title: Effect of underlying comorbidities on the infection and severity of COVID-19 in South Korea

text: ABSTRACT Background: The coronavirus disease (COVID-19) pandemic is an emerging threat worldwide. It is still unclear how comorbidities affect the risk of infection and severity of COVID-19. Methods: A nationwide retrospective case-control study of 65,149 individuals, aged 18 years or older, whose medical cost for COVID-19 testing were claimed until April 8, 2020. The diagnosis of COVID-19 and severity of COVID-19 infection were identified from the reimbursement data using diagnosis codes and based on whether respiratory support was used, respectively. Odds ratios were estimated using multiple logistic regression, after adjusting for age, sex, region, healthcare utilization, and insurance status. Results: The COVID-19 group (5,172 of 65,149) was younger and showed higher proportion of females. 5.6% (293 of 5,172) of COVID-19 cases were severe. The severe COVID-19 group had older patients and a higher male ratio than the non-severe group. Cushing syndrome (Odds ratio range (ORR) 2.059-2.358), chronic renal disease (ORR 1.292-1.604), anemia (OR 1.132), bone marrow dysfunction (ORR 1.471-1.645), and schizophrenia (ORR 1.287-1.556) showed significant association with infection of COVID-19. In terms of severity, diabetes (OR 1.417, 95% CI 1.047-1.917), hypertension (OR 1.378, 95% CI 1.008-1.883), heart failure (ORR 1.562-1.730), chronic lower respiratory disease (ORR 1.361-1.413), non-infectious lower digestive system disease (ORR 1.361-1.418), rheumatoid arthritis (ORR 1.865-1.908), substance use (ORR 2.790-2.848), and schizophrenia (ORR 3.434-3.833) were related with severe COVID-19. Conclusions: We identified several comorbidities associated with COVID-19. Health care workers should be more careful when diagnosing and treating COVID-19 when the patient has the above-mentioned comorbidities. Keywords: COVID-19, SARS-CoV-2, Comorbidity, Risk factor, Severity


title: Which Measures are Effective in Containing COVID-19?Empirical Research Based on Prevention and Control Cases in China

text: Various epidemic prevention and control measures aimed at reducing person-to-person contact has paid a certain cost while controlling the epidemic. So accurate evaluation of these measures helps to maximize the effectiveness of prevention and control while minimizing social costs. In this paper, we develop the model in Dirk Brockmann and Dirk Helbing (2013) to theoretically explain the impact mechanism of traffic control and social distancing measures on the spread of the epidemic, and empirically tests the effect of the two measures in China at the present stage using econometric approach. We found that both traffic control and social distancing measures have played a very good role in controlling the development of the epidemic. Nationally, social distancing measures are better than traffic control measures; the two measures are complementary and their combined action will play a better epidemic prevention effect; Traffic control and social distancing do not work everywhere. Traffic control only works in cities with higher GDP per capita and population size, while fails in cities with lower GDP per capita and population size. In cities with lower population size, social distancing becomes inoperative; the rapid and accurate transmission of information, a higher protection awareness of the public, and a stronger confidence of residents in epidemic prevention can promote the realization of the measure effects. The findings above verify the effectiveness and correctness of the measures implemented in China at present, at the same time, we propose that it is necessary to fully consider the respective characteristics of the two measures, cooperating and complementing each other; what's more, measures should be formulated according to the city's own situation, achieving precise epidemic prevention; Finally, we should increase the transparency of information, improve protection awareness of the public, guide emotions of the public in a proper way, enhancing public confidence.


docid: gpnhzlad

title: "Virus hunting"using radial distance weighted discrimination

text: Motivated by the challenge of using DNA-seq data to identify viruses in human blood samples, we propose a novel classification algorithm called"Radial Distance Weighted Discrimination"(or Radial DWD). This classifier is designed for binary classification, assuming one class is surrounded by the other class in very diverse radial directions, which is seen to be typical for our virus detection data. This separation of the 2 classes in multiple radial directions naturally motivates the development of Radial DWD. While classical machine learning methods such as the Support Vector Machine and linear Distance Weighted Discrimination can sometimes give reasonable answers for a given data set, their generalizability is severely compromised because of the linear separating boundary. Radial DWD addresses this challenge by using a more appropriate (in this particular case) spherical separating boundary. Simulations show that for appropriate radial contexts, this gives much better generalizability than linear methods, and also much better than conventional kernel based (nonlinear) Support Vector Machines, because the latter methods essentially use much of the information in the data for determining the shape of the separating boundary. The effectiveness of Radial DWD is demonstrated for real virus detection.


title: Level of IL-6 predicts respiratory failure in hospitalized symptomatic COVID-19 patients

text: The pandemic Coronavirus-disease 19 (COVID-19) is characterized by a heterogeneous clinical course. While most patients experience only mild symptoms, a relevant proportion develop severe disease progression with increasing hypoxia up to acute respiratory distress syndrome. The substantial number of patients with severe disease have strained intensive care capacities to an unprecedented level. Owing to the highly variable course and lack of reliable predictors for deterioration, we aimed to identify variables that allow the prediction of patients with a high risk of respiratory failure and need of mechanical ventilation Patients with PCR proven symptomatic COVID-19 infection hospitalized at our institution from 29th February to 27th March 2020 (n=40) were analyzed for baseline clinical and laboratory findings. Patients requiring mechanical ventilation 13/40 (32.5%) did not differ in age, comorbidities, radiological findings, respiratory rate or qSofa score. However, elevated interleukin-6 (IL-6) was strongly associated with the need for mechanical ventilation (p=1.2.10-5). In addition, the maximal IL-6 level (cutoff 80 pg/ml) for each patient during disease predicted respiratory failure with high accuracy (p=1.7.10-8, AUC=0.98). The risk of respiratory failure for patients with IL-6 levels of ≥ 80 pg/ml was 22 times higher compared to patients with lower IL-6 levels. In the current situation with overwhelmed intensive care units and overcrowded emergency rooms, correct triage of patients in need of intensive care is crucial. Our study shows that IL-6 is an effective marker that might be able to predict upcoming respiratory failure with high accuracy and help physicians correctly allocate patients at an early stage.


title: Master Regulator Analysis of the SARS-CoV-2/Human interactome

text: the recent epidemic outbreak of a novel human coronavirus called SARS-CoV-2 and causing the respiratory tract disease COVID-19 has reached worldwide resonance and a global effort is being undertaken to characterize the molecular features and evolutionary origins of this virus. In this paper, we set out to shed light on the SARS-CoV-2/host receptor recognition, a crucial factor for successful virus infection. Based on the current knowledge of the interactome between SARS-CoV-2 and host cell proteins, we performed Master Regulator Analysis to detect which parts of the human interactome are most affected by the infection. We detected, amongst others, affected apoptotic and mitochondrial mechanisms, and a downregulation of the ACE2 protein receptor, notions that can be used to develop specific therapies against this new virus.


title: The Epidemiology of COVID-19 and applying Non Pharmaceutical interventions by using the Susceptible, Infectious Recovered epidemiological Model in Pakistan.

text: Introduction: The COVID-19 is caused by the virus known as sever acute respiratory syndrome corona virus 2 (SARS-CoV-2) having the common symptoms such as Flue, fever, dry cough and shortness of breath. The first case was reported in WUHAN city china in December 2019 and it spread to the whole world, WHO declared as world pandemic on 11th march 2020. SIR Epidemiological Model: The first case in Pakistan was confirmed on 26th Feb 2020 as by the 8th April 2020 the total no of confirmed cases 4187 with 58 deaths and 467 recoveries throughout the country. The upcoming situation of the COVID-19 in Pakistan is forecasted by using SIR epidemiological, which is one of the mathematical derivative models with great accuracy rate prediction used for infectious disease. This model was introduced in the early 20th century. Results: Pakistan is will be having a heavy burden of patients 80000 plus infected patients 45000 recoveries 10000 hospitalized 3000 ICU and 800 plus deaths in the next 20 days. A complete lock down, social distancing and imposing curfew to keep every person at home can save Pakistan from a very huge number 1000000 infected patients with huge number of causalities with next 2 months. Key words: COVID-19, Coronavirus COV2, Pakistan, SIR model


title: Rhabdomyolysis as a Presentation of 2019 Novel Coronavirus Disease

text: An emerging viral infection is a global public health challenge. The development of modern, fast, and extensive transportation makes the outbreak hard to contain. Everyone is at risk, and the outbreak can rapidly turn into a pandemic crisis, like what we are currently facing for the 2019 novel coronavirus disease (COVID-19). Prompt diagnosis of the case is required to improve patients’ prognosis and control of the outbreak. The common manifestations of COVID-19 include fever, cough, dyspnea, and malaise. However, patients may present with atypical symptoms that pose a diagnostic challenge. We report the first case of an elderly male who presented with rhabdomyolysis and later was diagnosed with COVID-19. Clinicians should be aware that rhabdomyolysis can be an initial presentation of COVID-19 or can occur at any time during the disease course. Patients with rhabdomyolysis should receive aggressive fluid administration to prevent acute kidney injury (AKI). However, COVID-19 patients are at risk of worsening oxygenation and acute hypoxemic respiratory failure from fluid overload. Therefore, cautious fluid administration is needed in COVID-19 patients with rhabdomyolysis.


title: Eosinopenia Phenotype in Patients with Coronavirus Disease 2019: A Multi-center Retrospective Study from Anhui, China

text: Background: Coronavirus disease 19 (COVID-19) has become a global unprecedented pandemic infecting more than one millon people, which is declared by WHO as a international public health emergency. Eosinopenia may predict a poor prognosis of COVID-19. However, to date, there is no detailed analysis of the clinical characteristics of COVID-19 patients with eosinopenia. Research question: The aim of this study was to describe clinical characteristics of COVID-19 patients with eosinopenia. Study Design and Methods: This was a multi-center retrospective study conducted in three tertiary hospitals. A total of 59 patients with COVID-19 were reviewed from January 23, 2020 to March 10, 2020. We described clincial characteristics of patients with COIVD-19 and eosinopenia phenotype. Results: The median age of patients with COVID-19 was 39 years old, and 32 (54,2%) were male. Patients with severe type had higher proportions of dyspnea (50%) and gastrointestinal symptoms (50%) compared with mild or moderate patients. Laboratory findings indicated that lower counts of lymphocyte and eosnophils were observed in patients with severe type. Cough, sputum, and fatigue were more common symptoms in eosinopenia patients compared with non-eosinopenia patients. High proportion of comorbidities was observed in eosinopenia patients. Laboratory findings indicated that lymphocyte counts (median: 101 cells/l ) in eosinopenia patients were significantly less than those of non-eosinopenia patients (median: 167 cells/l, p<0.001). The use of corticosteroids therapy in COVID-19 patients with eosinopenia were notably higher than those in patients with non-eosinopenia (50% vs 13.8%, respectively, p=0.005). Compared with parameters in non-eosinopenia patients, eosinopenia patients were more inclined to have less lymphocyte counts (OR value 6.566, 95%CI[1.101-39.173], p=0.039). Interpretation Eosinopenia are very common in COVID-19 patient, particularly in severe patients. Common symptoms included fever, cough, sputum, and fatigue are frequent in eosinopenia patients. Eosinopenia may represent a novel phenotype in COVID-19, which needs further investigation.


title: Airway management and COVID-19 patient -Saudi Anesthesia Society guidelines-

text: The Saudi Anesthesia Society (SAS) in line with the Mission and Vision of the Kingdom of Saudi Arabia to contain the new coronavirus disease (COVID-19) is pleased to develop a statement regarding airway management of suspected/confirmed patients with this virus, to ensure the safe practice in dealing with the patient as well as protecting the medical staff from getting the infection. In this report, we have summarized the guidelines necessary for airway management of suspected/confirmed COVID-19 patient. Since the COVID-19 outbreak is up to date existed, therefore this report is considered as interim guidelines for airway management of the suspected/confirmed patients. The guidelines will be revisited and modified in the future, if necessary.


The Leonardo COVID-19 Diaries


title: Epidemic Model Guided Machine Learning for COVID-19 Forecasts in the United States

text: We propose a new epidemic model (SuEIR) for forecasting the spread of COVID-19, including numbers of confirmed and fatality cases at national and state levels in the United States. Specifically, the SuEIR model is a variant of the SEIR model by taking into account the untested/unreported cases of COVID-19, and trained by machine learning algorithms based on the reported historical data. Besides providing basic projections for confirmed and fatality cases, the proposed SuEIR model is also able to predict the peak date of active cases, and estimate the basic reproduction number (R0). In particular, the forecasts based on our model suggest that the peak date of the US, New York state, and California state are 06/01/2020, 05/10/2020, and 07/01/2020 respectively. In addition, the estimated R0 of the US, New York state, and California state are 2.5, 3.6 and 2.2 respectively. The prediction results for all states in the US can be found on our project website: https://covid19.uclaml.org, which are updated on a weekly basis, and have been adopted by the Centers for Disease Control and Prevention (CDC) for COVID-19 death forecasts (https://www.cdc.gov/coronavirus/2019-ncov/covid-data/forecasting-us.html).


title: India aims to be a global hub for drug production

text: ndia’s government has approved an initiative intended to make the country a global manufacturing hub for bulk drugs and medical devices Initial funding for the project is ₹137 6 billion ($1 8 billion)—₹99 4 billion for bulk drugs and ₹38 2 billion for medical devices The announcement came after the COVID-19 pandemic shut down manufacturing facilities and exports from China, where India gets much of its supply of key starting materials, drug intermediates, and active pharmaceutical ingredients India’s effort will involve building three bulk-drug manufacturing parks in the next 5 years, each of which will have solvent recovery, distillation, and effluent treatment plants In addition, the government will pay domestic drug manufacturers a 20% bonus on sales of 53 drugs deemed critical to the country The government also plans to build four medical device manufacturing parks The initiative—which India calls a production-linked investment scheme—will be implemented by a project management agency selected by the


title: THE COVID-19 FORECAST IN NORTHWEST SYRIAThe Imperative of Global Action to Avoid Catastrophe

text: Introduction: There is limited research on how the COVD-19 pandemic will affect countries with weakened health systems and particularly those in conflict. Syria protracted conflict has strained its health systems and caused fragmentation. In this study, we focus on northwest (NW) Syria, where recent violence has driven almost one million civilians (of the 4.17 million in the area) from their homes between December 2019 and March 2020. The area is challenged by overcrowding, inadequate WASH, shelter and insufficient healthcare services. Internationally promoted measures (social distancing, self-isolation, quarantine, lockdown) are not impossible. We model outcomes, according to three scenarios, should there be a COVD-19 outbreak. We aim to: 1. Predict the numbers of cases, including severe and critical ones, and deaths. 2. Identify critical time points when the health system capacity is overwhelmed due to COVID-19. Methodology: using the WHO COVD-19 Essential Supplies Forecasting Tool (COVID-ESFT) and data from the Health Information System Unit on population and health facility capacity and utilization in northwest Syria, we generate predicted numbers of cases, deaths and health care needs according to three scenarios. Scenario One assumes a medium doubling rate (every 4 days) and a medium clinical attack rate (20% of the population). Scenario Two assumes a fast doubling rate (every 3.2 days) and a medium clinical attack rate (20% of the population). Camp-population Scenario assumes a very fast doubling rate (every 2.3 days) and a medium clinical attack rate (20% of the population). Scenarios One and Two apply to the total population of 4.17 million and for 8 weeks from the first case while Camp-population Scenario applies only to the 1.2 million internally displaced persons (IDPs) in camps and tented settlements and for 6 weeks from the first case. For each scenario, we identify critical time-points when the health system capacity is overwhelmed assuming a highly conservative estimate that 50% of regular hospital (ward) and ICU beds can be occupied by COVID-19 patients. Results: Scenario One predicts 16,384 cases (0.4% of the total population), of which 2,458 are severe and 819 are critical, and 978 deaths in the first 8 weeks. Scenario Two predicts 185,364 cases (4.4% of the population), of which 27805 are severe and 9268 are critical, and 11,066 deaths in the first 8 weeks. Camp-population Scenario predicts 240,000 cases (20% of the IDP population) of which 36,000 are severe and 12,000 are critical and 14,328 deaths in the first 6 weeks. With only 2,429 inpatient beds and 240 ICU beds (98 with adult ventilators, 62 with paediatric ventilators) in northwest Syria, ward and ICU bed capacities will be overwhelmed within 4-7 weeks. The Camp-population Scenario will see the earliest critical time-points. Conclusion and recommendations: Should a COVID-19 outbreak occur in NW Syria, projected cases and deaths will be particularly severe among IDPs. Health system capacity will be overwhelmed within a short period after the first case in camp settings. There is need for further research to account for additional variables that can impact projections. However, it is urgent for international community to mobilize efforts and resources to support community-based measures, increase testing, strengthen health system capacity.


title: The COVID-19 Spread Patterns in Italy and India: A Comparison of the Current Situations

text: Epidemiological mathematical models and time series models can be used to forecast about the spread of an infectious disease. In this article, without using such models, we are going to show how exactly the pattern evolves day by day once a pattern is seen to be approximately followed by the data. Although in Italy as well as in India the novel corona virus appeared on the same day, in Italy the spread is nearly logarithmic by now and in India it is nearly exponential even now.


title: Analytical and Clinical Comparison of Three Nucleic Acid Amplification Tests for SARS-CoV-2 Detection

text: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) was first identified in December 2019 and has quickly become a worldwide pandemic. In response, many diagnostic manufacturers have developed molecular assays for SARS-CoV-2 under the Food and Drug Administration (FDA) Emergency Use Authorization (EUA) pathway. This study compared three of these assays: the Hologic Panther Fusion SARS-CoV-2 assay (Fusion), the Hologic Aptima SARS-CoV-2 assay (Aptima) and the BioFire Diagnostics COVID-19 test (BioFire), to determine analytical and clinical performance, as well as workflow. All three assays showed a similar limit of detection (LOD) using inactivated virus, with 100% detection ranging from 500-1,000 genome equivalents/ml, whereas use of a quantified RNA transcript standard showed the same trend, but had values ranging from 62.5 to 125 copies/ml, confirming variability in absolute quantification of reference standards. The clinical correlation found that the Fusion and BioFire assays had a positive percent agreement (PPA) of 98.7%, followed by the Aptima assay at 94.7% when compared to the consensus result. All three assays exhibited 100% negative percent agreement (NPA). Analysis of discordant results revealed that all four samples missed by the Aptima assay had Ct values >37 on the Fusion assay. In conclusion, while all three assays showed similar relative LODs, we showed differences in absolute LODs depending on which standard was employed. In addition, the Fusion and BioFire assays showed better clinical performance, while the Aptima assay showed a modest decrease in overall PPA. These findings should be kept in mind when making platform testing decisions.


title: Worries and concerns among healthcare workers during the coronavirus 2019 pandemic: a web-based cross-sectional survey

text: Background: Healthcare workers (HCWs) treating and caring for patients with emerging infectious diseases often experience psychological distress. However, the psychological impact and behavior change of the coronavirus disease 2019 (COVID-19) pandemic among HCWs are still unknown. This study aimed to investigate the worries and concerns of HCWs regarding the COVID-19 pandemic. Methods: In this cross-sectional survey, a web-based questionnaire was distributed among HCWs working in hospitals or clinics across Japanese medical facilities from April 20 to May 1, 2020. The questionnaire comprised items on demographics, worries and concerns, perceptions regarding the sufficiency of information, and behavioral changes pertaining to the COVID-19 pandemic. Results: A total of 4386 HCWs completed the survey; 1648 (64.7%) were aged 30-39 years, 2379 (54.2%) were male, and 782 (18.1%) were frontline HCWs, directly caring for patients with COVID-19 on a daily basis. 3500 HCWs (79.8%) indicated that they were seriously worried about the pandemic. The most frequent concern was the consequence of becoming infected on their family, work, and society (87.4%). Additionally, the majority (55.5%) had restricted social contact and almost all HCWs endorsed a shortage in personal protective equipment (median, 8/9 (interquartile range; 7-9) on a Likert scale). There was no significant difference in the degree of worry between frontline and non-frontline HCWs (8/9 (7-9) vs. 8/9 (7-9), p=0.25). Frontline HCWs, compared to non-frontline HCWs, were more likely to have the need to avoid contact with families and friends (24.8% vs. 17.8%, p<0.001) and indicated that they cannot evade their professional duty during the COVID-19 pandemic (9/9 (7-9) vs. 8/9 (6-9), p<0.001). Further, the extremely low proportion of frontline HCWs reported that they would take a leave of absence to avoid infection (1.2%). Conclusions: Both frontline and non-frontline HCWs expressed comparable concerns regarding the COVID-19 pandemic. Because HCWs, especially frontline HCWs, reported that they cannot be obliged to do avoid their duty, effective mental health protection strategies should be developed and implemented for HCWs.


title: Covid-19 infection after recent heart transplantation: A case report

text: History of heart transplantation in combination with immunosuppressive therapy and acute viral respiratory infection overlay makes the patient difficult to manage. In case of COVID-19, the setting is complicated by unknown pathogenesis, including its effect on blood, coagulation system, and lung tissue. Current case report discusses the 60-year-old patient with a COVID-19 infection occurred in the immediate postoperative period after heart transplantation.


title: Quality monitoring in milling of unidirectional CFRP through wavelet packet transform of force signals

text: Abstract Machining of CFRP is challenging and necessitates efficient and robust process monitoring techniques to minimize the machining induced damage such as fiber pullouts and delamination. In this study, wavelet packet transform of forces signals was used to monitor the surface quality of CFRP subjected to conventional edge trimming. Conventional milling experiments were performed on unidirectional CFRP machined at differ fiber orientation angles - 0°, 45°, 90° and 135°. The feed rate was varied between 0.025 and 0.75 mm/tooth. Depending on the fiber orientation, the ten point average roughness Rz varied between 2.9 and 104.1 µm. A novel algorithm using Wavelet Packet Decomposition was proposed to identify the signal features that could effectively establish a correlation between signal features, process variables (feed and speed) and surface roughness Rz. A bank of 35 different mother wavelets with decomposition levels up to 10 was explored. Seven different features were calculated for the wavelet packets obtained upon decomposition. Optimal wavelet parameters were identified based on the regression statistics. Among others, two features – standard deviation and energy-entropy coefficient were identified as primary candidates which resulted in roughness prediction with R2>91%. In addition, the morphology and removal mechanisms of the machined surfaces was examined using scanning electron microscopy. The nexus between those surfaces and signals was established which corroborated the utility of the proposed algorithm.


title: Functional prediction and comparative population analysis of variants in genes for proteases and innate immunity related to SARS-CoV-2 infection

text: New coronavirus SARS-CoV-2 is capable to infect humans and cause a novel disease COVID-19. Aiming to understand a host genetic component of COVID-19, we focused on variants in genes encoding proteases and genes involved in innate immunity that could be important for susceptibility and resistance to SARS-CoV-2 infection. Analysis of sequence data of coding regions of FURIN, PLG, PRSS1, TMPRSS11a, MBL2 and OAS1 genes in 143 unrelated individuals from Serbian population identified 22 variants with potential functional effect. In silico analyses (PolyPhen-2, SIFT, MutPred2 and Swiss-Pdb Viewer) predicted that 10 variants could impact the structure and/or function of proteins. These protein-altering variants (p.Gly146Ser in FURIN; p.Arg261His and p.Ala494Val in PLG; p.Asn54Lys in PRSS1; p.Arg52Cys, p.Gly54Asp and p.Gly57Glu in MBL2; p.Arg47Gln, p.Ile99Val and p.Arg130His in OAS1) may have predictive value for inter-individual differences in the response to the SARS-CoV-2 infection. Next, we performed comparative population analysis for the same variants using extracted data from the 1000 genomes project. Population genetic variability was assessed using delta MAF and Fst statistics. Our study pointed to 7 variants in PLG, TMPRSS11a, MBL2 and OAS1 genes with noticeable divergence in allelic frequencies between populations worldwide. Three of them, all in MBL2 gene, were predicted to be damaging, making them the most promising population-specific markers related to SARS-CoV-2 infection. Comparing allelic frequencies between Serbian and other populations, we found that the highest level of genetic divergence related to selected loci was observed with African, followed by East Asian, Central and South American and South Asian populations. When compared with European populations, the highest divergence was observed with Italian population. In conclusion, we identified 4 variants in genes encoding proteases (FURIN, PLG and PRSS1) and 6 in genes involved in the innate immunity (MBL2 and OAS1) that might be relevant for the host response to SARS-CoV-2 infection.


title: Predicting the disease outcome in COVID-19 positive patients through Machine Learning: a retrospective cohort study with Brazilian data

text: The first officially registered case of COVID-19 in Brazil was on February 26, 2020. Since then, the situation has worsened with more than 672,000 confirmed cases and at least 36,000 reported deaths at the time of this writing. Accurate diagnosis of patients with COVID-19 is extremely important to offer adequate treatment, and avoid overloading the healthcare system. Characteristics of patients such as age, comorbidities and varied clinical symptoms can help in classifying the level of infection severity, predict the disease outcome and the need for hospitalization. Here, we present a study to predict a poor prognosis in positive COVID-19 patients and possible outcomes using machine learning. The study dataset comprises information of 13,690 patients concerning closed cases due to cure or death. Our experimental results show the disease outcome can be predicted with a ROC AUC of 0.92, Sensitivity of 0.88 and Specificity of 0.82 for the best prediction model. This is a preliminary retrospective study which can be improved with the inclusion of further data. Conclusion: Machine learning techniques fed with demographic and clinical data along with comorbidities of the patients can assist in the prognostic prediction and physician decision-making, allowing a faster response and contributing to the non-overload of healthcare systems.


title: Application of a Gray-Based Decision Support Framework for Location Selection of a Temporary Hospital during COVID-19 Pandemic

text: The hospital location selection problem is one of the most important decisions in the healthcare sector in big cities due to population growth and the possibility of a high number of daily referred patients A poor location selection process can lead to many issues for the health workforce and patients, and it can result in many unnecessary costs for the healthcare systems The COVID-19 outbreak had a noticeable effect on people’s lives and the service quality of hospitals during recent months The hospital location selection problem for infected patients with COVID-19 turned out to be one of the most significant and complicated decisions with many uncertain involved parameters for healthcare sectors in countries with high cases In this study, a gray-based decision support framework using criteria importance through inter-criteria correlation (CRITIC) and combined compromise solution (CoCoSo) methods is proposed for location selection of a temporary hospital for COVID-19 patients A case study is performed for Istanbul using the proposed decision-making framework


title: Ken Hyland Second Language Writing

text: Unknown


title: Antiviral activity of Glucosylceramide synthase inhibitors against SARS-CoV-2 and other RNA virus infections

text: The need for antiviral drugs is real and relevant. Broad spectrum antiviral drugs have a particular advantage when dealing with rapid disease outbreaks, such as the current COVID-19 pandemic. Since viruses are completely dependent on internal cell mechanisms, they must cross cell membranes during their lifecycle, creating a dependence on processes involving membrane dynamics. Thus, in this study we examined whether the synthesis of glycosphingolipids, biologically active components of cell membranes, can serve as an antiviral therapeutic target. We examined the antiviral effect of two specific inhibitors of GlucosylCeramide synthase (GCS); (i) Genz-123346, an analogue of the FDA-approved drug Cerdelga®, (ii) GENZ-667161, an analogue of venglustat which is currently under phase III clinical trials. We found that both GCS inhibitors inhibit the replication of four different enveloped RNA viruses of different genus, organ-target and transmission route: (i) Neuroinvasive Sindbis virus (SVNI), (ii) West Nile virus (WNV), (iii) Influenza A virus, and (iv) SARS-CoV-2. Moreover, GCS inhibitors significantly increase the survival rate of SVNI-infected mice. Our data suggest that GCS inhibitors can potentially serve as a broad-spectrum antiviral therapy and should be further examined in preclinical and clinical trial. Analogues of the specific compounds tested have already been studied clinically, implying they can be fast-tracked for public use. With the current COVID-19 pandemic, this may be particularly relevant to SARS-CoV-2 infection. One Sentence Summary An analogue of Cerdelga®, an FDA-approved drug, is effective against a broad range of RNA-viruses including the newly emerging SARS-CoV-2.


Immunized camels and COVID-19


title: Mass Spectrometric Identification of SARS-CoV-2 Proteins from Gargle Solution Samples of COVID-19 Patients

text: Mass spectrometry (MS) can deliver valuable diagnostic data that complements genomic information and allows us to increase our current knowledge of the COVID-19 disease caused by the SARS-CoV-2 virus. We developed a simple, MS-based method to specifically detect SARS-CoV-2 proteins from gargle solution samples of COVID-19 patients. Our protocol consists of an acetone precipitation and tryptic digestion of proteins contained within the gargle solution, followed by a targeted MS analysis. Our methodology identifies unique peptides originating from SARS-CoV-2 nucleoprotein. Building on these promising initial results, faster MS protocols can now be developed as routine diagnostic tools for COVID-19 patients. Graphical Abstract Image credit (left): Gerd Altmann, Pixabay License, https://pixabay.com/illustrations/corona-coronavirus-virus-covid-19-4959447


title: RNA secondary structure packages ranked and improved by high-throughput experiments

text: The computer-aided study and design of RNA molecules is increasingly prevalent across a range of disciplines, yet little is known about the accuracy of commonly used structure prediction packages in real-world tasks. Here, we evaluate the performance of current packages using EternaBench, a dataset comprising 23 in vitro structure mapping and 11 riboswitch activity datasets involving 18,509 synthetic sequences from the crowdsourced RNA design project Eterna. We find that CONTRAfold and RNAsoft, packages with parameters derived through statistical learning, achieve consistently higher accuracy than more widely used packages like the ViennaRNA software, which derive parameters primarily from thermodynamic experiments. Motivated by these results, we develop a multitask-learning-based model, EternaFold, which demonstrates improved performance that generalizes to diverse external datasets, including complete viral genomes probed in vivo and synthetic designs modeling mRNA vaccines.


title: Acalculous Acute Pancreatitis in a COVID-19 Patient

text: Coronavirus disease 2019 (COVID-19) is a multisystemic condition caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with manifestations ranging from mild upper respiratory symptoms to cytokine storm causing acute respiratory distress syndrome. Pancreatic exocrine tissue and endocrine islets both express angiotensin-converting enzyme 2 (ACE2), the proven receptor for SARS-CoV-2 cell internalization. An increase in pancreatic enzymes has been increasingly recognized in patients with COVID-19, but little is known about the real prevalence of acute pancreatitis in this population. We report a case of acute acalculous pancreatitis in a COVID-19 patient. LEARNING POINTS: Acute pancreatitis may be a manifestation of SARS-CoV-2 infection. Future studies must address the real impact of pancreatic involvement in COVID-19 patients.


title: Celebrex adjuvant therapy on COVID-19: An experimental study

text: Background: The world is under serious threat with the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19). However, there is no effective drug for the treatment of COVID-19. Based on analyses of available data, we deduced that the excessive prostaglandins E2 (PGE2) accumulation mediated by cyclooxygenase-2 (COX-2) was the key pathological basis of COVID-19. Methods: The urine PGE2 levels were measured by mass spectrometry. An experimental study about Celebrex to treat COVID-19 was conducted based on routine treatment. A total of 44 confirmed COVID-19 patients were enrolled (Experimental group n=37, Control group n=7). Patients in experimental group were given Celebrex once or twice a day (0.2 g/time) for 7-14 days. The dosage or duration was modified for individuals. Clinical outcomes of Celebrex adjuvant therapy were evaluated by vital signs, laboratory tests, and computed tomography upon the discontinuance of Celebrex. Results: We found that the concentrations of PGE2 in urine samples of COVID-19 patients were significantly higher than that of healthy individuals (mean value is 170 ng/ml vs 18.8 ng/ml, p<0.01) and positively correlated with the progression of COVID-19. Among the experimental group (ordinary n=29, severe n=7, critical n=1), 25 cases were treated with full dose and 11 cases with half dose of Celebrex, and 1 case with Ibuprofen. The remission rate were 100%, 82% and 57% in full dose, half dose and control group respectively. Celebrex significantly reduced the PGE2 levels and promoted recovery of ordinary or severe COVID-19. Conclusion: Our study suggests that Celebrex adjuvant treatment may be helpful for the therapy of COVID-19.


title: SARS pandemic exposure impaired early childhood development: A lesson for COVID-19

text: Social and mental stressors associated with the COVID-19 pandemic may promote long-term effects on child development. However, reports aimed at identifying the relationship between pandemics and child health are limited. We conducted a retrospective study to evaluate the severe acute respiratory syndrome (SARS) pandemic in 2003 and its relationship to child development indicators using a representative sample across China. Our study involved longitudinal measurements of 14,647 children, 36% of whom (n = 5216) were born before or during the SARS pandemic. Cox models were utilized to examine the effects of SARS on preterm birth and four milestones of development: age to (1) walk independently, (2) say a complete sentence, (3) count from 0 to 10, and (4) undress him/herself for urination. Mixed effect models were utilized to associate SARS with birthweight, body weight and height. Our results show that experiencing SARS during early childhood was significantly associated with delayed milestones, with adjusted hazard ratios of 3.17 [95% confidence intervals (CI): 2.71, 3.70], 3.98 (3.50, 4.53), 4.96 (4.48, 5.49), or 5.57 (5.00, 6.20) for walking independently, saying a complete sentence, counting from 0 to 10, and undressing him/herself for urination, respectively. Experiencing SARS was also associated with reduced body weight. This effect was strongest for preschool children [a weight reduction of 4.86 (0.36, 9.35) kg, 5.48 (-0.56, 11.53) kg or 5.09 (-2.12, 12.30) kg for 2, 3, 4 year-olds, respectively]. We did not identify a significant effect of maternal SARS exposure on birthweight or gestational length. Collectively, our results showed that the SARS pandemic was associated with delayed child development and provided epidemiological evidence to support the association between infectious disease epidemics and impaired child health. These results provide a useful framework to investigate and mitigate relevant impacts from the COVID-19 pandemic.


title: The Early Food Insecurity Impacts of COVID-19

text: Background COVID-19 has disrupted food access and impacted food insecurity, which is associated with numerous adverse individual and public health outcomes. Methods We conducted a statewide population-level survey in Vermont from March 29-April 12, 2020, during the beginning of a statewide stay-at-home order. We utilized the USDA six-item validated food security module to measure food insecurity before COVID-19 and since COVID-19. We assessed food insecurity prevalence and reported food access challenges, coping strategies, and perceived helpful interventions among food secure, consistently food insecure (pre-and post COVID-19), and newly food insecure (post COVID-19) respondents. Results Among 3,219 respondents, there was a 33% increase in household food insecurity since COVID-19 (p<0.001), with 35.6% of food insecure households classified as newly food insecure. Respondents experiencing a job loss were more likely to experience food insecurity (OR 3.43; 95% CI, 2.45-4.80). Multiple physical and economic barriers, as well as concerns related to food access during COVID-19, are reported, with respondents experiencing household food insecurity more likely to face access challenges (p<0.001). Significant differences in coping strategies were documented between respondents in newly food insecure vs. consistently insecure households. Conclusions Since the declaration of the COVID-19 pandemic, there has been a significant increase in food insecurity in Vermont, accompanied by major food access barriers. These findings have important potential impacts on individual health, including mental health and malnutrition, as well as on future healthcare costs. We suggest proactive strategies to address food insecurity during this crisis.


title: Translational adaptation of human viruses to the tissues they infect

text: Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of over 500 human-infecting viruses and determine that tropism explains changes in codon usage. Using an in silico model of translational efficiency, we validate the correspondence of the viral codon usage with the translational machinery of their tropism. In particular, we propose that the improved translational adaptation to the upper respiratory airways of the pandemic agent SARS-CoV-2 coronavirus could enhance its transmissibility. Furthermore, this correspondence is specifically defined in early viral proteins, as upon infection cells undergo reprogramming of tRNA pools that favors the translation of late counterparts.


title: Dynamic Response Systems of Healthcare Mask Production to COVID-19: A Case Study of Korea

text: Korea initiated a new experiment, called a dynamic response system for open democratic societies as a principle to respond to the novel coronavirus (COVID-19) The global pandemic of COVID-19 led to a surge in demand for healthcare medical masks and respirators, and strained the global supply chain of mask production and distribution systems This study provides a systemic view of critical personal protective equipment for both healthcare staff and the public to stop the spread of COVID-19 This study investigates the dynamic response system of healthcare mask production to the coronavirus and discusses lessons learned in view of systems thinking The study shows that it is critical to developing a quick and dynamic response system to the evolving market conditions with flexible and agile operations Visibility with transparency with information sharing with the public is also critical under global pandemic Due to the shortage of mask supply, smart consumption is required along with collaboration with public and private sectors, as well as global organizations Democratic leadership and a well-prepared strategic plan for long-term period are essential to the open society to prepare the global pandemic in the future This study serves as a benchmark for dynamic and timely responses to the global pandemic


title: Indian communitys Knowledge, Attitude & Practice towards COVID-19

text: As COVID-19 pandemic has caused unprecedented human health consequences. Knowledge, attitude, perception of general population of India towards the transmission and prevention plays vital role for effective control measures. The study was conducted to assess the knowledge, attitude and practice of the general public of India on COVID-19. In this study, a web-based cross-sectional survey was conducted between 10th March to 18th April 2020. A 19-item questionnaire was generated, Cronbachs alpha was used to measure the internal consistency of the questionnaire & randomly distributed among the public using Google forms through social media networks. The chi-square test or Fischer exact test was used to compare categorical data and multiple linear regression was used to identify factor influencing KAP. Among 7978 participants, the overall knowledge, attitude and practice score was 80.64%, 97.33% and 93.8% consecutively. Majority of Indian population demonstrated preceded good knowledge, positive attitude and good practice regarding COVID-19 pandemic.


title: Fatal toxicity of chloroquine or hydroxychloroquine with metformin in mice

text: Guided by the principle of primum non nocere (first do no harm), we report a cautionary note on the potential fatal toxicity of chloroquine (CQ) or hydroxychloroquine (HCQ) in combination with anti-diabetic drug metformin. We observed that the combination of CQ or HCQ and metformin, which were used in our studies as potential anti-cancer drugs, killed 30-40% of mice. While our observations in mice may not translate to toxicity in humans, the reports that CQ or HCQ has anti-COVID-19 activity, the use of CQ resulting in toxicity and at least one death, and the recent Emergency Use Authorization (EUA) for CQ and HCQ by the US Food and Drug Administration (FDA) prompted our report. Here we report the lethality of CQ or HCQ in combination with metformin as a warning of its potential serious clinical toxicity. We hope that our report will be helpful to stimulate pharmacovigilance and monitoring of adverse drug reactions with the use of CQ or HCQ, particularly in combination with metformin.


title: Transcriptional response of signalling pathways to SARS-CoV-2 infection in normal human bronchial epithelial cells

text: SARS-CoV-2 virus, the pathogen that causes Covid-19 disease, emerged in Wuhan region in China in 2019, infected more than 4M people and is responsible for death of at least 300K patients globally as of May 2020. Identification of the cellular response mechanisms to viral infection by SARS-CoV-2 may shed light on progress of the disease, indicate potential drug targets, and make design of new test methods possible. In this study, we analysed transcriptomic response of normal human bronchial epithelial cells (NHBE) to SARS-CoV-2 infection and compared the response to H1N1 infection. Comparison of transcriptome of NHBE cells 24 hours after mock-infection and SARS-CoV-2 infection demonstrated that most genes that respond to infection were upregulated (320 genes) rather than being downregulated (115 genes).While upregulated genes were enriched in signalling pathways related to virus response, downregulated genes are related to kidney development. We mapped the upregulated genes on KEGG pathways to identify the mechanisms that mediate the response. We identified canonical NFκB, TNF and IL-17 pathways to be significantly upregulated and to converge to NFκB pathway via positive feedback loops. Although virus entry protein ACE2 has low expression in NHBE cells, pathogen response pathways are strongly activated within 24 hours of infection. Our results also indicate that immune response system is activated at the early stage of the infection and orchestrated by a crosstalk of signalling pathways. Finally, we compared transcriptomic SARS-CoV-2 response to H1N1 response in NHBE cells to elucidate the virus specificity of the response and virus specific extracellular proteins expressed by NHBE cells.


title: Geometric simulation of power skiving of internal gear using solid model with triple-dexel representation

text: Abstract Gear manufacturing is a fundamental technology for machine production. Power skiving has rapidly become an efficient method for the manufacturing of internal high-precision gears. To analyze the cutting force during power skiving, a geometric simulation of the power skiving process, particularly a visualization of the resulting machining shape and a prediction of the chip geometry generated during the cutting process, is important. In this study, we propose a novel method for precisely simulating the power skiving process using solid modeling. The resulting shape of power skiving is computed by repeatedly subtracting the swept volume of the cutting edge from a solid model of the workpiece. To realize a robust computation in a subtraction operation, a solid model with triple-dexel representation is used to represent the workpiece shape. To accelerate the operations, the parallel processing function of a graphics processing unit (GPU) is used. An experimental simulation system is implemented, and some computational experiments are conducted.


The impact of Covid-19 pandemic on plastic reconstructive and aesthetic surgery practice


title: Soft Skills On-Line Development in Times of Crisis

text: While the 21st century is typified with constant change, over the past few months, with the break of the COVID-19, the world is undergoing tremendous changes at a pace and magnitude that have not been seen before It has been argued that coping and succeeding in the changing reality of the 21st century globally requires a wider set of skills than before, many of which are soft, social-emotional skills This is particularly true in the uncertainly of the current times worldwide Incorporating the development of soft skills in the current academic systems, which still hold a mainly cognitive focus has been found challenging and efforts are relatively scarce and isolated This is becoming even more challenging as the current situation has forced the academy to adapt quickly to digital teaching methods and the use of various platforms for E learning Aim: to presents a unique method and tool for cultivating soft skills in students, which can be integrated in the general curriculum through digital and E learning Method: presenting the theoretical basis of the model and exemplifying the ways it can be used in different subjects and as part of higher education institutions (HEI) strategy Result: although pilot studies are still undergoing, it is believed that integrating soft skills development using online learning and linking them to course subjects will help HEI to stay relevant in a changing world and fulfil their role in preparing students to the 21st century reality, in the times of the recent health crisis COVID-19 and beyond


title: A Systematic Review of the Digital Interventions for Fighting COVID-19: The Bangladesh Perspective

text: The objective of this paper is to synthesize the digital interventions initiatives to fight against COVID-19 in Bangladesh and compare with other countries. In order to obtain our research objective, we conducted a systematic review of the online content. We first reviewed the digital interventions that have been used to fight against COVID-19 across the globe. We then reviewed the initiatives that have been taken place in Bangladesh. Thereafter, we present a comparative analysis between the initiatives taken in Bangladesh and the other countries. Our findings show that while Bangladesh is capable to take benefits of the digital intervention approaches, tighter cooperation between government and private organizations as well as universities would be needed to get the most benefits. Furthermore, the government needs to make sure that the privacy of its citizens are protected.


title: Optimal Control applied to a SEIR model of 2019-nCoV with social distancing

text: Does the implementation of social distancing measures have merit in controlling the spread of the novel coronavirus? In this study, we develop a mathematical model to explore the effect of social distancing on new disease infections. Mathematical analyses of our model indicate that successful eradication of the disease is strongly dependent on the chosen preventive measure. Numerical computations of the model solution demonstrate that the ability to flatten the curve becomes easier as social distancing is strictly enforced. Based on our model, we also formulate an optimal control problem and solve it using Pontryagin's Maximum Principle and an efficient numerical iterative method. Our numerical results of an optimal 2019-nCoV treatment protocol that yields a minimum disease burden from this disease indicates that social distancing is vitally important.


title: Simulating and Forecasting the Cumulative Confirmed Cases of SARS-CoV-2 in China by Boltzmann Function-based Regression Analyses

text: An ongoing outbreak of atypical pneumonia caused by the 2019 novel coronavirus (SARS-CoV-2) is hitting Wuhan City and has spread to other provinces/cities of China and overseas. It very urgent to forecast the future course of the outbreak. Here, we provide an estimate of the potential total number of confirmed cases in mainland China by applying Boltzmann-function based regression analyses. We found that the cumulative number of confirmed cases from Jan 21 to Feb 14, 2020 for mainland China, Hubei Province, Wuhan City and other provinces were all well fitted with the Boltzmann function (R2 being close to 0.999). The potential total number of confirmed cases in the above geographic regions were estimated at 95% confidence interval (CI) as 79589 (71576, 93855), 64817 (58223, 77895), 46562 (40812, 57678) and 13956 (12748, 16092), respectively. Notably, our results suggest that the number of daily new confirmed cases of SARS-CoV-2 in mainland China (including Hubei Province) will become minimal between Feb 28 and Mar 10, 2020, with 95% CI. In addition, we found that the data of cumulative confirmed cases of 2003 SARS-CoV in China and Worldwide were also well fitted to the Boltzmann function. To our knowledge this is the first study revealing that the Boltzmann function is suitable to simulate epidemics. The estimated potential total number of confirmed cases and key dates for the SARS-CoV-2 outbreak may provide certain guidance for governments, organizations and citizens to optimize preparedness and response efforts.


title: Characterizing occupations that cannot work from home: a means to identify susceptible worker groups during the COVID-19 pandemic

text: Introduction As the COVID-19 pandemic spreads globally, public health guidance is advising all workers to work from home. However, not all workers are employed in occupations which can be done from home. These workers are at an increased risk for exposure to SARS-CoV-2due to increased interaction with the public and other workers, and also potentially at an increased risk for job displacement as more extreme public health measures (such as closing of retail operations or enforcing shelter in place) occur. Methods To characterize the occupations least likely to be able to work from home, national employment and wage data maintained by the United States Bureau of Labor Statistics (BLS) was merged with measures from the BLS O*NET survey data, which ranks occupations by a variety of physical, ergonomic, psychosocial, and structural exposures. Noting that the work that could most easily be done at home would be work done on a computer that does not rely on interaction with the public, O*NET measures quantifying the importance of computer use at work, and the importance of working with or performing for the public at work were utilized. Results From this analysis, 19.5% (28.2 M) of the United States workforce covered by O*NET are employed in occupations where working from home would be difficult, due to minimal use of computer at work, and a high level of interaction with the public. These workers tend to be in service occupations, including retail and food service, protective service occupations, and transportation occupations such as bus drivers. About 25% (35.6 M) of the United States workforce covered by O*NET are employed in occupations where working from home could likely be more easily accommodated, as these workers do much of their work on computers and interaction with the public is not important. These workers tend to be in technology, computer, management, administrative, financial, engineering, and some science occupations, which typically have higher pay than occupations which cannot be done at home. Conclusions The workers in occupations that have minimal computer use, and high interaction with the public are least likely to be able to work from home during a public health emergency. These workers could also be at an increased risk for job displacement if public-facing establishments close or alter their business model in the face of increased public health restrictions. Occupations where working from home is not possible tend to have lower annual median incomes than occupations where working from home is possible, increasing the vulnerability of these workers. Characterizing which occupational groups are least likely to be able to work from home can inform public health risk management and prioritize occupational sectors where additional workplace protections are necessary.


title: Epidemiological study to detect active SARS-CoV-2 infections and seropositive persons in a selected cohort of employees in the Frankfurt am Main metropolitan area

text: So far, 170,000 Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) infections have been confirmed in Germany, of which more than 5,000 have been detected in the Frankfurt am Main metropolitan region. When examining 1,000 nasopharyngeal swabs and serum samples from healthy volunteers from this region, one RT-PCR-positive and five antibody-positive persons were identified. The five positive serum samples were confirmed to be specific. Four of the five positive sera cross-neutralized SARS-CoV.


title: BCG VACCINES MAY NOT REDUCE COVID-19 MORTALITY RATES

text: The reason for the observed country-wise variability in incidence and severity of the COVID-19 outcome remains unknown. Few recent studies have suggested a positive protective correlation of the BCG vaccination policy of the countries with the observed COVID-19 severity. The current study was undertaken to reassess the existing data as of 4th April 2020. The incidence rates (cases per million population), Case Fatality Rates (CFR) and inherently more robust Infection Fatality Rates (IFR) were calculated across countries accounting for about 99% COVID-19 deaths. The initial scrutiny suggested a weaker association with BCG vaccination policy or BCG coverage, so positivity to the Tuberculin Sensitivity Test (TST)/ Interferon Gamma Release Assay (IGRA) as a measure of the potential protective effect of the resident populations exposure to Mycobacterium spp. whether from BCG vaccination or as a result of exposure to environmental mycobacteria was analyzed. The incidence rates (the number of cases per million population) decreased with an increase in % LTBI (TST/IGRA positivity) for the analyzed countries with R2 =0.6343, suggesting an exponentially negative covariation. However, the covariation of CFR estimates that ranged from 0.29% to 12.25 % (average 5.39%) among countries, was tenuous. Interim estimates of IFR (i-IFR), a more dependable measure for such studies, for the best and worst-case scenarios, i.e., i-IFR-l and i-IFR-h, predict on an average 20.57% to 30.15 % COVID-19 fatality rates globally, but individual country estimates display huge variation. Among countries accounting for 92.14% deaths (11 countries; top 20% countries included in current study) the estimate for lowest IFRs (i-IFR-l=4.16 (China) & i-IFR-h=4.61 (China)) and highest IFRs (i-IFR-l=96.39% (UK); & i-IFR-h=96.54% (UK)) displayed huge difference (average for the group: CFR=6.8 ± 3.6%; i-IFR-l=34.97 ± 30.55%; & i-IFR-h=44.20 ± 29.08%). Currently, the worst affected countries Italy (CFR=12.25%; i-IFR-l=42.63%; i-IFR-h=48.69%) and Spain (CFR=9.39%; i-IFR-l=26.85%; i-IFR-h=36.60%) would seemingly cope with COVID-19 better than UK, Netherlands and USA while the countries Germany (CFR=1.40%; i-IFR-l=4.93%; i-IFR-h=17.49%) and Switzerland (CFR=3.01%; i-IFR-l=10.87%; i-IFR-h=16.23%) along with China could fare the best. The rest of the 80% countries (accounting for 6.74% deaths), seemed to have reduced mortality (CFR=2.45 ± 2.01; i-IFR-l= 30.62 ± 28.24%; i-IFR-h=40.99 ± 30.47%) with associated high % LTBI (17.28 ± 8.87) than top 20% countries. The inherent issues in the data set (e.g., heterogeneity, non-random sampling, different criteria of sampling and reporting, access to health care, genetic composition, underlying co-morbidities, etc) need to be taken into account for making informed decisions.


title: SARS-CoV-2 titers in wastewater are higher than expected from clinically confirmed cases

text: Wastewater surveillance may represent a complementary approach to measure the presence and even prevalence of infectious diseases when the capacity for clinical testing is limited. Moreover, aggregate, population-wide data can help inform modeling efforts. We tested wastewater collected at a major urban treatment facility in Massachusetts and found the presence of SARS-CoV-2 at high titers in the period from March 18 - 25 using RT-qPCR. We then confirmed the identity of the PCR product by direct DNA sequencing. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of March 25. The reason for the discrepancy is not yet clear, however, and until further experiments are complete, these data do not necessarily indicate that clinical estimates are incorrect. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks.


Corona virus disease 2019 in infant: Case report/ 婴儿新型冠状病毒肺炎1例


title: RNA structure prediction using positive and negative evolutionary information

text: Knowing the structure of conserved structural RNAs is important to elucidate their function and mechanism of action. However, predicting a conserved RNA structure remains unreliable, even when using a combination of thermodynamic stability and evolutionary covariation information. Here we present a method to predict a conserved RNA structure that combines the following three features. First, it uses significant covariation due to RNA structure and removes spurious covariation due to phylogeny. Second, it uses negative evolutionary information: basepairs that have variation but no significant covariation are prevented from occurring. Lastly, it uses a battery of probabilistic folding algorithms that incorporate all positive covariation into one structure. The method, named CaCoFold (Cascade variation/covariation Constrained Folding algorithm), predicts a nested structure guided by a maximal subset of positive basepairs, and recursively incorporates all remaining positive basepairs into alternative helices. The alternative helices can be compatible with the nested structure such as pseudoknots, or overlapping such as competing structures, base triplets, or other 3D non-antiparallel interactions. We present evidence that CaCoFold predictions are consistent with structures modeled from crystallography. Author Summary The availability of deeper comparative sequence alignments and recent advances in statistical analysis of RNA sequence covariation have made it possible to identify a reliable set of conserved base pairs, as well as a reliable set of non-basepairs (positions that vary without covarying). Predicting an overall consensus secondary structure consistent with a set of individual inferred pairs and non-pairs remains a problem. Current RNA structure prediction algorithms that predict nested secondary structures cannot use the full set of inferred covarying pairs, because covariation analysis also identifies important non-nested pairing interactions such as pseudoknots, base triples, and alternative structures. Moreover, although algorithms for incorporating negative constraints exist, negative information from covariation analysis (inferred non-pairs) has not been systematically exploited. Here I introduce an efficient approximate RNA structure prediction algorithm that incorporates all inferred pairs and excludes all non-pairs. Using this, and an improved visualization tool, I show that the method correctly identifies many non-nested structures in agreement with known crystal structures, and improves many curated consensus secondary structure annotations in RNA sequence alignment databases.


title: SARS-CoV-2 Infection in Pregnancy – a Review of the Current Literature and Possible Impact on Maternal and Neonatal Outcome

text: In December 2019, cases of pneumonia of unknown cause first started to appear in Wuhan in China; subsequently, a new coronavirus was soon identified as the cause of the illness, now known as Coronavirus Disease 2019 (COVID-19). Since then, infections have been confirmed worldwide in numerous countries, with the number of cases steadily rising. The aim of the present review is to provide an overview of the new severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) and, in particular, to deduce from it potential risks and complications for pregnant patients. For this purpose, the available literature on cases of infection in pregnancy during the SARS epidemic of 2002/2003, the MERS (Middle East respiratory syndrome) epidemic ongoing since 2012, as well as recent publications on cases infected with SARS-CoV-2 in pregnancy are reviewed and reported. Based on the literature available at the moment, it can be assumed that the clinical course of COVID-19 disease may be complicated by pregnancy which could be associated with a higher mortality rate. It may also be assumed at the moment that transmission from mother to child in utero is unlikely. Breastfeeding is possible once infection has been excluded or the disease declared cured.


title: Chloroquine and hydroxychloroquine as ACE2 blockers to inhibit viropexis of COVID-19 Spike pseudotype virus

text: The pandemic coronavirus COVID-19 affected global health from the end of 2019 to 2020 and may challenge global health in the future. There have been reports of Chloroquine (CQ) and Hydroxychloroquine (HCQ) used in clinical treatment. In our study, we used CCK-8 stain, flow cytometry and immunofluorescent stain to evaluated the toxicity and autophagy of CQ and HCQ respectively on ACE2 high expressed HEK293T cells (ACE2hi cells). We further analysied the binding character of CQ and HCQ to ACE2 by molecular docking, surface plasmon resonance (SPR) assays and molecule docking, COVID-19 spike pseudotype virus was also taken to investigate the suppression viropexis effect of CQ and HCQ. Results showed that HCQ is slightly more toxic to ACE2hi cells than CQ, both CQ and HCQ could bind to ACE2, and they also exhibit equivalent suppression effect for the entrance of COVID-19 Spike pseudotype virus into ACE2hi cells. Our finding provides a theoretical and experimental basis for the clinical treatment of CQ and HCQ for COVID-19.


title: Cross-reaction of sera from COVID-19 patients with SARS-CoV assays.

text: Background: The SARS-CoV-2 shares 74.5% genome identity with SARS-CoV, both exhibiting a similar well conserved structure. Therefore, antibodies produced in COVID-19 and SARS patients should not be that dissimilar. We evaluated SARS-CoV test assays to detect for the presence of antibodies to SARS-CoV-2 and tried to determine the timing of appearance of these antibodies by testing serial sera from these patients. Methods: Tests were carried out using ELISA (total antibodies) and indirect immunofluorescence (IIFA) (IgM & IgG) methods on serial sera from patients confirmed with SARS-CoV-2 infection. Results: Cross-reactivity was seen in these two test assays with sera from COVID-19 patients and was detected in 6 out of 7 patients from 7 days after onset of symptoms. Five of the patients had detectable antibodies by the 3rd week into their illness and there was evidence of seroconversion in 4 patients. The IIFA method was marginally more sensitive compared to the ELISA assay, however the IIFA IgM test was not useful in the early phase of the illness with poor sensitivity. Conclusions: Existing diagnostic assays for SARS-CoV can detect antibodies in patients who were diagnosed with COVID-19. These assays maybe be utilized as an interim measure in epidemiological investigations for contact tracing and to determine the extent of community spread of this new emerging virus pending the availability of specific serology tests for SARS-CoV-2.


title: Periodic COVID-19 Testing in Emergency Department Staff

text: Background: As the number of COVID-19 cases in the US continues to rise and hospitals are experiencing personal protective equipment (PPE) shortages, healthcare workers have been disproportionately affected by COVID-19 infection. Since COVID-19 testing is now available, some have raised the question of whether we should be routinely testing asymptomatic healthcare workers. Methods: Using publicly available data on COVID-19 infections and emergency department visits, as well as internal hospital staffing information, we generated a mathematical model to predict the impact of periodic COVID-19 testing in asymptomatic members of the emergency department staff in regions affected by COVID-19 infection. We calculated various transmission constants based on the Diamond Princess cruise ship data, used a logistic model to calculate new infections, and we created a Markov model according to average COVID-19 incubation time. Results: Our model predicts that after 30 days, with a transmission constant of 1.219e-4 new infections per person2, weekly COVID-19 testing of healthcare workers (HCW) would reduce new HCW and patient infections by 5.1% and bi-weekly testing would reduce both by 2.3%. At a transmission constant of 3.660e-4 new infections per person,2 weekly testing would reduce infections by 21.1% and bi-weekly testing would reduce infections by 9.7-9.8%. For a lower transmission constant of 4.067e-5 new infections per person2, weekly and biweekly HCW testing would result in a 1.54% and 0.7% reduction in infections respectively. Conclusion: Periodic COVID-19 testing for emergency department staff in regions that are heavily-affected by COVID-19 and/or facing resource constraints may reduce COVID-19 transmission significantly among healthcare workers and previously-uninfected patients.


Human Relations virtual special issue: Virtual Working


title: Clinical characteristics of the recovered COVID-19 patients with re-detectable positive RNA test

text: Background It has been reported that several cases recovered from COVID-19 tested positive for SARS-CoV-2 after discharge (re-detectable positive, RP), however the clinical characteristics, significance and potential cause of RP patients remained elusive. Methods A total of 262 COVID-19 patients were discharged from January 23 to February 25, 2020, and were enrolled for analysis of their clinical parameters. The RP and non-RP (NRP) patients were grouped according to the disease severity during their hospitalization period. The clinical characterization at re-admission to the hospital was analyzed. SARS-CoV-2 RNA and plasma antibody levels were detected using high-sensitive detection methods. Findings Up to March 10, 2020, all of patients were followed up for at least 14 days, and 38/262 of RP patients (14.5%) were present. The RP patients were characterized by being less than 14-years old and having mild and moderate conditions as compared to NRP patients, while no severe patients became RP. Retrospectively, the RP patients displayed fewer symptoms, more sustained remission of CT imaging and earlier RNA negative-conversion but similar plasma antibody levels during their hospitalization period as compared to those NRP patients. When re-admitted to the hospital, these RP patients showed no obvious clinical symptoms or disease progression indicated by normal or improving CT imaging and inflammatory cytokine levels. All 21 close contacts of RP patients were tested negative for SARS-CoV-2 RNA, and no suspicious clinical symptoms were reported. However, 18/24 of RNA-negative samples detected by the commercial kit were tested to be positive for virus RNA using a hyper-sensitive method, suggesting the carrier status of virus possibly existed in patients recovered from COVID-19. Interpretation Our results showed that young and mild COVID-19 patients seem to be RP patients after discharge, who show no obviously clinical symptoms and disease progression upon re-admission. More sensitive RNA detection methods are required to monitor these patients during follow-up. Our findings provide empirical information and evidence for the effective management of COVID-19 patients during their convalescent phase.


title: From SARS to COVID-19: A previously unknown SARS- related coronavirus (SARS-CoV-2) of pandemic potential infecting humans – Call for a One Health approach

text: Human coronaviruses continue to pose a threat to human health. The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019 which causes coronavirus disease-2019 (COVID-19), an acute respiratory disease marked the third introduction of a highly pathogenic coronavirus into the human population in the twenty-first century. This recent emergence of a previously unknown coronavirus in China leads to huge impacts on humans globally. Covid-19 is a challenge to global public health. Here, we discuss the COVID-19 outbreak in a one health context, highlighting the need for the implementation of one health measures and practices to improve human health and reduce the emergence of pandemic viruses.


title: SARS-CoV-2 Encodes a PPxY Late Domain Motif that is Known to Enhance Budding and Spread in Enveloped RNA Viruses

text: Currently, the global COVID-19 (Coronavirus Disease-2019) pandemic is affecting the health and/or socioeconomic life of almost each people in the world. Finding vaccines and therapeutics is urgent but without forgetting to elucidate the molecular mechanisms that allow some viruses to become dangerous for humans. Here, analysis of all proteins of SARS-CoV-2 revealed a unique PPxY Late (L) domain motif 25PPAY28 in spike protein inside hot disordered loop predicted subject to phosphorylation and binding. It was demonstrated in enveloped RNA viruses that PPxY motif recruits Nedd4 E3 ubiquitin ligases and ultimately the ESCRT complex to enhance virus budding and release that means a high viral load, hence facilitating new infections. Note that PPxY motif is not present in proteins of SARS-CoV. This suggests that PPxY motif by its role in enhancing the viral load could explain why SARS-CoV-2 is more contagious than SARS-CoV. Of course, after the experimental verifications showing that PPxY motif plays the same role as reported for other enveloped RNA viruses, it could become an interesting target for the development of novel host-oriented antivirals therapeutics for preventing S protein to recruit Nedd4 E3 ubiquitin ligases partners.


title: Isolation, sequence, infectivity and replication kinetics of SARS-CoV-2

text: SARS-CoV-2 emerged in December 2019 in Wuhan, China and has since infected over 1.5 million people, of which over 107,000 have died. As SARS-CoV-2 spreads across the planet, speculations remain about the range of human cells that can be infected by SARS-CoV-2. In this study, we report the isolation of SARS-CoV-2 from two cases of COVID-19 in Toronto, Canada. We determined the genomic sequences of the two isolates and identified single nucleotide changes in representative populations of our virus stocks. More importantly, we tested a wide range of human immune cells for productive infection with SARS-CoV-2. Here we confirm that human primary peripheral blood mononuclear cells (PBMCs) are not permissive for SARS-CoV-2. As SARS-CoV-2 continues to spread globally, it is essential to monitor single nucleotide polymorphisms in the virus and to continue to isolate circulating viruses to determine viral genotype and phenotype using in vitro and in vivo infection models.


title: Asthma in COVID-19: An extra chain fitting around the neck?

text: Introduction The novel coronavirus disease 2019 (COVID-19) has rapidly spread across the globe, overwhelming healthcare systems and depleting resources. The infection has a wide spectrum of presentations, and pre-existing comorbidities have been found to have a dramatic effect on the disease course and prognosis. We sought to analyze the effect of asthma on the disease progression and outcomes of COVID-19 patients. Methods We conducted a multi-center retrospective study of positively confirmed COVID-19 patients from multiple hospitals in Louisiana. Demographics, medical history, comorbidities, clinical presentation, daily laboratory values, complications, and outcomes data were collected and analyzed. The primary outcome of interest was in-hospital mortality. Secondary outcomes were Intensive Care Unit (ICU) admission, risk of intubation, duration of mechanical ventilation, and length of hospital stay. Results A total of 502 COVID-19 patients (72 asthma and 430 non-asthma cohorts) were included in the study. The frequency of asthma in hospitalized cohorts was 14.3%, higher than the national prevalence of asthma (7.7%). Univariate analysis revealed that asthma patients were more likely to be obese (75% vs 54.2%, p=0.001), with higher frequency of intubation (40.3% vs 27.8%, p = 0.036), and required longer duration of hospitalization (15.1{+/-}12.5 vs 11.5{+/-}10.6, p=0.015). After adjustment, multivariable analysis showed that asthmatic patients were not associated with higher risk of ICU admission (OR=1.81, 95%CI=0.98-3.09, p=0.06), endotracheal intubation (OR=1.77, 95%CI=0.99-3.04, p=0.06) or complications (OR=1.37, 95%CI=0.82-2.31, p=0.23). Asthmatic patients were not associated with higher odds of prolonged hospital length of stay (OR=1.48, 95%CI=0.82-2.66, p=0.20) or with the duration of ICU stay (OR=0.76, 95%CI=0.28-2.02, p=0.58). Kaplan-Meier curve showed no significant difference in overall survival of the two groups (p=0.65). Conclusion Despite the increased prevalence of hospitalization in asthmatic COVID-19 patients compared to the general population, after adjustment for other variables, it was neither associated with increased severity nor worse outcomes.


docid: abiuiiff

title: Inf-Net: Automatic COVID-19 Lung Infection Segmentation from CT Scans

text: Coronavirus Disease 2019 (COVID-19) spread globally in early 2020, causing the world to face an existential health crisis. Automated detection of lung infections from computed tomography (CT) images offers a great potential to augment the traditional healthcare strategy for tackling COVID-19. However, segmenting infected regions from CT scans faces several challenges, including high variation in infection characteristics, and low intensity contrast between infections and normal tissues. Further, collecting a large amount of data is impractical within a short time period, inhibiting the training of a deep model. To address these challenges, a novel COVID-19 Lung Infection Segmentation Deep Network (Inf-Net) is proposed to automatically identify infected regions from chest CT scans. In our Inf-Net, a parallel partial decoder is used to aggregate the high-level features and generate a global map. Then, the implicit reverse attention and explicit edge-attention are utilized to model the boundaries and enhance the representations. Moreover, to alleviate the shortage of labeled data, we present a semi-supervised segmentation framework based on a randomly selected propagation strategy, which only requires a few labeled images and leverages primarily unlabeled data. Our semi-supervised framework can improve the learning ability and achieve a higher performance. Extensive experiments on a COVID-19 infection dataset demonstrate that the proposed Inf-Net outperforms most cutting-edge segmentation models and advances the state-of-the-art


title: Advising Medical Students during COVID-19: The Case for a Single Emergency Medicine Rotation for All

text: The COVID-19 pandemic has disrupted the usual approach to exploring and applying into emergency medicine (EM) for medical students. On March 17th, 2020, the American Association of Medical Colleges issued guidance strongly suggesting that medical students be removed from direct patient care. Many medical schools removed medical students from clerkships and postponed hosting visiting medical students indefinitely. An informal query of EM clerkship directors on the Clerkship Directors in Emergency Medicine (CDEM) list-serve confirmed this trend in EM, with a clear majority of respondents pulling their students from clinical rotations and halting visiting student rotations.


title: Calculated grades, predicted grades, forecasted grades and actual A-level grades: Reliability, correlations and predictive validity in medical school applicants, undergraduates, and postgraduates in a time of COVID-19

text: Calculated A-level grades will replace actual, attained A-levels and other Key Stage 5 qualifications in 2020 in the UK as a result of the COVID 19 pandemic. This paper assesses the likely consequences for medical schools in particular, beginning with an overview of the research literature on predicted grades, concluding that calculated grades are likely to correlate strongly with the predicted grades that schools currently provide on UCAS applications. A notable absence from the literature is evidence on whether predicted grades are better or worse than actual grades in predicting university outcomes. This paper provides such evidence on the reduced predictive validity of predicted A-level grades in comparison with actual A-level grades. The present study analyses the extensive data on predicted and actual grades which are available in UKMED (United Kingdom Medical Education Database), a large-scale administrative dataset containing longitudinal data from medical school application, through undergraduate and then postgraduate training. In particular, predicted A-level grades as well as actual A-level grades are available, along with undergraduate outcomes and postgraduate outcomes which can be used to assess predictive validity of measures collected at selection. This study looks at two UKMED datasets. In the first dataset we compare actual and predicted A-level grades in 237,030 A-levels taken by medical school applicants between 2010 and 2018. 48.8% of predicted grades were accurate, grades were over-predicted in 44.7% of cases and under-predicted in 6.5% of cases. Some A-level subjects, General Studies in particular, showed a higher degree of over-estimation. Similar over-prediction was found for Extended Project Qualifications, and for SQA Advanced Highers. The second dataset considered 22,150 18-year old applicants to medical school in 2010 to 2014, who had both predicted and actual A-level grades. 12,600 students entered medical school and had final year outcomes available. In addition there were postgraduate outcomes for 1,340 doctors. Undergraduate outcomes are predicted significantly better by actual, attained A-level grades than by predicted A-level grades, as is also the case for postgraduate outcomes. Modelling the effect of selecting only on calculated grades suggests that because of the lesser predictive ability of predicted grades, medical school cohorts for the 2020 entry year are likely to under-attain, with 13% more gaining the equivalent of the current lowest decile of performance, and 16% fewer gaining the equivalent of the current top decile, effects which are then likely to follow through into postgraduate training. The problems of predicted/calculated grades can to some extent, although not entirely, be ameliorated, by taking U(K)CAT, BMAT, and perhaps other measures into account to supplement calculated grades. Medical schools will probably also need to consider whether additional teaching is needed for entrants who are struggling, or might have missed out on important aspects of A-level teaching, with extra support being needed, so that standards are maintained.


title: Studies of Novel Coronavirus Disease 19 (COVID-19) Pandemic: A Global Analysis of Literature

text: An exponential growth of literature about novel coronavirus disease 19 (COVID-19) has been observed in the last few months. This textual analysis of 5,780 publications extracted from the Web of Science, Medline, and Scopus databases was performed to explore the current research focuses and propose further research agenda. The Latent Dirichlet allocation was used for topic modeling. Regression analysis was conducted to examine country variations in the research focuses. Results indicated that publications were mainly contributed by the United States, China, and European countries. Guidelines for emergency care and surgical, viral pathogenesis, and global responses in the COVID-19 pandemic were the most common topics. There was variation in the research approaches to mitigate COVID-19 problems in countries with different income and transmission levels. Findings highlighted the need for global research collaboration among high- and low/middle-income countries in the different stages of prevention and control the pandemic.


title: The dynamics of Covid-19: weather, demographics and infection timeline

text: We study the effects of three types of variables on the early pace of spread of Covid-19: weather variables, temperature and absolute humidity; population density; the timeline of Covid-19 infection, as outbreak of disease occurs in different dates for different regions. The regions considered were all 50 U.S. states and 110 countries (those which had enough data available by April 10th. We looked for associations between the above variables and an estimate of the growth rate of cases, the exponential coefficient, computed using data for 10 days starting when state/country reached 100 confirmed cases. The results for U.S. states indicate that one cannot expect that higher temperatures and higher levels of absolute humidity would translate into slower pace of Covid-19 infection rate, at least in the ranges of those variables during the months of February and March of 2020 (-2.4 to 24C and 2.3 to 15g/m3). In fact, the opposite is true: the higher the temperature and the absolute humidity, the faster the Covid-19 has expanded in the U.S. states, in the early stages of the outbreak. Secondly, using the highest county population density for each state, there is strong positive association between population density and (early) faster spread of Covid-19. Finally, there is strong negative association between the date when a state reached 100 accumulated cases and the speed of Covid-10 outbreak (the later, the lower the estimate of growth rate). When these variables are considered together, only population density and the timeline variable show statistical significance. We also develop the basic models for the collection of countries, without the demographic variable. Despite the evidence, in that case, that warmer and more humid countries have shown lower rates of Covid-19 expansion, the weather variables lose statistical significance when the timeline variable is added.


title: Stability and infectivity of coronaviruses in inanimate environments

text: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious virus that can transmit through respiratory droplets, aerosols, or contacts. Frequent touching of contaminated surfaces in public areas is therefore a potential route of SARS-CoV-2 transmission. The inanimate surfaces have often been described as a source of nosocomial infections. However, summaries on the transmissibility of coronaviruses from contaminated surfaces to induce the coronavirus disease 2019 are rare at present. This review aims to summarize data on the persistence of different coronaviruses on inanimate surfaces. The literature was systematically searched on Medline without language restrictions. All reports with experimental evidence on the duration persistence of coronaviruses on any type of surface were included. Most viruses from the respiratory tract, such as coronaviruses, influenza, SARS-CoV, or rhinovirus, can persist on surfaces for a few days. Persistence time on inanimate surfaces varied from minutes to up to one month, depending on the environmental conditions. SARS-CoV-2 can be sustained in air in closed unventilated buses for at least 30 min without losing infectivity. The most common coronaviruses may well survive or persist on surfaces for up to one month. Viruses in respiratory or fecal specimens can maintain infectivity for quite a long time at room temperature. Absorbent materials like cotton are safer than unabsorbent materials for protection from virus infection. The risk of transmission via touching contaminated paper is low. Preventive strategies such as washing hands and wearing masks are critical to the control of coronavirus disease 2019.


title: Single cell resolution regulatory landscape of the mouse kidney highlights cellular differentiation programs and renal disease targets

text: Determining the epigenetic program that generates unique cell types in the kidney is critical for understanding cell-type heterogeneity during tissue homeostasis and injury response. Here, we profiled open chromatin and gene expression in developing and adult mouse kidneys at single cell resolution. We show critical reliance of gene expression on distal regulatory elements (enhancers). We define key cell type-specific transcription factors and major gene-regulatory circuits for kidney cells. Dynamic chromatin and expression changes during nephron progenitor differentiation demonstrated that podocyte commitment occurs early and is associated with sustained Foxl1 expression. Renal tubule cells followed a more complex differentiation, where Hfn4a was associated with proximal and Tfap2b with distal fate. Mapping single nucleotide variants associated with human kidney disease identified critical cell types, developmental stages, genes, and regulatory mechanisms. We provide a global single cell resolution view of chromatin accessibility of kidney development. The dataset is available via interactive public websites.


title: Security Enhancement Against Insiders in Cyber-Manufacturing Systems

text: Abstract Insiders—who are within a security parameter of a system—can intentionally or unintentionally harm the system due to their granted access authorization and intimate knowledge of the system. Especially, Cyber-Manufacturing systems employing Programmable Logic Controller (PLC) to control manufacturing processes via various computer networks can be easily compromised and critically damaged by insiders. This paper presents a system architecture of an applied blockchain in Cyber-Manufacturing System, where the input data for PLC is stored and retrieved through the blockchain. The paper demonstrates how the blockchain technology can help preventing the data from unintended manipulation or data injection by insiders.


title: Differences by country-level income in COVID-19 cases, deaths, case-fatality rates, and rates per million population in the first five months of the pandemic

text: Abstract Objective: To describe differences by country-level income in COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates per million population. Methods: Publicly available data on COVID-19 cases and deaths from December 31, 2019 to June 3, 2020 were analyzed. Kruskal-Wallis tests were used to examine associations of country-level income with COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates. Results: A total of 380,803 deaths out of 6,348,204 COVID-19 cases were reported from 210 countries and territories globally in the period under study, and the global case-fatality rate was 6.0%. Of the total globally reported cases and deaths, the percentages of cases and deaths were 59.9% and 75.0% for high-income countries, and 30.9% and 20.7% for upper-middle-income countries. Countries in higher-income categories had higher incidence rates and death rates. Between April and May, the incidence rates in higher-income groups of countries decreased, but in other groups, it increased. Conclusions In the first five months of the COVID-19 pandemic, most cases and deaths were reported from high-income and upper-middle-income countries, and those countries had higher incidence rates and death rates per million population than did lower-middle and low-income countries. Keywords: COVID-19, incidence rate, death rate, case fatality rate, income, and country


title: Erythrocyte Sedimentation Rate in COVID-19 Infections

text: Objectives To compare the clinical characteristics between the rapid cohort and the normal cohort of erythrocyte sedimentation rate (ESR) in COVID-19 infections, analyze the variables with significant differences, and explore the influencing factors of rapid ESR. Methods Selected a total of 80 patients with ESR detection during hospitalization were measured in 146 patients who received medical observation in concentrated isolation hospital in Guizhou province in China , collected and compared demographic information, epidemiological data, clinical symptoms, laboratory test data and CT image data during the observation between rapid cohort and normal group of ESR. Results By comparison, the proportion of male in the rapid cohort was higher than female. The average age was more than 35 years old, with a large age gap. The proportion of severe and critical patients was more than 26.53% (13/49). However, in the normal cohort the proportion of female was more than male, and the average age was about 8 years lower than the rapid cohort, and the age gap was smaller. The proportion of severe and critical patients was 12.90%, which was less than half of the rapid group. In the two groups, the proportion of clustered cases accounted for more than 50%, and the average number of patients in one family was more than 3. The most common clinical symptoms were cough, sputum, fever, sore throat and weakness of limbs. There were significant differences in ALT, {gamma}-GT and C-reactive protein between the rapid and normal cohort (P<0.05), but no statistically significant in other indicators. Hemoglobin and C-reactive protein have a significant effect on erythrocyte sedimentation rate. Conclusions In this study, we found that ESR is related to Hemoglobin and C-reactive protein.


title: DisCVR: Rapid viral diagnosis from high-throughput sequencing data

text: High-throughput sequencing (HTS) enables most pathogens in a clinical sample to be detected from a single analysis, thereby providing novel opportunities for diagnosis, surveillance and epidemiology. However, this powerful technology is difficult to apply in diagnostic laboratories because of its computational and bioinformatic demands. We have developed DisCVR, which detects known human viruses in clinical samples by matching sample k-mers (22 nucleotide sequences) to k-mers from taxonomically labelled viral genomes. DisCVR was validated using published HTS data for 89 clinical samples from adults with upper respiratory tract infections. These samples had been tested for viruses metagenomically and also by real-time polymerase chain reaction assay, which is the standard diagnostic method. DisCVR detected human viruses with high sensitivity (79%) and specificity (100%), and was able to detect mixed infections. Moreover, it produced results comparable to those in a published metagenomic analysis of 177 blood samples from patients in Nigeria. DisCVR has been designed as a user-friendly tool for detecting human viruses from HTS data using computers with limited RAM and processing power, and includes a graphical user interface to help users interpret and validate the output. It is written in Java and is publicly available from http://bioinformatics.cvr.ac.uk/discvr.php. Issue Section Resources


title: Global profiling of SARS-CoV-2 specific IgG/ IgM responses of convalescents using a proteome microarray

text: COVID-19 is caused by SARS-CoV-2, and has become a global pandemic. There is no highly effective medicine or vaccine, most of the patients were recovered by their own immune response, especially the virus specific IgG and IgM responses. However, the IgG/ IgM responses is barely known. To enable the global understanding of SARS-CoV-2 specific IgG/ IgM responses, a SARS-CoV-2 proteome microarray with 18 out of the 28 predicted proteins was constructed. The microarray was applied to profile the IgG/ IgM responses with 29 convalescent sera. The results suggest that at the convalescent phase 100% of patients had IgG/ IgM responses to SARS-CoV-2, especially to protein N, S1 but not S2. S1 purified from mammalian cell demonstrated the highest performance to differentiate COVID-19 patients from controls. Besides protein N and S1, significant antibody responses to ORF9b and NSP5 were also identified. In-depth analysis showed that the level of S1 IgG positively correlate to age and the level of LDH (lactate dehydrogenase), especially for women, while the level of S1 IgG negatively correlate to Ly% (Lymphocyte percentage). This study presents the first whole picture of the SARS-CoV-2 specific IgG/ IgM responses, and provides insights to develop precise immuno-diagnostics, effective treatment and vaccine.