bluuebunny/crossref_metadata_2025 huggingface dataset:
Data model to predict prevalence of COVID-19 in Pakistan
Authors: Qasim Muhammad , Ahmad Waqas , Zhang Shenghuan , Yasir Muhammad , Azhar Muhammad
Published: April 2020

Coronavirus disease 2019 (COVID19) has spread to 181 countries and regions and leaving behind 1,133,788 confirmed cases and 62784 deaths worldwide. Countries with lower health services and facilities like Pakistan are on great risk. Pakistan so far has 3,277 confirmed cases and 50 reported deaths due to COVID19. Various mathematical models had presented to predict the global and regional size of pandemic. However, all those models have certain limitation due to their dependence on different variables and analyses are subject to potential bias. As each country has its own dimension therefore country specific model are required to develop accurate estimate. Here we present a data model to predict the size of COVID19 in Pakistan. In this mathematical data model, we used the time sequence mean weighting (TSMW) to estimate the expected future number of COVID19 cases in Pakistan until 29th April 2020. For future expected numbers of cases for long terms the data collection have to be maintained in real time.
A study of SARS-CoV-2 epidemiology in Italy: from early days to secondary effects after social distancing
Authors: Traini Marco Claudio , Caponi Carla , Ferrari Riccardo , De Socio Giuseppe Vittorio
Published: April 2020

Background

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to 101739 confirmed cases, in Italy, as of March 30th, 2020. While the analogous event in China appears to be under control at the moment, the outbreaks in western countries are still at an early stage of development. Italy, at present, is playing a major role in understanding the transmission dynamics of these new infections and evaluating the effectiveness of control measures in a western social context.

Methods

We combined a quarantined model with early-stage development data in Italy (during the period February 20th - March 30th) to predict longer-term progression (up to March 30th, and till June 25th, 2020 in a longterm view) with different control measures. Due to significant variations in the control strategies, which have been changing over time, and thanks to the introduction of detection technologies leading to faster confirmation of the SARS-CoV-2 infections, we made use of time-dependent contact and diagnosis rates to estimate when the effective daily reproduction ratio can fall below 1. Within the same framework, we analyze the possible secondary infection event after relaxing the isolation measures.

Outcomes and interpretation

We study two simplified scenarios compatible with the observation data and the effects of two stringent measures on the evolution of the epidemic. On one side, the contact rate must be kept as low as possible, but it is also clear that, in a modern developed country, it cannot fall under certain minimum levels and for a long time. The complementary parameter tuned is the transition rate of the symptomatic infected individuals to the quarantined class, a parameter δI connected with the time tI = 1/δI needed to perform diagnostic tests. Within the conditions of the outbreak in Italy, this time must fall under 12-8 hours in order to make the reproduction number less than 1 to minimize the case numbers. Moreover, we show how the same parameter plays an even more important role in mitigating the effects of a possible secondary infection event.

Funding

No funding has been provided by private or public actors beyond the current clinical practice (National Health Service).
COVID-19: Tracking the Pandemic with A Simple Curve Approximation Tool (SCAT)
Authors: Courtney Jane
Published: April 2020

In the current COVID-19 pandemic, much focus is put on ‘flattening the curve’. This epidemiological ‘curve’ refers to the cases versus time graph, which shows the rise of a disease to its peak before descending. The aim in a pandemic is to flatten this curve by reducing the peak and spreading out the timeline. However, the models used to predict this curve are often not clearly outlined, no model parameters are given, and models are not tested against real data. This lack of detail makes it difficult to recreate the curve. What is much needed is a simple tool for approximating the curve to allow ideas to be tested and comparisons made.

This work presents a Simple Curve Approximation Tool (SCAT) which can be used by anyone. This tool allows the user to approximate and draw the curve and allows testing of assumptions, trajectories and the wildly varying figures reported in the media. The mathematics behind SCAT is clearly outlined here but understanding of this is not required. SCAT is provided online as a downloadable MS Excel workbook with some sample cases shown. Throughout this work, the parameters used are specified so that all results can be easily reproduced.

Although not intended as a prediction tool, SCAT has achieved less than 0.5 % error in short-term forward prediction. It also shows a very significant improvement on the pandemic exponential approximations found throughout media reporting. As a comparison tool, it highlights obvious differences between COVID-19 and other diseases, such as influenza, and between countries at different stages of the pandemic (China, Italy and the UK are used here for demonstration purposes).

SCAT allows for quick approximation of the curve and creates meaningful comparisons and understandable visualisations for COVID-19 and other diseases.
Delivery of CPAP respiratory support for COVID-19 using repurposed technologies
Authors: Culmer P. , Keeling A. , Osnes C. , Birch W. Davis , Jones D. , Waters I. , Hetherington R. , Parmar J. , Lawton T. , Ashton S. , Latham M. , Murdoch S. , Brettle D. , Kapur N.
Published: April 2020

The COVID-19 pandemic has placed a dramatic increase in demand on healthcare providers to provide respiratory support for patients with moderate to severe symptoms. In conjunction, the pandemic has challenged existing supply-chains to meet demands for medical equipment and resources. In response to these challenges, we report our work to repurpose two existing non-invasive ventilation (NIV) systems to provide solutions for the delivery of oxygen-enriched CPAP ventilation which are inherently resource and oxygen-efficient. We consider adaptation of CPAP systems typically used for sleep apnoea, together with a new Venturi-valve design which can be readily produced through 3D printing. Our aim in both cases was to support Positive end-expiratory pressure (PEEP) of ≥10cmH2O while achieving ≥40% FiO2. This supports a crucial part in the patient pathway for COVID-19 treatment, helping to provide early respiratory support prior to invasive ventilation options in the ICU.
A virus that has gone viral: Amino acid mutation in S protein of Indian isolate of Coronavirus COVID-19 might impact receptor binding and thus infectivity
Authors: Saha Priyanka , Banerjee Arup Kumar , Tripathi Prem Prakash , Srivastava Amit Kumar , Ray Upasana
Published: April 2020

Since 2002, beta coronaviruses (CoV) have caused three zoonotic outbreaks, SARS-CoV in 2002, MERS-CoV in 2012, and the recent outbreak of SARS-CoV-2 late in 2019 (also named as COVID-19 or novel coronavirus 2019 or nCoV2019. Spike(S) protein, one of the structural proteins of this virus plays key role in receptor (ACE2) binding and thus virus entry. Thus, this protein has attracted scientists for detailed study and therapeutic targeting. As the 2019 novel coronavirus takes its course throughout the world, more and more sequence analyses are been done and genome sequences getting deposited in various databases. From India two clinical isolates have been sequenced and the full genome deposited in GenBank. We have performed sequence analyses of the spike protein of the Indian isolates and compared with that of the Wuhan, China (where the outbreak was first reported). While all the sequences of Wuhan isolates are identical, we found point mutations in the Indian isolates. Out of the two isolates one was found to harbour a mutation in its Receptor binding domain (RBD) at position 407. At this site arginine (a positively charged amino acid) was replaced by isoleucine (a hydrophobic amino acid that is also a C-beta branched amino acid). This mutation has been seen to change the secondary structure of the protein at that region and this can potentially alter receptor ding of the virus. Although this finding needs further validation and more sequencing, the information might be useful in rational drug designing and vaccine engineering.
Vulnerabilities of the SARS-CoV-2 virus to proteotoxicity – opportunity for repurposed chemotherapy of COVID-19 infection
Authors: Al-Motawa Maryam , Abbas Hafsa , Wijten Patrick , de la Fuente Alberto , Xue Mingzhan , Rabbani Naila , Thornalley Paul J.
Published: April 2020

The global pandemic of COVID-19 disease caused by infection with the SARS-CoV-2 coronavirus, has produced an urgent requirement and search for improved treatments whilst effective vaccines are developed. A strategy for improved drug therapy is to increase levels of endogenous reactive metabolites for selective toxicity to SARS-CoV-2 by preferential damage to the viral proteome. Key reactive metabolites producing major quantitative damage to the proteome in physiological systems are: reactive oxygen species (ROS) and the reactive glycating agent methylglyoxal (MG); cysteine residues and arginine residues are their most susceptible targets, respectively. From sequenced-based prediction of the SARS-CoV-2 proteome, we found 0.8-fold enrichment or depletion of cysteine residues in functional domains of the viral proteome; whereas there was a 4.6-fold enrichment of arginine residues, suggesting SARS-CoV-2 is resistant to oxidative agents and sensitive to MG. For arginine residues of the SARS-CoV-2 predicted to be in functional domains, we examined which are activated towards modification by MG – residues with predicted or expected low pKaby neighbouring group in interactions. We found 25 such arginine residues, including 2 in the spike protein and 10 in the nucleoprotein. These sites were partially conserved in relatedcoronaviridae: SARS-COV and MERS. Finally, we identified drugs which increase cellular MG concentration to virucidal levels: antitumor drugs with historical antiviral activity, doxorubicin and paclitaxel. Our findings provide evidence of potential vulnerability of SARS-CoV-2 to inactivation by MG and a scientific rationale for repurposing of doxorubicin and paclitaxel for treatment of COVID-19 disease, providing efficacy and adequate therapeutic index may be established.
Pat1 increases the range of decay factors and RNA bound by the Lsm1-7 complex
Authors: Lobel Joseph H. , Gross John D.
Published: April 2020

Pat1 promotes the activation and assembly of multiple proteins during mRNA decay. After deadenylation, the Pat1/Lsm1-7 complex binds to transcripts containing oligo(A) tails, which can be modified by the addition of several terminal uridine residues. Pat1 enhances Lsm1-7 binding to the 3’ end, but it is unknown how this interaction is influenced by nucleotide composition. Here we examine Pat1/Lsm1-7 binding to a series of oligoribonucleotides containing different A/U contents using recombinant purified proteins from fission yeast. We observe a positive correlation between fractional uridine content and Lsm1-7 binding affinity. Addition of Pat1 broadens RNA specificity of Lsm1-7 by enhancing binding to A-rich RNAs and increases cooperativity on all oligonucleotides tested. Consistent with increased cooperativity, Pat1 promotes multimerization of the Lsm1-7 complex, which is potentiated by RNA binding. Furthermore, the inherent ability of Pat1 to multimerize drives liquid-liquid phase separation with multivalent decapping enzyme complexes of Dcp1/Dcp2. Our results uncover how Pat1 regulates RNA binding and higher order assembly by mRNA decay factors.
Exploring the genomic and proteomic variations of SARS-CoV-2 spike glycoprotein: a computational biology approach
Authors: Lokman Syed Mohammad , Rasheduzzaman Md. , Salauddin Asma , Barua Rocktim , Tanzina Afsana Yeasmin , Rumi Meheadi Hasan , Hossain Md. Imran , Siddiki Amam Zonaed , Mannan Adnan , Hasan Md. Mahbub
Published: April 2020

The newly identified SARS-CoV-2 has now been reported from around 183 countries with more than a million confirmed human cases including more than 68000 deaths. The genomes of SARS-COV-2 strains isolated from different parts of the world are now available and the unique features of constituent genes and proteins have gotten substantial attention recently. Spike glycoprotein is widely considered as a possible target to be explored because of its role during the entry of coronaviruses into host cells. We analyzed 320 whole-genome sequences and 320 spike protein sequences of SARS-CoV-2 using multiple sequence alignment tools. In this study, 483 unique variations have been identified among the genomes including 25 non-synonymous mutations and one deletion in the spike protein of SARS-CoV-2. Among the 26 variations detected, 12 variations were located at the N-terminal domain and 6 variations at the receptor-binding domain (RBD) which might alter the interaction with receptor molecules. In addition, 22 amino acid insertions were identified in the spike protein of SARS-CoV-2 in comparison with that of SARS-CoV. Phylogenetic analyses of spike protein revealed that Bat coronavirus have a close evolutionary relationship with circulating SARS-CoV-2. The genetic variation analysis data presented in this study can help a better understanding of SARS-CoV-2 pathogenesis. Based on our findings, potential inhibitors can be designed and tested targeting these proposed sites of variation.
Early estimates of COVID-19 infections in small, medium and large population clusters
Authors: Siraj AS , Worku A , Berhane K , Berhane Y , Siraj DS
Published: April 2020

Since its emergence in December 2019, COVID-19 has rapidly developed into a pandemic with many countries declaring emergency conditions to contain its spread. The impact of the disease, while it has been relatively low in the Sub Saharan Africa (SSA) so far, is feared to be potentially devastating given the less developed and fragmented health care system in the continent. In addition, most emergency measures practiced may not be effective due to their limited affordability as well as the communal way people in SSA live in relative isolation in clusters of large as well as smaller population centers. To address the acute need for estimates of the potential impacts of the disease once it sweeps through the region, we developed a process-based model with key parameters obtained from recent studies, taking local context into consideration. We further used the model to estimate the number of infections within a year of sustained local transmissions under a total of 216 scenarios that cover different sizes of population, urban status, effectiveness and coverage of social distancing, contact tracing and usage of cloth facemask. We showed that when implemented early, 50% coverage of contact tracing and facemask, with 33% effective social distancing policies can “flattens the curve” of local epidemics and even bending it enough to result in fewer cumulative infections, bringing the pandemic to a manageable level for all population sizes we assessed. In SSA countries with limited healthcare workforce, hospital resources and ICU care, a robust system of social distancing, contact tracing and facemask use could yield in outcomes that prevent several millions of infections and thousands of deaths across the continent.

Funding

No funding source.
Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan
Authors: Chang Meng-Chun , Kahn Rebecca , Li Yu-An , Lee Cheng-Sheng , Buckee Caroline O. , Chang Hsiao-Han
Published: April 2020

Background

As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases.

Methods

In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan.

Results

We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact.

Conclusions

To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.
Polar Vantage and Oura physical activity and sleep trackers: A validation and comparison study
Authors: Henriksen André , Svartdal Frode , Grimsgaard Sameline , Hartvigsen Gunnar , Hopstock Laila
Published: April 2020

Background

Consumer-based activity trackers are increasingly used in research as they have potential to increase activity participation and can be used for estimating physical activity. However, the accuracy of newer consumer-based devices is mostly unknown, and validation studies are needed.

Objective

The objective of this study was to test the accuracy of the Polar Vantage watch and Oura ring activity trackers for measuring physical activity, total energy expenditure, resting heart rate, and sleep duration, in free-living adults.

Methods

Twenty-one participants wore two consumer-based activity trackers (Polar, Oura), an ActiGraph accelerometer, an Actiheart accelerometer and heart rate monitor, and completed a sleep diary for up to seven days. We assessed Polar and Oura validity and comparability for physical activity, total energy expenditure, resting heart rate (Oura), and sleep duration. We analysed repeated measures correlation, Bland-Altman plots, and mean absolute percentage error.

Results

Polar and Oura were both strongly correlated (p<0.001) with ActiGraph for steps (Polar r 0.75, 95% CI 0.54-0.92. Oura r 0.77, 95% CI 0.62-0.87), moderate-to-vigorous physical activity (Polar r 0.76, 95% CI 0.62-0.88. Oura r 0.70, 95% CI 0.49-0.82), and total energy expenditure (Polar r 0.69, 95% CI 0.48-0.88. Oura r 0.70, 95% CI 0.51-0.83) and strongly or very strongly correlated (p<0.001) with the sleep diary for sleep duration (Polar r 0.74, 95% CI 0.56-0.88. Oura r 0.82, 95% CI 0.68-0.91). Oura had a very strong correlation (p<0.001) with Actiheart for resting heart rate (r 0.9, 95% CI 0.85-0.96). However, all confidence interval ranges were wide and mean absolute percentage error was high for all variables, except Oura sleep duration (10%) and resting heart rate (3%) where Oura under-reported on average one beat per minute.

Conclusions

Oura can potentially be used as an alternative to Actiheart to measure resting heart rate. For sleep duration, Polar and Oura can potentially be used as a replacement for a manual sleep diary, depending on acceptable error. Neither Polar nor Oura can replace ActiGraph for measuring steps, moderate-to-vigorous physical activity, and total energy expenditure, but may be used as an additional source of physical activity in some settings.
A Very Flat Peak: Why Standard SEIR Models Miss the Plateau of COVID-19 Infections and How it Can be Corrected
Authors: Ansumali Santosh , Prakash Meher K.
Published: April 2020

Innumerable variants of the susceptible-exposed-infected-recovered (SEIR) model predicted the course of COVID-19 infections for different countries, along with the ‘peaks’ and the subsequent decline of infections. One thing these models could not have predicted prospectively in January or did not adapt to in the following months is that the peak is rather a ‘plateau’ for many countries. For example, USA and UK have been persisting at the same high peak of approximately 30,000 and 5,000 daily new infections respectively, for more than a month. Other countries had shorter plateaus of about 3 weeks (6,400 cases in Spain). We establish that this plateau is not an artifact, and the “persistence number” describing the decline needs an equally important attention as the “reproduction number”. The solution lies in including the specific epidemiological role of asymptomatics and pre-symptomatics in COVID-19 transmission, different from SARS and influenza. We identify the minimal changes that can be made to any SEIR model to capture this plateau while studying seasonal effects, mitigation strategies, or the second wave of infections etc.
Adjuvant corticosteroid therapy for critically ill patients with COVID-19
Authors: Lu Xiaofan , Chen Taige , Wang Yang , Wang Jun , Zhang Bing , Li Yongsheng , Yan Fangrong
Published: April 2020

Addition of adjuvant corticosteroid therapy to standard antiviral treatment of patients with coronavirus disease (COVID-19) is common in clinical practice. However, evidence is scarce regarding the efficacy of adjuvant corticosteroids in patients who are critically ill. We retrospectively evaluated the effects of adjuvant corticosteroid treatment on the outcome of 244 critically ill patients with COVID-19, using a risk stratification model that adjusts for potential differences between the steroid group (n=151) and the non-steroid group (n=93). We observed that adjuvant corticosteroid therapy was independent from 28-day mortality, either in multivariate logistic regression of the entire cohort after adjustment for major mortality-associated variables (age, SpO2/FiO2, and lymphocyte count) and individual propensity score (adjusted OR: 1.05; 95% CI: −1.92-2.01), or in propensity score-matched (1:1 without replacement) case-control analysis (62 patients in 31 pairs; log-rank test P=0.17). Additionally, subgroup analyses of 147 (60%) patients who had dyspnea and 87 (36%) patients who had ARDS revealed corticosteroid treatment was not associated with clinical outcome (both, P>0.3). However, increased corticosteroids dosage was significantly associated with elevated mortality risk after adjustment for administration duration (P=0.003); every ten-milligram increase in hydrocortisone-equivalent dosage was associated with additional 4% mortality risk (adjusted HR: 1.04, 95% CI: 1.01-1.07). Our findings indicated that limited effect of corticosteroid therapy could pose to overall survival and prudent dose within effective limits may be recommended for critically ill patients under certain circumstances.
Convalescent Plasma to Treat COVID-19: Chinese Strategy and Experiences
Authors: Pei Shiyao , Yuan Xi , Zhang Zhimin , Yao Run , Xie Yubin , Shen Minxue , Li Bijuan , Chen Xiang , Yin Mingzhu
Published: April 2020

The COVID-19 is currently spreading around the world, which has posed significant threats to global health and economy. Convalescent plasma is confirmed effective against the novel corona virus in preliminary studies. In this paper, we first described the therapeutic schedule, antibody detection method, indications, contraindications of the convalescent plasmas, and reported the operability of the treatment by case study.
EHRtemporalVariability: delineating temporal dataset shifts in electronic health records
Authors: Sáez Carlos , Gutiérrez-Sacristán Alba , Kohane Isaac , García-Gómez Juan M , Avillach Paul
Published: April 2020

Background

Temporal variability in healthcare processes or protocols is intrinsic to medicine. Such variability can potentially introduce dataset shifts, a data quality issue when reusing electronic health records (EHRs) for secondary purposes. Temporal dataset shifts can present as trends, abrupt or seasonal changes in the statistical distributions of data over time, being particularly complex to address in multi-modal and highly coded data. These changes, if not delineated, can harm population and data-driven research, such as machine learning. Given that biomedical research repositories are increasingly being populated with large historical data from EHRs, there is a need for specific software methods to help delineate temporal dataset shifts to ensure reliable data reuse.

Findings

EHRtemporalVariability is an Open Source R-package and Shiny-app designed to explore and identify temporal dataset shifts. EHRtemporalVariability estimates the statistical distributions of coded and numerical data over time, projects their temporal-evolution through non-parametric Information Geometric Temporal plots, and enables the exploration of changes in variables through Data Temporal Heatmaps. We demonstrate the capability of EHRtemporalVariability to delineate dataset shifts in three impact case studies, one of them available for reproducibility.

Conclusions

EHRtemporalVariability enables the exploration and identification of dataset shifts, contributing to broadly examine and repurpose large, longitudinal datasets. Our goal is to help ensure reliable data reuse to a wide range of biomedical data users. EHRtemporalVariability is suited to technical users programmatically using the R-package and to those users not familiar with programming using the Shiny user interface.

Availability

https://github.com/hms-dbmi/EHRtemporalVariability/ Reproducible vignette: https://cran.r-project.org/web/packages/EHRtemporalVariability/vignettes/EHRtemporalVariability.html On-line demo: http://ehrtemporalvariability.upv.es/
Use of a Single Ventilator to Support Multiple Patients: Modeling Tidal Volume Response to Heterogeneous Lung Mechanics
Authors: Kheyfets Vitaly O. , Lammers Steven , Wagner Jennifer , Bartels Karsten , Smith Bradford
Published: April 2020

The COVID-19 pandemic is creating ventilator shortages in many countries that is sparking a conversation about placing multiple people on a single ventilator. However, on March 26th the American College of Chest Physicians (CHEST), along with other leading medical organizations, released a joint statement warning clinicians that attempting this technique could lead to poor outcomes and high mortality. Nevertheless, several hospitals around the United States and abroad are turning to this technique out of desperation (e.g. New York), but little data exists to guide their approach. The overall objective of this study is to utilize a computational model of mechanically ventilated lungs to assess how patient-specific lung mechanics and ventilator settings impact lung tidal volume (Vt).

Methods

We developed a single compartment computational model of four patients connected to a shared ventilator and validated it against a similar experimental study. We used this model to evaluate how patient-specific lung compliance (C) and resistance (R) would impact Vt under 5 ventilator settings of pre-set PIP, PEEP, and I:E ratio (suggested by Farkas, J.D. MD as an approach by hospitals to manage multiple patients on a single ventilator).

Results

Our computational model predicts Vt within 10% of experimental measurements. Using this model to perform a parametric study, we provide proof-of-concept for an algorithm to better match patients in different hypothetical scenarios of a single ventilator shared by more than one patient.

Conclusions

Assigning patients to pre-set ventilators based on their lung mechanics could be used to overcome some of the legitimate concerns of placing multiple patients on a single ventilator. We emphasize that our results are currently based on a computational model that has not been validated against any pre-clinical/clinical data. Therefore, clinicians considering this approach should not look to our study as an exact estimate of predicted patient tidal volumes.
Stress-Induced Transient Cell Cycle Arrest Coordinates Metabolic Resource Allocation to Balance Adaptive Tradeoffs
Authors: Bonny Alain R. , Kochanowski Karl , Diether Maren , El-Samad Hana
Published: April 2020

The ability of a cell to mount a robust response to an environmental perturbation is paramount to its survival. While cells deploy a spectrum of specialized counter-measures to deal with stress, a near constant feature of these responses is a down regulation or arrest of the cell cycle. It has been widely assumed that this modulation of the cell cycle is instrumental in facilitating a timely response towards cellular adaptation. Here, we investigate the role of cell cycle arrest in the hyperosmotic shock response of the model organismS. cerevisiaeby deleting the osmoshock-stabilized cell cycle inhibitor Sic1, thus enabling concurrent stress response activation and cell cycle progression. Contrary to expectation, we found that removal of stress-induced cell cycle arrest accelerated the adaptive response to osmotic shock instead of delaying it. Using a combination of time-lapse microscopy, genetic perturbations and quantitative mass spectrometry, we discovered that unabated cell cycle progression during stress enables the liquidation of internal glycogen stores, which are then shunted into the osmotic shock response to fuel a faster adaptation. Therefore, osmo-adaptation in wild type cells is delayed because cell cycle arrest diminishes the ability of the cell to tap its glycogen stores. However, acceleration of osmo-adaptation in mutant cells that do not arrest comes at the cost of acute sensitivity to a subsequent osmo-stress. This indicates that despite the ostensible advantage faster adaptation poses, there is a trade-off between the short-term benefit of faster adaptation and the vulnerability it poses to subsequent insults. We suggest that cell cycle arrest acts as a carbon flux valve to regulate the amount of material that is devoted to osmotic shock, balancing short term adaptation with long-term robustness.
MTXPK.org: A clinical decision support tool evaluating high-dose methotrexate pharmacokinetics to inform post-infusion care and use of glucarpidase
Authors: Taylor Zachary L. , Mizuno Tomoyuki , Punt Nieko C. , Baskaran Balaji , Sainz Adriana Navarro , Shuman William , Felicelli Nicholas , Vinks Alexander A. , Heldrup Jesper , Ramsey Laura B.
Published: April 2020

Methotrexate (MTX), an anti-folate, is administered at high-doses to treat malignancies in children and adults. However, there is considerable interpatient variability in clearance of high-dose (HD) MTX. Patients with delayed clearance are at an increased risk for severe nephrotoxicity and life-threatening systemic MTX exposure. Glucarpidase is a rescue agent for severe MTX toxicity that reduces plasma MTX levels via hydrolysis of MTX into inactive metabolites, but is only indicated when MTX concentrations are > 2 standard deviations above the mean excretion curve specific for the given dose together with a significant creatinine increase (> 50%). Appropriate administration of glucarpidase is challenging due to the ambiguity in the labeled indication. A recent consensus guideline was published with an algorithm to provide clarity in when to administer glucarpidase, yet clinical interpretation of lab results that do not directly correspond to the algorithm prove to be a limitation of its use.

The goal of our study was to develop a clinical decision support tool to optimize the administration of glucarpidase for patients receiving HD MTX. Here, we describe the development of a novel three-compartment MTX population PK model using 31,672 MTX plasma concentrations from 772 pediatric patients receiving HD MTX for the treatment of acute lymphoblastic leukemia and its integration into the online clinical decision support tool, MTXPK.org. This web-based tool has the functionality to utilize individualized demographics, serum creatinine, and real-time drug concentrations to predict the elimination profile and facilitate model-informed administration of glucarpidase.
Introductions and early spread of SARS-CoV-2 in the New York City area
Authors: Gonzalez-Reiche Ana S. , Hernandez Matthew M. , Sullivan Mitchell , Ciferri Brianne , Alshammary Hala , Obla Ajay , Fabre Shelcie , Kleiner Giulio , Polanco Jose , Khan Zenab , Alburquerque Bremy , van de Guchte Adriana , Dutta Jayeeta , Francoeur Nancy , Melo Betsaida Salom , Oussenko Irina , Deikus Gintaras , Soto Juan , Sridhar Shwetha Hara , Wang Ying-Chih , Twyman Kathryn , Kasarskis Andrew , Altman Deena Rose , Smith Melissa , Sebra Robert , Aberg Judith , Krammer Florian , García-Sastre Adolfo , Luksza Marta , Patel Gopi , Paniz-Mondolfi Alberto , Gitman Melissa , Sordillo Emilia Mia , Simon Viviana , van Bakel Harm
Published: April 2020

New York City (NYC) has emerged as one of the epicenters of the current SARS-CoV2 pandemic. To identify the early events underlying the rapid spread of the virus in the NYC metropolitan area, we sequenced the virus causing COVID19 in patients seeking care at the Mount Sinai Health System. Phylogenetic analysis of 84 distinct SARS-CoV2 genomes indicates multiple, independent but isolated introductions mainly from Europe and other parts of the United States. Moreover, we find evidence for community transmission of SARS-CoV2 as suggested by clusters of related viruses found in patients living in different neighborhoods of the city.
BRAVE-NET: Fully Automated Arterial Brain Vessel Segmentation In Patients with Cerebrovascular Disease
Authors: Hilbert Adam , Madai Vince I. , Akay Ela M. , Aydin Orhun U. , Behland Jonas , Sobesky Jan , Galinovic Ivana , Khalil Ahmed A. , Taha Abdel A. , Wuerfel Jens , Dusek Petr , Niendorf Thoralf , Fiebach Jochen B. , Frey Dietmar , Livne Michelle
Published: April 2020

Introduction

Arterial brain vessel assessment is crucial for the diagnostic process in patients with cerebrovascular disease. Noninvasive neuroimaging techniques such as time-of-flight (TOF) magnetic resonance angiography (MRA) imaging are applied in the clinical routine to depict arteries. They are, however, only visually assessed. Fully automated vessel segmentation integrated into the clinical routine could facilitate the time-critical diagnosis of vessel abnormalities and might facilitate the identification of valuable biomarkers for cerebrovascular events. In the present work, we developed and validated a new deep learning model for vessel segmentation, coined BRAVE-NET, on a large aggregated dataset of patients with cerebrovascular diseases.

Methods

BRAVE-NET is a multiscale 3-D convolutional neural network (CNN) model developed on a dataset of 264 patients from 3 different studies enrolling patients with cerebrovascular diseases. A context path, dually capturing high- and low-resolution volumes, and deep supervision were implemented. The BRAVE-NET model was compared to a baseline Unet model and variants with only context paths and deep supervision, respectively. The models were developed and validated using high-quality manual labels as ground truth. Next to precision and recall, the performance was assessed quantitatively by Dice coefficient (DSC); average Hausdorff distance (AVD); 95- percentile Hausdorff distance (95HD) and via visual qualitative rating.

Results

The BRAVE-NET performance surpassed the other models for arterial brain vessel segmentation with a DSC = 0.931, AVD = 0.165 and 95HD = 29.153. The BRAVE-NET model was also the most resistant towards false labelings as revealed by the visual analysis. The performance improvement is primarily attributed to the integration of the multiscaling context path into the 3-D Unet and to a lesser extent to the deep supervision architectural component.

Discussion

We present a new state-of-the-art of arterial brain vessel segmentation tailored to cerebrovascular pathology. We provide an extensive experimental validation of the model using a large aggregated dataset encompassing a large variability of cerebrovascular disease. The framework provides the technological foundation for improving the clinical workflow and can serve as a biomarker extraction tool in cerebrovascular diseases.
Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA
Authors: Burstyn Igor , Goldstein Neal D. , Gustafson Paul
Published: April 2020

The aim of our work was to better understand misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves. We examined publically available time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, about the sensitivity and specificity of the PCR-based diagnostic test. Data originated from Alberta, Canada (available on 3/28/2020) and city of Philadelphia, USA (available on 3/31/2020). Our analysis revealed that the data were compatible with near-perfect specificity but it was challenging to gain information about sensitivity (prior and posterior largely overlapped). We applied these insights to uncertainty/bias analysis of epidemic curves into jurisdictions under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the observed and adjusted epidemic curves likely fall within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. In the extreme scenario, hundreds of undiagnosed cases, even among tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves, a task for which the Bayesian method we presented is well-suited.
Testing the association between blood type and COVID-19 infection, intubation, and death
Authors: Zietz Michael , Zucker Jason , Tatonetti Nicholas P.
Published: April 2020

The rapid global spread of the novel coronavirus SARS-CoV-2 has strained healthcare and testing resources, making the identification and prioritization of individuals most at-risk a critical challenge. Recent evidence suggests blood type may affect risk of severe COVID-19. We used observational healthcare data on 14,112 individuals tested for SARS-CoV-2 with known blood type in the New York Presbyterian (NYP) hospital system to assess the association between ABO and Rh blood types and infection, intubation, and death. We found slightly increased infection prevalence among non-O types. Risk of intubation was decreased among A and increased among AB and B types, compared with type O, while risk of death was increased for type AB and decreased for types A and B. We estimated Rh-negative blood type to have a protective effect for all three outcomes. Our results add to the growing body of evidence suggesting blood type may play a role in COVID-19.
Fast SARS-CoV-2 detection by RT-qPCR in preheated nasopharyngeal swab samples
Authors: Alcoba-Florez Julia , González-Montelongo Rafaela , Íñigo-Campos Antonio , García-Martínez de Artola Diego , Gil-Campesino Helena ,   The Microbiology Technical Support Team, Ciuffreda Laura , Valenzuela-Fernández Agustín , Flores Carlos
Published: April 2020

The current reference for COVID-19 diagnosis is based on the detection of SARS-CoV-2 on RNA extracts using one-step retrotranscription and quantitative PCR (RT-qPCR). Based on the urgent need for high-throughput COVID-19 screening, we tested the performance of three alternative, simple and affordable protocols to rapidly detect SARS-CoV-2, overcoming the long and tedious RNA extraction step. Although with an average increase of 6.1 (± 1.6) cycles compared to standard tests with RNA extracts, we show that RT-qPCR yielded consistent results in nasopharyngeal swab samples that were subject to a direct 70°C incubation for 10 min. Our findings provide viable options to overcome any supply chain issue and help to increase the throughput of diagnostic tests by using any qPCR device, thereby complementing standard COVID-19 testing.
Brief Analysis of the ARIMA model on the COVID-19 in Italy
Authors: Ding Guorong , Li Xinru , Jiao Fan , Shen Yang
Published: April 2020

Coronavirus disease 2019 (COVID-19) has been considered as a global threat infectious disease, and various mathematical models are being used to conduct multiple studies to analyze and predict the evolution of this epidemic. We statistically analyze the epidemic data from February 24 to March 30, 2020 in Italy, and proposes a simple time series analysis model based on the Auto Regressive Integrated Moving Average (ARIMA). The cumulative number of newly diagnosed and newly diagnosed patients in Italy is preprocessed and can be used to predict the spread of the Italian COVID-19 epidemic. The conclusion is that an inflection point is expected to occur in Italy in early April, and some reliable points are put forward for the inflection point of the epidemic: strengthen regional isolation and protection, do a good job of personal hygiene, and quickly treat the team leaders existing medical forces. It is hoped that the “City Closure” decree issued by the Italian government will go in the right direction, because this is the only way to curb the epidemic.
Temporal rise in the proportion of both younger adults and older adolescents among COVID-19 cases in Germany: evidence of lesser adherence to social distancing practices?
Authors: Goldstein Edward , Lipsitch Marc
Published: April 2020

Background

There is uncertainty about the role of different age groups in propagating the SARS-CoV-2 epidemics in different countries, particularly under current social distancing practices.

Methods

We used the Robert Koch Institute data on weekly COVID-19 cases in different age groups in Germany. To minimize the effect of changes in healthcare seeking behavior (e.g. for older adults) and testing practices, we included the following eight 5-year age groups in the analyses: 10-14y through 45-49y. For each age group g, we considered the proportion PL(g) of individuals in age group g among all detected cases aged 10-49y during weeks 13-14, 2020 (later period), as well as corresponding proportion PE(g) for weeks 10-11, 2020 (early period), and defined the relative risk RR(g) for the age group g to be the ratio RR (g) = PL(g)/PE(g). For each pair of age groups g1, g2, a higher value of RR(g1) compared to RR(g2), or, alternatively, a value above 1 for the odds ratio OR (g1, g2) = RR(g1)/RR(g2) for a COVID-19 case to be in group g1 vs. g2 for the later vs. early periods is interpreted as the relative increase in the population incidence of SARS-Cov-2 in the age group g1 compared to g2 for the later vs. early period.

Results

The relative risk RR(g) was highest for individuals aged 20-24y (RR=1.4(95% CI (1.27,1.55))), followed by individuals aged 15-19y (RR=1.14(0.99,1.32)), aged 30-34y (RR= 1.07(0.99,1.16)), aged 25-29y (RR= 1.06(0.98,1.15)), aged 35-39y (RR=0.95(0.87,1.03)), aged 40-44y (RR=0.9(0.83,0.98)), aged 45-49y (RR=0.83(0.77,0.89)) and aged 10-14y (RR=0.78(0.64,0.95)). For the age group 20-24y, the odds ratio relative to any other age group for a case to be during the later vs. early period was significantly above 1. For the age group 15-19y, the odds ratio relative to any other age group either above 35y or 10-14y for a case to be during the later vs. early period was significantly above 1.

Conclusions

The observed relative increase with time in the prevalence of individuals aged 15-34y (particularly those aged 20-24y) among detected COVID-19 cases in Germany is unlikely to be explained by increases in the likelihood of seeking medical care or the likelihood of being tested for individuals in those age groups compared to individuals aged 35-49y or 10-14y, and should be indicative of the actual increase in the prevalence of individuals aged 15-34y among SARS-CoV-2 infections in the German population. That increase likely reflects elevated mixing among individuals aged 15-34y (particularly those aged 20-24y) compared to other age groups, possibly due to lesser adherence to social distancing practices.
Distal-less genesDlx1/Dlx2repress oligodendrocyte genesis through transcriptional inhibition ofOlig2expression in the developing vertebrate forebrain
Authors: Jiang Qiang , Zagozewski Jamie , Godbout Roseline , Eisenstat David D.
Published: April 2020

In this study, we demonstrate that mouse DLX2 binds to theOlig2gene locus in mouse embryonic forebrainin vivo. We further confirm the specificity and the transcriptional repressive effect of the bindingin vitro. Furthermore, loss ofDlx1/2function leads to increasedOlig2expression in the ventral embryonic mouse forebrainin vivo. As well, we demonstrate that chicken DLX1 binds to one chicken Olig2 gene domainin vitro, and overexpression ofDlx1is sufficient to repressOlig2expression in the developing chicken forebrainin ovo. Chicken DLX1 with a mutation eliminating its DNA binding ability is unable to bind to theOlig2probein vitro, and abrogates its repressive function onOlig2expressionin ovo. Our results establish thatDlx1/2is both necessary and sufficient to repress oligodendrocyte specification mediated via direct transcriptional inhibition ofOlig2expression in the developing vertebrate forebrain.
DIVA: natural navigation inside 3D images using virtual reality
Authors: Beheiry Mohamed El , Godard Charlotte , Caporal Clément , Marcon Valentin , Ostertag Cécilia , Sliti Oumaima , Doutreligne Sébastien , Fournier Stéphane , Hajj Bassam , Dahan Maxime , Masson Jean-Baptiste
Published: April 2020

As three-dimensional microscopy becomes commonplace in biological re-search, there is an increasing need for researchers to be able to view experimental image stacks in a natural three-dimensional viewing context. Through stereoscopy and motion tracking, commercial virtual reality headsets provide a solution to this important visualization challenge by allowing researchers to view volumetric objects in an entirely intuitive fashion. With this motivation, we present DIVA, a user-friendly software tool that automatically creates detailed three-dimensional reconstructions of raw experimental image stacks that are integrated in virtual reality. In DIVA’s immersive virtual environment, users can view, manipulate and perform volumetric measurements on their microscopy images as they would to real physical objects. In contrast to similar solutions, our software provides high-quality volume rendering with native TIFF file compatibility. We benchmark the software with diverse image types including those generated by confocal, light-sheet and electron microscopy. DIVA is available athttps://diva.pasteur.frand will be regularly updated.