bluuebunny/crossref_metadata_2025 huggingface dataset:
TEG Max Clot Strength is Consistently Elevated and May Be Predictive of COVID-19 Status at the Time of ICU Admission
Authors: Lawicki Shaun , Wang Katherine , Han Bing , Love Gordon
Published: May 2020

Background

Hypercoagulability is becoming widely recognized as a major complication of COVID-19 infection as evidenced by high levels of fibrinogen degradation products and microthrombi identified within the lungs and kidneys of autopsy specimens from these patients. We report thromboelastography (TEG) testing on a cohort of patients with suspected COVID-19 infection at the time of admission to the intensive care unit.

Methods

TEG testing was performed using the TEG 6s analyzer near or at the time of ICU admission. We also report the results of other coagulation or inflammatory related indices such as platelet count, prothrombin time, fibrinogen, D-dimer, C-reactive protein, ferritin, and procalcitonin. All laboratory testing was performed at the discretion of the attending physician in the course of normal patient care and retrospectively reviewed.

Results

We found that maximum clot strength was consistently elevated in COVID-19 patients while normal in all patients found to be negative. We did not encounter significant prolongations of coagulation assays outside of those expectedly prolonged by heparin therapy nor was meeting the criteria for disseminated intravascular coagulation encountered.

Conclusions

We postulate that elevated maximum clot strength by TEG testing is predictive of COVID-19 status as within our cohort this perfectly predicted patients’ COVID-19 status despite a high level of suspicion in negative patients with normal TEG results. While these results require a larger cohort for confirmation, we feel that TEG testing could improve confidence in COVID-19 testing results in suspected patients possibly allowing for earlier de-escalation of infectious precautions and personal protective equipment utilization.
Monitoring social distancing and SARS-CoV-2 transmission in Brazil using cell phone mobility data
Authors: de Oliveira Silvano Barbosa , Pôrto Victor Bertollo Gomes , Ganem Fabiana , Mendes Fabio Macedo , Almiron Maria , de Oliveira Wanderson Kleber , Fantinato Francieli Fontana Sutile Tardetti , de Almeida Walquiria Aparecida Ferreira , de Macedo Borges Abel Pereira , Pinheiro Hector Natan Batista , Oliveira Raíza dos Santos , Andrews Jason R. , Faria Nuno R , Lopes Marcelo Barreto , de Araújo Wildo Navegantes , Diaz-Quijano Fredi A. , Nakaya Helder I. , Croda Julio
Published: May 2020

Social distancing measures have emerged as the predominant intervention for containing the spread of COVID-19, but evaluating adherence and effectiveness remains a challenge. We assessed the relationship between aggregated mobility data collected from mobile phone users and the time-dependent reproduction number R(t), using severe acute respiratory illness (SARI) cases reported by São Paulo and Rio de Janeiro. We found that the proportion of individuals staying home all day (isolation index) had a strong inverse correlation with R(t) (rho<-0.7) and was predictive of COVID-19 transmissibility (p<0.0001). Furthermore, indexs of 46.7% had the highest accuracy (93.9%) to predict R(t) below one. This metric can be monitored in real time to assess adherence to social distancing measures and predict their effectiveness for controlling SARS-CoV-2 transmission.

One Sentence Summary

Mobility data to monitoring social distancing in the COVID-19 outbreak
SARS-CoV-2 infection of the placenta
Authors: Hosier Hillary , Farhadian Shelli , Morotti Raffaella A. , Deshmukh Uma , Lu-Culligan Alice , Campbell Katherine H. , Yasumoto Yuki , Vogels Chantal B.F. , Casanovas-Massana Arnau , Vijayakumar Pavithra , Geng Bertie , Odio Camila D. , Fournier John , Brito Anderson F. , Fauver Joseph R. , Liu Feimei , Alpert Tara , Tal Reshef , Szigeti-Buck Klara , Perincheri Sudhir , Larsen Christopher , Gariepy Aileen M. , Aguilar Gabriela , Fardelmann Kristen L. , Harigopal Malini , Taylor Hugh S. , Pettker Christian M. , Wyllie Anne L. , Cruz Charles Dela , Ring Aaron M. , Grubaugh Nathan D. , Ko Albert I. , Horvath Tamas L. , Iwasaki Akiko , Reddy Uma M. , Lipkind Heather S.
Published: May 2020

Background

The effects of Covid-19 in pregnancy remain relatively unknown. We present a case of second trimester pregnancy with symptomatic Covid-19 complicated by severe preeclampsia and placental abruption.

Methods

We analyzed placenta for the presence of SARS-CoV-2 through molecular and immunohistochemical assays and by and electron microscopy, and we measured the maternal antibody response in blood to this infection.

Results

SARS-CoV-2 localized predominantly to syncytiotrophoblast cells at the maternal-fetal interface of the placenta. Histological examination of the placenta revealed a dense macrophage infiltrate, but no evidence for vasculopathy typically associated with preeclampsia.

Conclusion

This case demonstrates, for the first time, SARS-CoV-2 invasion of the placenta, highlighting the potential for severe morbidity among pregnant women with Covid-19.
Hindsight is 2020 vision: a characterisation of the global response to the COVID-19 pandemic
Authors: Warne David J. , Ebert Anthony , Drovandi Christopher , Hu Wenbiao , Mira Antonietta , Mengersen Kerrie
Published: May 2020

Background

The global impact of COVID-19 and the country-specific responses to the pandemic provide an unparalleled opportunity to learn about different patterns of the outbreak and interventions. We model the global pattern of trajectories of reported COVID-19 cases during the primary response period, with the aim of learning from the past to prepare for the future.

Methods

Using Bayesian methods, we analyse the response to the COVID-19 outbreak for 158 countries for the period 22 January to 9 June 2020. This encompasses the period in which many countries imposed a variety of response measures and initial relaxation strategies. Instead of modelling specific intervention types and timings for each country explicitly, we adopt a stochastic epidemiological model including a feedback mechanism on virus transmission to capture complex nonlinear dynamics arising from continuous changes in community behaviour in response to rising case numbers. We analyse the overall effect of interventions and community responses across diverse regions. This approach mitigates explicit consideration of issues such as period of infectivity and public adherence to government restrictions.

Results

Countries with the largest cumulative case tallies are characterised by a delayed response, whereas countries that avoid substantial community transmission during the period of study responded quickly. Countries that recovered rapidly also have a higher case identification rate and small numbers of undocumented community transmission at the early stages of the outbreak. We also demonstrate that uncertainty in numbers of undocumented infections dramatically impacts the risk of second waves. Our approach is also effective at pre-empting potential second waves and flare-ups.

Conclusions

We demonstrate the utility of modelling to interpret community behaviour in the early epidemic stages. Two lessons learnt that are important for the future are: i) countries that imposed strict containment measures early in the epidemic fared better with respect to numbers of reported cases; and ii) broader testing is required early in the epidemic to understand the magnitude of undocumented infections and recover rapidly. We conclude that clear patterns of containment are essential prior to relaxation of restrictions and show that modelling can provide insights to this end.
Influence of body mass index on SAPS3 prognostic performance in critically ill patients from Brazil
Authors: Ferreira Isabella B. B. , Menezes Rodrigo C. , Otero Matheus L. , Carmo Thomas A. , Telles Gabriel P. , Fahel Bruno V. B. , Barral-Netto Manoel , Arriaga Maria B. , Fukutani Kiyoshi F. , Neto Licurgo Pamplona , Agareno Gabriel A. , Agareno Sydney , Akrami Kevan M. , Filho Nivaldo M.Filgueiras , Andrade Bruno B.
Published: May 2020

Obesity has emerged as a significant global health problem, and its association with increased morbidity and mortality is well established. An obesity paradox has been extensively documented in the critically ill, appearing as a protective factor. Whether body mass index (BMI) impacts critical care severity scores has not been extensively studied previously, particularly in developing countries. This study aimed to evaluate the performance of severity scores across different BMI categories in a tertiary intensive care unit in Brazil. Observational and analytical cohort study in a general ICU in Northeastern Brazil between August 2015 and July 2018 that included all patients over 18 years of age admitted to the ICU. A total of 2,179 patients were included, with a mean age of 67.9 years and female predominance (53.1%). Similar to previous findings, those with overweight and obesity of any grade were not significantly associated with mortality, though for each additional 1kg/m2 there was a decrease of 0.04% in odds of death. The Simplified Acute Physiology Score III (SAPS3) accurately predicted mortality in all groups except in those underweight. Low weight appeared as an independent risk factor for mortality in the ICU. Furthermore, this is the first study to identify poor prognostic performance of a common ICU severity score in those with low weight, highlighting the need for alternative more precise metrics.
Incidence of COVID-19 in a cohort of adult and paediatric patients with rheumatic diseases treated with targeted biologic and synthetic disease-modifying anti-rheumatic drugs
Authors: Michelena Xabier , Borrell Helena , López-Corbeto Mireia , López-Lasanta María , Moreno Estefanía , Pascual-Pastor María , Erra Alba , Serrat Mayte , Espartal Esther , Antón Susana , Añez Gustavo Adolfo , Caparrós-Ruiz Raquel , Pluma Andrea , Trallero-Araguás Ernesto , Barceló-Bru Mireia , Almirall Miriam , De Agustín Juan José , Segura Jordi Lladós , Julià Antonio , Marsal Sara
Published: May 2020

OBJECTIVES

To investigate the incidence of COVID-19 in a cohort of adult and paediatric patients with rheumatic diseases receiving targeted biologic and synthetic disease modifying anti-rheumatic drugs (tDMARDs) and to explore the possible effect of these treatments in the clinical expression of COVID-19.

METHODS

A cross-sectional study comprising of a telephone survey and electronic health records review was performed including all adult and paediatric patients with rheumatic diseases treated with tDMARDs in a large rheumatology tertiary centre in Barcelona, Spain. Demographics, disease activity, COVID-19 related symptoms and contact history data were obtained from the start of the 2020 pandemic. Cumulative incidence of confirmed cases (SARS-CoV-2 positive PCR test) was compared to the population estimates for the same city districts from a governmental COVID-19 health database. Suspected cases were defined following WHO criteria and compared to those without compatible symptoms.

RESULTS

959 patients with rheumatic diseases treated with tDMARDs were included. We identified 11 confirmed SARS-CoV-2 positive cases in the adult cohort and no confirmed positive cases in the paediatric cohort. All patients had a successful recovery and only one patient required admission in the intensive care unit. When using the same classification criteria (only COVID-19 positive cases with pneumonia), COVID-19 incidence rates of the rheumatic patient cohort were very similar to that of the general population [(0.48% (95% CI 0.09 to 8.65%)] and [0.58% (95% CI 5.62 to 5.99%)], respectively. We found significant differences in tDMARDs proportions between the suspected and non-suspected cases (p=0.002).

CONCLUSION

Adult and paediatric patients with rheumatic diseases on tDMARDs do not seem to present a higher risk of COVID-19 or a more severe disease outcome when compared to general population. Our exploratory analysis suggests that the proportion of COVID-19 suspected cases differs between tDMARDs.
A Simple Method for Estimating the Number of Unconfirmed COVID-19 Cases in a Local Area that Includes a Confidence Interval: A Case Study of Whatcom County, Washington
Authors: Swanson David A. , Cossman Ronald E.
Published: May 2020

Along with many other data problems affecting the unfolding of the COVID-10 pandemic in the United States, virtually nothing is known about the number of positive, unconfirmed cases, especially in local areas. We show that it is possible to estimate the number of positive, unconfirmed COVID-19 cases using a simple, long-established method employed by demographers to estimate a population in the absence of a census count. We go on to show how a confidence interval can be constructed around an estimate of positive, unconfirmed COVID-19 cases constructed from this method, using Whatcom County, Washington as a case study.
Modelling and simulation of COVID-19 propagation in a large population with specific reference to India
Authors: Menon Ashish , Rajendran Nithin K , Chandrachud Anish , Setlur Girish
Published: May 2020

Deterministic mathematical models (called Compartmental models) of disease propagation such as the SIR model and its variants (MSIR, Carrier state, SEIR, SEIS, MSEIR, MSEIRS models) are used to study the propagation of COVID19 in a large population with specific reference to India.
The distribution and spread of susceptible and resistantNeisseria gonorrhoeaeacross demographic groups in a major metropolitan center
Authors: Mortimer Tatum D. , Pathela Preeti , Crawley Addie , Rakeman Jennifer L. , Lin Ying , Harris Simon R. , Blank Susan , Schillinger Julia A. , Grad Yonatan H.
Published: May 2020

Background

Genomic epidemiology studies of gonorrhea in the United States have primarily focused on national surveillance for antibiotic resistance, and patterns of local transmission between demographic groups of resistant and susceptible strains are unknown.

Methods

We analyzed a convenience sample of genome sequences, antibiotic susceptibility, and patient data from 897 gonococcal isolates cultured at the NYC Public Health Laboratory from NYC Department of Health and Mental Hygiene (DOHMH) Sexual Health Clinic (SHC) patients, primarily in 2012-13. We reconstructed the gonococcal phylogeny, defined transmission clusters using a 10 non-recombinant single nucleotide polymorphism threshold, tested for clustering of demographic groups, and placed NYC isolates in a global phylogenetic context.

Results

The NYC gonococcal phylogeny reflected global diversity with isolates from 22/23 of the prevalent global lineages (96%). Isolates clustered on the phylogeny by patient sexual behavior (p<0.001) and race/ethnicity (p<0.001).Minimum inhibitory concentrations were higher across antibiotics in isolates from men who have sex with men compared to heterosexuals (p<0.001) and white heterosexuals compared to black heterosexuals (p<0.01). In our dataset, all large transmission clusters (≥10 samples) ofN. gonorrhoeaewere susceptible to ciprofloxacin, ceftriaxone, and azithromycin and comprised isolates from patients across demographic groups.

Conclusions

All large transmission clusters were susceptible to gonorrhea therapies, suggesting that resistance to empiric therapy was not a main driver of spread, even as risk for resistance varied across demographic groups. Further study of local transmission networks is needed to identify drivers of transmission.
Early evidence of a higher incidence of COVID-19 in the air-polluted regions of eight severely affected countries
Authors: Pansini Riccardo , Fornacca Davide
Published: May 2020

COVID-19 has spread in all continents in a span of just over three months, escalating into a pandemic that poses several humanitarian as well as scientific challenges. We here investigated the geographical character of the infection and correlate it with several annual satellite and ground indexes of air quality in: China, the United States, Italy, Iran, France, Spain, Germany, and the United Kingdom. Controlling for population size, we found more viral infections in those areas afflicted by high PM 2.5 and Nitrogen Dioxide values. Higher mortality was also correlated with relatively poor air quality. In Italy, the correspondence between the Po valley pollution and SARS-CoV-2 infections and induced mortality was the starkest, originating right in the most polluted European area. Air pollution appears to be for this disease a risk factor similar to smoking. This suggests the detrimental impact climate change will have on the trajectory of future respiratory epidemics.
Novel Spatiotemporal Feature Extraction Parallel Deep Neural Network for Forecasting Confirmed Cases of Coronavirus Disease 2019
Authors: Huang Chiou-Jye , Shen Yamin , Kuo Ping-Huan , Chen Yung-Hsiang
Published: May 2020

The coronavirus disease 2019 pandemic continues as of March 26 and spread to Europe on approximately February 24. A report from April 29 revealed 1.26 million confirmed cases and 125 928 deaths in Europe. This study proposed a novel deep neural network framework, COVID-19Net, which parallelly combines a convolutional neural network (CNN) and bidirectional gated recurrent units (GRUs). Three European countries with severe outbreaks were studied—Germany, Italy, and Spain—to extract spatiotemporal feature and predict the number of confirmed cases. The prediction results acquired from COVID-19Net were compared to those obtained using a CNN, GRU, and CNN-GRU. The mean absolute error, mean absolute percentage error, and root mean square error, which are commonly used model assessment indices, were used to compare the accuracy of the models. The results verified that COVID-19Net was notably more accurate than the other models. The mean absolute percentage error generated by COVID-19Net was 1.447 for Germany, 1.801 for Italy, and 2.828 for Spain, which were considerably lower than those of the other models. This indicated that the proposed framework can accurately predict the accumulated number of confirmed cases in the three countries and serve as a crucial reference for devising public health strategies.
Social Media Platforms for Health Communication and Research in the Face of COVID-19 Pandemic: A Cross Sectional Survey in Uganda
Authors: Olum Ronald , Bongomin Felix
Published: May 2020

Objectives

(1) To examine the usage of social media and other forms of media among medical students (MS) and healthcare professionals (HCPs) in Uganda. (2) To assess the perceived usefulness of social media and other forms of media for COVID-19 public health campaigns.

Design

A descriptive WhatsApp messenger-based cross-sectional survey in April 2020.

Setting

Makerere University Teaching Hospitals (MUTH) and 9 of the 10 medical schools in Uganda.

Participants

HCPs at MUTH and MS in the 9 medical schools in Uganda.

Main outcome measures

We collected data on sociodemographic characteristics, sources of information on COVID-19, preferences of social media platform and perceived usefulness of the different media platforms for acquisition of knowledge on COVID-19.

Result

Overall, response rate was 21.5% for both MS and HCPs. In total, 877 (HCPS [136, 15.5%], MS [741, 85.5%]) were studied. Majority (n=555, 63.3%) were male with a median age of 24 (range: 18-66) years. Social media was a source of information for 665 (75.8%) participants. Usage was similar among MS and HCPs (565/741 (76.2%) vs. 100/136 (73.5%), p=0.5). Among the MS, commonly used social media were: WhatsApp (n=705, 95.1%) Facebook (n=405, 54.8%), Twitter (n=290, 39.1%), Instagram (n=178, 24.0) and Telegram (n=80, 10.8%). Except for WhatsApp, male MS we more likely to use the other social media platforms (p= <0.001 − 0.01). Mass media (television and radio) and social media were preferred the most useful tools for dissemination of COVID-19 related information.

Conclusion

More than two-thirds of MS and HCPs are routinely using social media in Uganda. Social media platforms may be used for dissemination of information as well as a research tool among MS and HCPs. Social media alongside other media platforms can also be used as sources of reliable information on COVID-19 as well as for dissemination of research findings and guidelines.

Strengths and limitations

This is the first study in sub Saharan Africa on the use of social media for research during the COVID-19 pandemic.

The study also explores perceived usefulness of different media for COVID-19 public health campaigns.

Diversity of the participants consisting both healthcare professionals and medical students.

A relatively large sample size was enrolled in the survey despite a low response rate.
Perspectives of Cancer Patients and Their Health during the COVID-19 Pandemic
Authors: Lou Emil , Teoh Deanna , Brown Katherine , Blaes Anne , Holtan Shernan G. , Jewett Patricia , Parsons Helen , Mburu E. Waruiru , Thomaier Lauren , Hui Jane Yuet Ching , Nelson Heather H. , Vogel Rachel I.
Published: May 2020

Introduction

The immunosuppressive nature of some cancers and many cancer-directed treatments may increase the risk of infection with and severe sequelae from Coronavirus Disease 2019 (COVID-19). The objective of this study was to compare concerns about COVID-19 among individuals undergoing cancer treatment to those with a history of cancer not currently receiving therapy and to those without a cancer history.

Methods

We conducted a cross-sectional anonymous online survey study of adults currently residing in the United States. Participants were recruited over a one-week period (April 3-11, 2020) using promoted advertisements on Facebook and Twitter. Groups were compared using chi-squared tests, Fisher’s exact tests, and t-tests.

Results

543 respondents from 47 states provided information on their cancer history and were included in analyses. Participants receiving active treatment reported greater concern about coronavirus infection (p<0.0001), higher levels of family distress caused by the COVID-19 pandemic (p=0.004), and greater concern that the general public does not adequately understand the seriousness of COVID-19 (p=0.04). Those with metastatic disease were more likely to indicate that COVID-19 had negatively affected their cancer care compared to patients with non-metastatic cancer (50.8% vs. 31.0%; p=0.02). The most commonly reported treatment modifications included chemotherapy delays.

Conclusions

Patients undergoing active treatment for cancer were most concerned about the short-term effects of the COVID-19 pandemic on the logistics as well as potential efficacy of ongoing cancer treatment, longer term effects, and overarching societal concerns that the population at large is not as concerned about the public health implications of the coronavirus.
Modeling the COVID-19 outbreak in the United States
Authors: Narayanan Charit Samyak
Published: May 2020

The COVID-19 contagion has developed at an alarming rate in the US and as of April 24, 2020, tens of thousands of people have already died from the disease. In the event of an outbreak like such, forecasting the extent of the mortality that will occur is crucial to aid the implementation of effective interventions. Mortality depends on two factors: the case fatality rate and the case incidence. We combine a cohort-based model that determines case fatality rates along with a modified logistic model that evaluates the case incidence to determine the number of deaths in all the US states over time; the model is also able to include the impact of interventions. Both models yield exceptional goodness-of-fit. The model predicted a range of death outcomes (79k to 246k) all of which are considerably greater than the figures presented in mainstream media. This model can be used more effectively than current models to estimate the number of deaths during an outbreak, allowing for better planning.
Dopamine firing plays a double role in coding reward prediction errors and signaling motivation in a working memory task
Authors: Sarno Stefania , Beirán Manuel , Falcó-Roget Joan , Diaz-deLeon Gabriel , Rossi-Pool Román , Romo Ranulfo , Parga Néstor
Published: May 2020

Little is known about how dopamine (DA) neuron firing rates behave in cognitively demanding decision-making tasks. Here we investigated midbrain DA activity in monkeys performing a discrimination task in which the animal had to use working memory (WM) to report which of two sequentially applied vibrotactile stimuli had the higher frequency. We found that perception was altered by an internal bias, likely generated by deterioration of the representation of the first frequency during the WM period. This bias greatly controlled the DA phasic response during the two stimulation periods, confirming that DA reward prediction errors reflected subjective stimulus perception. Contrastingly, tonic dopamine activity during WM was not affected by the bias and did not encode the stored frequency. More interestingly, both WM activity and phasic responses before the second stimulus negatively correlated with reaction times of the animal after the trial start cue and thus represented motivated behavior on a trial-by-trial basis. During WM, this motivation signal underwent a ramp-like increase. At the same time, motivation reduced noise in perception and, by decreasing the effect of the bias, improved performance, especially in difficult trials. Overall, our results show that DA activity was simultaneously involved in reward prediction, motivation and WM. Also, the ramping activity during the WM period suggests a possible DA role in stabilizing sustained cortical activity, hypothetically by increasing the gain communicated to prefrontal neurons in a motivation-dependent way.
The development trends of antineoplastics targeting PD-1/PD-L1 based on scientometrics and patentometrics
Authors: Zhang Ting , Chen Juan , Lu Yan , Ouyang Zhaolian
Published: May 2020

Background

This paper aims to show the scientific research and technological development trends of antineoplastics targeting PD-1/PD-L1 based on scientometrics and patentometrics.

Methodology/Principal Findings

Publications and patents related to antineoplastics targeting PD-1/PD-L1were searched and collected from the Web of Science (WoS) and the Derwent Innovation Index (DII) respectively. Totally, 11244 publications and 5501 patents were obtained. The publications were analyzed from the annual number, the top countries/regions and organizations to describe the scientific research trends in this field. The patents were analyzed from the annual number, the top priority countries and patent assignees to reveal the characteristics and status of technological development. As well as the identification of scientific research focus and technological development focus was based on the title and abstract of the publications and patents, using the freely available computer program VOSviewer for clustering and visualization analysis. The number of scientific publications and patent applications showed obvious increase of 29.84% and 33.46% in recent ten years (2009-2018), respectively. Results suggested that the most productive countries/regions publishing on antineoplastics targeting PD-1/PD-L1 were USA and China, and the top three productive organizations were all from USA, including Harvard University, VA Boston Healthcare System (VA BHS) and University Of California System. There were four scientific research focus: (1) immune escape mechanism, (2) biomarkers related to efficacy and prognosis, (3) immune-related adverse event, and (4) drug design and preparation, and five technological development focus: (1) testing methods and apparatus, (2) indications related to carcinoma, (3) biomarkers related to diagnosis and prognosis, (4) small molecule inhibitors, and (5) indications other than carcinoma.

Conclusions/Significance

The results of this study presents an overview of the characteristics of research status and trends of antineoplastics targeting PD-1/PD-L1, which could help readers broaden innovative ideas and discover new technological opportunities, and also serve as important indicators for government policymaking.
A Susceptible-Infected-Removed (SIR) model of COVID-19 epidemic trend in Malaysia under Movement Control Order (MCO) using a data fitting approach
Authors: Arifin Wan Nor , Chan Weng Howe , Amaran Safiya , Musa Kamarul Imran
Published: May 2020

Background

In this work, we presented a Susceptible-Infected-Removed (SIR) epidemiological model of COVID-19 epidemic in Malaysia post- and pre-Movement Control Order (MCO). The proposed SIR model was fitted to confirmed COVID-19 cases from the official press statements to closely reflect the observed epidemic trend in Malaysia. The proposed model is aimed to provide an accurate predictive information for decision makers in assessing the public health and social measures related to COVID-19 epidemic.

Methods

The SIR model was fitted to the data by minimizing a weighted loss function; the sum of the residual sum of squares (RSS) of infected, removed and total cases. Optimized beta (β),), gamma (γ) parameter values) parameter values and the starting value of susceptible individuals (N) were obtained.

Results

The SIR model post-MCO indicates the peak of infection on 10 April 2020, less than 100 active cases by 8 July 2020, less than 10 active cases by 29 August 2020, and close to zero daily new case by 22 July 2020, with a total of 6562 infected cases. In the absence of MCO, the model predicts the peak of infection on 1 May 2020, less than 100 active cases by 14 February 2021, less than 10 active cases by 26 April 2021 and close to zero daily new case by 6 October 2020, with a total of 1.6 million infected cases. Conclusion: The results suggest that the present MCO has significantly reduced the number of susceptible population and the total number of infected cases. The method to fit the SIR model used in this study was found to be accurate in reflecting the observed data. The method can be used to predict the epidemic trend of COVID-19 in other countries.
Presence and vitality of SARS-CoV-2 virus in wastewaters and rivers
Authors: Rimoldi Sara Giordana , Stefani Fabrizio , Gigantiello Anna , Polesello Stefano , Comandatore Francesco , Mileto Davide , Maresca Mafalda , Longobardi Concetta , Mancon Alessandro , Romeri Francesca , Pagani Cristina , Moja Lorenzo , Gismondo Maria Rita , Salerno Franco
Published: May 2020

Wastewater-based epidemiology has been proposed to monitor the diffusion and trend of SARS-CoV-2 pandemic. In the present study, raw and treated samples from three wastewater treatment plants, and two river samples characterized the Milano Metropolitan Area, Italy, were surveyed for SARS-CoV-2 RNA positivity to real time PCR and infectiveness. Moreover, whole genome sequencing and phylogenetic analysis of isolated strains was performed.
Raw wastewater samples resulted positive to PCR amplification, while treated water samples were always negative (four and two samples, respectively, sampled in two dates). Moreover, the rate of positivity in raw wastewater samples decreased after eight days, in congruence with the epidemiological trend estimated for the interested provinces. Virus infectiveness was always not significant, indicating the effectiveness of wastewater treatments, or the natural decay of viral vitality, which implied the absence of significant risk of infection from wastewaters. Samples from receiving rivers (two sites, sampled in the same dates as wastewaters) showed in some cases a positivity to PCR amplification, probably due to non-treated discharges, or the combined sewage overflows. Nevertheless, also for rivers vitality was negligible, indicating the absence of sanitary risks. Phylogenetic analysis of genome indicated that the isolated virus belongs to the most spread strain present in Europe and similar to another strain found in Lombardy.
Characteristics of lymphocyte subsets and their predicting values for the severity of COVID-19 patients
Authors: Wang Jingrong , Dong Xingqi , Zhang Boting , Yang Xinping , Li Zhi , Wang Xicheng , Zuo Shuguang
Published: May 2020

Severe COVID-19 patients showed worse clinical outcomes compared to mild and moderate patients. However, effective indicators are still lacking to predict the severity of the disease. In the present study, we retrospectively analyzed the clinical and laboratory data of 16 COVID-19 patients and found that the absolute counts of three T-cells (CD3+, CD4+, and CD8+) were significantly lower in the moderate and severe patients than those in mild patients and were significantly lower in severe patients than in moderate patients on admission. With the recovery of the COVID-19, serum levels of inflammatory biomarkers (CRP, PCT, and IL6) of moderate and severe patients gradually decreased. In contrast, the counts of lymphocytes and their subsets including CD3+, CD4+, and CD8+T cells gradually increased in severe patients, and eventually showed comparable levels with moderate patients. ROC analysis showed that the counts of CD3+, CD4+, and CD8+T-cells with AUC > 0.9 have potential values for predicting the severity of COVID-19 patients. In conclusion, the reduction of CD3+, CD4+, and CD8+T-cells is related to the severity of COVID-19 and dynamic detection of these T-lymphocyte subsets may help predict the outcome of the patients.
Computational methods to develop potential neutralizing antibody Fab region against SARS-CoV-2 as therapeutic and diagnostic tool
Authors: Manikyam Hemanth K. , Joshi Sunil K.
Published: May 2020

SARS-CoV-2, a global pandemic originated from Wuhan city of China in the month of December 2019. There is an urgency to identify potential antibodies to neutralize the virus and also as a diagnostic tool candidate. At present palliative treatments using existing antiviral drugs are under trails to treat SARS-CoV-2.Whole Genome sequence of Wuhan market sample of SARS-CoV-2 was obtained from NCBI Gene ID MN908947.3.Spike protein sequence PDB ID 6VSB obtained from RCSB database. Spike protein sequence had shown top V gene match with IGLV1-44*01, IGLV1-47*02 and has VL type chain. Whole Genome sequence had shown top V gene match with IGHV1-38-4*01 and has VH type chain. VD chain had shown link to allele HLA-A0206 80%, HLA-A0217 80%, HLA-A2301 75%, HLA-A0203 75%, HLA-A0202 70% and HLA-A0201 55% of binding levels. Some conserved regions of spike protein had shown strong binding affinity with HLA-A-0*201, HLA-A24, HLA-B-5701 and HLA-B-5703 alpha chains. Synthetic Fab construct BCR type antibody IgG (CR5840) had shown Polyspecific binding activity with spike glycoprotein when compared with available Anti-SARS antibody CR3022.Thus we propose CR5840 Fab constructed antibody as potential neutralizing antibody for SARS-CoV-2. Based on germline analysis we also propose cytotoxic T lymphocyte epitope peptide selective system as effective tool for the development of SARS-CoV-2 vaccine.
Previous experience with depression in others and self: a cross-sectional study of the impact on stigma and help-seeking attitudes
Authors: Conceição Virgínia da , Rothes Inês , Severo Milton , Griffiths Kathy , Hegerl Ulrich , Gusmão Ricardo
Published: May 2020

Background

Stigma has been considered a significant barrier both in treatment, rehabilitation and help-seeking behaviours of people diagnosed with depression. This study aimed to assess the influence of the type of previous experience with depression on depression stigma, identify the effects of previous experience with depression on stigma and to analyse the effects of stigma on help-seeking attitudes.

Methods

A total of 1693 participants with a mean age of 47.2 (SD=18.17) completed the Depression Stigma Scale (DSS), the Attitude Toward Seeking Professional Psychological Help (ATSPPH), and a sociodemographic questionnaire. We categorised participants into four comparison groups: no previous experience with depression (n=479), indirect experience with depression (n=661), direct experience with depression (n=137), and both direct and indirect experience with depression (n=416). Data were analysed using SPSS 24.0.

Results

Levels of personal stigma were lower in people who had family and friends experiencing depression in comparison with individuals with no history of depression experience. Better attitudes towards help-seeking were evident in those with lower personal stigma, and worse help-seeking attitudes were associated with higher perceived stigma in the indirect previous experience group.

Limitations

Duration of participant exposure to depression was not collected.

Conclusions

The individual’s experience with depression influences the development of personal stigmatisation towards depression and plays a role in help-seeking behaviours. Addressing people’s experience of depression might be a practical way of reducing depression stigma and improve help-seeking behaviours.
Predicting amphibian intraspecific diversity with machine learning: Challenges and prospects for integrating traits, geography, and genetic data
Authors: Barrow Lisa N. , Masiero da Fonseca Emanuel , Thompson Coleen E. P. , Carstens Bryan C.
Published: May 2020

The growing availability of genetic datasets, in combination with machine learning frameworks, offer great potential to answer long-standing questions in ecology and evolution. One such question has intrigued population geneticists, biogeographers, and conservation biologists: What determines intraspecific genetic diversity? This question is challenging to answer because many factors may influence genetic variation, including life history traits, historical influences, and geography, and the relative importance of these factors varies across taxonomic and geographic scales. Furthermore, interpreting the influence of numerous, potentially correlated variables is difficult with traditional statistical approaches. To address these challenges, we combined repurposed data with machine learning and investigated predictors of genetic diversity, focusing on Nearctic amphibians as a case study. We aggregated species traits, range characteristics, and >42,000 genetic sequences for 299 species using open-access scripts and various databases. After identifying important predictors of nucleotide diversity with random forest regression, we conducted follow-up analyses to examine the roles of phylogenetic history, geography, and demographic processes on intraspecific diversity. Although life history traits were not important predictors for this dataset, we found significant phylogenetic signal in genetic diversity within amphibians. We also found that salamander species at northern latitudes contain lower genetic diversity. Data repurposing and machine learning provide valuable tools for detecting patterns with relevance for conservation, but concerted efforts are needed to compile meaningful datasets with greater utility for understanding global biodiversity.
Mesenchymal stem cells with overexpression of Angiotensin-converting enzyme-2 improved the microenvironment and cardiac function in a rat model of myocardial infarction
Authors: Liu Chao , Fan Yue , Zhu Hong-Yi , zhou Lu , Wang Yu , Li Qing-Ping
Published: May 2020

Background

Angiotensin-converting enzyme-2 (ACE2) overexpression improves left ventricular remodeling and function in diabetic cardiomyopathy; however, the effect of ACE2-overexpressed mesenchymal stem cells (MSCs) on myocardial infarction (MI) remains unexplored. This study aimed to investigate the effect of ACE2-overexpression on the function of MSCs and the therapeutic efficacy of MSCs for MI.

Methods

MSCs were transfected with Ace2 gene using lentivirus, and then transplanted into the border zone of ischemic heart. The renin-angiotensin system (RAS) expression, nitric oxide synthase (NOS) expression, paracrine factors, anti-hypoxia ability, tube formation of MSCs, and heart function were determined.

Results

MSCs expressed little ACE2. ACE2-overexpression decreased the expression of AT1 and VEGF apparently, up-regulated the paracrine of HGF, and increased the synthesis of Angiotensin 1-7 in vitro. ACE2-overexpressed MSCs showed a cytoprotective effect on cardiomyocyte, and an interesting tube formation ability, decreased the heart fibrosis and infarct size, and improved the heart function.

Conclusion

Therapies employing MSCs with ACE2 overexpression may represent an effective treatment for improving the myocardium microenvironment and the cardiac function after MI.
Trapped Topoisomerase II initiates formation ofde novoduplicationsviathe nonhomologous end-joining pathway in yeast
Authors: Stantial Nicole , Rogojina Anna , Gilbertson Matthew , Sun Yilun , Miles Hannah , Shaltz Samantha , Berger James , Nitiss Karin C. , Jinks-Robertson Sue , Nitiss John L.
Published: May 2020

Topoisomerase II (Top2) is an essential enzyme that resolves catenanes between sister chromatids as well as supercoils associated with the over- or under-winding of duplex DNA. Top2 alters DNA topology by making a double-strand break (DSB) in DNA and passing an intact duplex through the break. Each component monomer of the Top2 homodimer nicks one of the DNA strands and forms a covalent phosphotyrosyl bond with the 5’ end. Stabilization of this intermediate by chemotherapeutic drugs such as etoposide leads to persistent and potentially toxic DSBs. We describe the isolation of a yeasttop2mutant (top2- F1025Y,R1128G) whose product generates a stabilized cleavage intermediatein vitro. In yeast cells, overexpression of thetop2- F1025Y,R1128Gallele is associated with a novel mutation signature that is characterized byde novoduplications of DNA sequence that depend on the nonhomologous end-joining pathway of DSB repair. Top2-associated duplications are promoted by the clean removal of the enzyme from DNA ends and are suppressed when the protein is removed as part of an oligonucleotide.TOP2cells treated with etoposide exhibit the same mutation signature, as do cells that over-express the wild-type protein. These results have implications for genome evolution and are relevant to the clinical use of chemotherapeutic drugs that target Top2.

SIGNIFICANCE STATEMENT

DNA-strand separation during transcription and replication creates topological problems that are resolved by topoisomerases. These enzymes nick DNA strands to allow strand passage and then reseal the broken DNA to restore its integrity. Topoisomerase II (Top2) nicks complementary DNA strands to create double-strand break (DSBs) intermediates that can be stabilized by chemotherapeutic drugs and are toxic if not repaired. We identified a mutant form of yeast Top2 that forms stabilized cleavage intermediates in the absence of drugs. Over- expression of the mutant Top2 was associated with a unique mutation signature in which small (1-4 bp), unique segments of DNA were duplicated. Thesede novoduplications required the nonhomologous end-joining pathway of DSB repair, and their Top2-dependence has clinical and evolutionary implications.
RLP23 is required for Arabidopsis immunity against the grey mould pathogenBotrytis cinerea
Authors: Ono Erika , Mise Kazuyuki , Takano Yoshitaka
Published: May 2020

Necrosis- and ethylene-inducing-like proteins (NLPs) are secreted by fungi, oomycetes and bacteria. Conserved nlp peptides derived from NLPs are recognized as pathogen-associated molecular patterns (PAMPs), leading to PAMP-triggered immune responses. RLP23 is the receptor of the nlp peptides inArabidopsis thaliana; however, its actual contribution to plant immunity is unclear. Here, we report that RLP23 is required for Arabidopsis immunity against the necrotrophic fungal pathogenBotrytis cinerea. Arabidopsisrlp23mutants exhibited enhanced susceptibility toB. cinereacompared with the wild-type plants. Notably, microscopic observation of theB. cinereainfection behaviour indicated the involvement of RLP23 in pre-invasive resistance to the pathogen.B. cinereacarried twoNLPgenes,BcNEP1andBcNEP2;BcNEP1was expressed preferentially before/during invasion into Arabidopsis, whereasBcNEP2was expressed at the late phase of infection. Importantly, the nlp peptides derived from both BcNEP1 and BcNEP2 induced the production of reactive oxygen species in an RLP23-dependent manner. In contrast, other necrotrophic fungusAlternaria brassicicoladid not express theNLPgene in the early infection phase and exhibited no enhanced virulence in therlp23mutants. Collectively, these results strongly suggest that RLP23 contributes to Arabidopsis pre-invasive resistance toB. cinereavia NLP recognition at the early infection phase.
Computational analysis on the ACE2-derived peptides for neutralizing the ACE2 binding to the spike protein of SARS-CoV-2
Authors: Lupala Cecylia S. , Kumar Vikash , Li Xuanxuan , Su Xiao-dong , Liu Haiguang
Published: May 2020

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the COVID-19, is spreading globally and has infected more than 3 million people. It has been discovered that SARS-CoV-2 initiates the entry into cells by binding to human angiotensin-converting enzyme 2 (hACE2) through the receptor binding domain (RBD) of its spike glycoprotein. Hence, drugs that can interfere the SARS-CoV-2-RBD binding to hACE2 potentially can inhibit SARS-CoV-2 from entering human cells. Here, based on the N-terminal helix α1 of human ACE2, we designed nine short peptides that have potential to inhibit SARS-CoV-2 binding. Molecular dynamics simulations of peptides in the their free and SARS-CoV-2 RBD-bound forms allow us to identify fragments that are stable in water and have strong binding affinity to the SARS-CoV-2 spike proteins. The important interactions between peptides and RBD are highlighted to provide guidance for the design of peptidomimetics against the SARS-CoV-2.
igv.js: an embeddable JavaScript implementation of the Integrative Genomics Viewer (IGV)
Authors: Robinson James T. , Thorvaldsdóttir Helga , Turner Douglass , Mesirov Jill P.
Published: May 2020

igv.js is an embeddable JavaScript implementation of the Integrative Genomics Viewer (IGV). It can be easily dropped into any web page with a single line of code and has no external dependencies. The viewer runs completely in the web browser, with no backend server and no data pre-processing required.
COVIDier: A Deep-learning Tool For Coronaviruses Genome And Virulence Proteins Classification
Authors: Habib Peter T. , Alsamman Alsamman M. , Saber-Ayad Maha , Hassanein Sameh E. , Hamwieh Aladdin
Published: May 2020

COVID-19, caused by SARS-CoV-2 infection, has already reached pandemic proportions in a matter of a few weeks. At the time of writing this manuscript, the unprecedented public health crisis caused more than 2.5 million cases with a mortality range of 5-7%. The SARS-CoV-2, also called novel Coronavirus, is related to both SARS-CoV and bat SARS. Great efforts have been spent to control the pandemic that has become a significant burden on the health systems in a short time. Since the emergence of the crisis, a great number of researchers started to use the AI tools to identify drugs, diagnosing using CT scan images, scanning body temperature, and classifying the severity of the disease. The emergence of variants of the SARS-CoV-2 genome is a challenging problem with expected serious consequences on the management of the disease. Here, we introduce COVIDier, a deep learning-based software that is enabled to classify the different genomes of Alpha coronavirus, Beta coronavirus, MERS, SARS-CoV-1, SARS-CoV-2, and bronchitis-CoV. COVIDier was trained on 1925 genomes, belonging to the three families of SARS retrieved from NCBI Database to propose a new method to train deep learning model trained on genome data using Multi-layer Perceptron Classifier (MLPClassifier), a deep learning algorithm, that could blindly predict the virus family name from the genome of by predicting the statistically similar genome from training data to the given genome. COVIDier able to predict how close the emerging novel genomes of SARS to the known genomes with accuracy 99%. COVIDier can replace tools like BLAST that consume higher CPU and time.