and thus the generation of precise estimates for pandemic management before the development of vaccines.
Analysis of COVID-19 case numbers: adjustment for diagnostic misclassification on the example of German case reporting data
Authors: Günther Felix , Berger Ursula , Höhle Michael , Bender Andreas , Wildner Manfred , Heid Iris M. , Küchenhoff Helmut 
Published: September 2020

AbstractBackgroundReported COVID-19 case numbers are key to monitoring pandemic spread and decision-making on policy measures but require careful interpretation as they depend substantially on testing strategy. A high and targeted testing activity is essential for a successful Test-Trace-Isolate strategy. However, it also leads to increased numbers of false-positives and can foster a debate on the actual pandemic state, which can slow down action and acceptance of containment measures.AimWe evaluate the impact of misclassification in COVID-19 diagnostics on reported case numbers and estimated numbers of disease onsets (epidemic curve).MethodsWe developed a statistical adjustment of reported case numbers for erroneous diagnostic results that facilitates a misclassification-adjusted real-time estimation of the epidemic curve based on nowcasting. Under realistic misclassification scenarios, we provide adjusted case numbers for Germany and illustrate misclassification-adjusted nowcasting for Bavarian data.ResultsWe quantify the impact of diagnostic misclassification on time-series of reported case numbers, highlighting the relevance of a specificity smaller than one when test activity changes over time. Adjusting for misclassification, we find that the increase of cases starting in July might have been smaller than indicated by raw case counts, but cannot be fully explained by increasing numbers of false-positives due to increased testing. The effect of misclassification becomes negligible when true incidence is high.ConclusionsAdjusting case numbers for misclassification can improve this important measure on short-term dynamics of the pandemic and should be considered in data-based surveillance. Further limitations of case reporting data exist and have to be considered.
Self-reported work activities, mucus membrane symptoms, and respiratory health outcomes among an industrial hog operation worker cohort, North Carolina, USA
Authors: Coffman Vanessa R. , Hall Devon J. , Pisanic Nora , Love David C. , Nadimpalli Maya , McCormack Meredith , Diener-West Marie , Davis Meghan F. , Heaney Christopher D. 
Published: September 2020

ABSTRACTBackgroundRespiratory disease among industrial hog operation (IHO) workers is well documented; however, it remains unclear whether specific work activities are more harmful and if personal protective equipment (PPE), as used by workers, can reduce adverse health outcomes.ObjectivesTo assess the relationship between self-reported IHO work activities and PPE use with mucus membrane and respiratory health symptoms in an occupational cohort.MethodsIHO workers (n=103) completed baseline and up to eight bi-weekly (i.e., every two weeks) study visits. Workers reported typical (baseline) and transient (bi-weekly) work activities, PPE use, and physical health symptoms. Baseline and longitudinal associations between work activities and health outcomes were assessed using generalized logistic and fixed-effects logistic regression models, respectively.ResultsAt baseline, reports of ever versus never drawing pig blood, applying pesticides, and increasing years worked at any IHO were positively associated with reports of eye, nose, and/or throat irritation. Over time, transient exposures, including those associated with dustiness in barns, cleaning of barns, and pig contact were associated with increased odds of symptoms including sneezing, headache, and eye or nose irritation, particularly in the highest categories of exposure. When PPE was used, workers had decreased odds of symptoms interfering with sleep (odds ratio (OR): 0.1; 95% confidence interval (CI): 0.01, 0.8), sneezing (OR: 0.1; 95% CI: 0.01, 1.0), and eye or nose irritation (OR: 0.1; 95% CI: 0.02, 0.9). Similarly, when they washed their hands ≥8 times per shift (the median) versus less frequently, workers had decreased odds of any respiratory symptom (OR: 0.3; 95% CI: 0.1, 0.8).DiscussionIn this healthy volunteer IHO worker population, increasingly unfavorable work activities were associated with self-reported mucus membrane and respiratory health outcomes. Strong protective associations were seen between PPE use and handwashing and the odds of symptoms, warranting further investigation in intervention studies.
Discovery and engineering of small SlugCas9 with broad targeting range and high specificity and activity
Authors: Hu Ziying , Zhang Chengdong , Wang Shuai , Wei Jingjing , Li Miaomiao , Hou Linghui , Liu Hongmao , Liu Dong , Lan Feng , Lu Daru , Wang Hongyan , Li Jixi , Wang Yongming 
Published: September 2020

AbstractThe compact CRISPR/Cas9 system, which can be delivered by adeno-associated virus (AAV), is a promising platform for therapeutic applications. However, current compact Cas9 nucleases have limited activity, targeting scope and specificity. Here, we identified three compact SaCas9 orthologs,Staphylococcus lugdunensisCas9 (SlugCas9),Staphylococcus lutraeCas9 (SlutrCas9) andStaphylococcus haemolyticusCas9 (ShaCas9), for mammalian genome editing. Interestingly, SlugCas9 recognizes a simple NNGG PAM and displays comparable activity to SaCas9. We further generated a SlugCas9-SaCas9 chimeric nuclease, which has both high specificity and high activity. We lastly engineered SlugCas9 with mutations to generate a high fidelity variant that maintains high specificity without compromising on-target editing efficiency. Our study offers important minimal Cas9 tools that are ideal for both basic research and clinical applications.
De NovoDiscovery of High Affinity Peptide Binders for the SARS-CoV-2 Spike Protein
Authors: Pomplun Sebastian , Jbara Muhammad , Quartararo Anthony J. , Zhang Genwei , Brown Joseph S. , Lee Yen-Chun , Ye Xiyun , Hanna Stephanie , Pentelute Bradley L. 
Published: September 2020

AbstractThe β-coronavirus SARS-CoV-2 has caused a global pandemic. Affinity reagents targeting the SARS-CoV-2 spike protein, the most exposed surface structure of the virus, are of interest for the development of therapeutics and diagnostics. We used affinity selection-mass spectrometry for the rapid discovery of synthetic high affinity peptide binders for the receptor binding domain (RBD) of the SARS-CoV-2 spike protein. From library screening with 800 million synthetic peptides, we identified three sequences with nanomolar affinities (dissociation constantsKd= 80 to 970 nM) for RBD and selectivity over human serum proteins. Picomolar RBD concentrations in biological matrix could be detected using the biotinylated lead peptide in ELISA format. These peptides might associate with the SARS-CoV-2-spike-RBD at a site unrelated to ACE2 binding, making them potential orthogonal reagents for sandwich immunoassays. We envision our discovery as a robust starting point for the development of SARS-CoV-2 diagnostics or conjugates for virus directed delivery of therapeutics.Abstract Figure
Ash1 and Tup1 Dependent Repression of theSaccharomyces cerevisiae HOpromoter Requires Activator-Dependent Nucleosome Eviction
Authors: Parnell Emily J. , Parnell Timothy J. , Yan Chao , Bai Lu , Stillman David J. 
Published: September 2020

ABSTRACTTranscriptional regulation of theSaccharomyces cerevisiae HOgene is highly complex, requiring a balance of multiple activating and repressing factors to ensure that only a few transcripts are produced in mother cells within a narrow window of the cell cycle. Here, we show that the Ash1 repressor associates with two DNA sequences that are usually concealed within nucleosomes in theHOpromoter and recruits the Tup1 corepressor and the Rpd3 histone deacetylase, both of which are required for full repression in daughters. Genome-wide ChIP identified greater than 200 additional sites of co-localization of these factors, primarily within large, intergenic regions from which they could regulate adjacent genes. Most Ash1 binding sites are in nucleosome depleted regions (NDRs), while a small number overlap nucleosomes, similar toHO. We demonstrate that Ash1 binding to theHOpromoter does not occur in the absence of the Swi5 transcription factor, which recruits coactivators that evict nucleosomes, including the nucleosomes obscuring the Ash1 binding sites. In the absence of Swi5, artificial nucleosome depletion allowed Ash1 to bind, demonstrating that nucleosomes are inhibitory to Ash1 binding. The location of binding sites within nucleosomes may therefore be a mechanism for limiting repressive activity to periods of nucleosome eviction that are otherwise associated with activation of the promoter. Our results illustrate that activation and repression can be intricately connected, and events set in motion by an activator may also ensure the appropriate level of repression and reset the promoter for the next activation cycle.