title: Document addressed to cardiovascular echography operators at the time of COVID-19: A Document by the 'Società Italiana di Ecocardiografia e CardioVascular Imaging' Board 2019-2021

text: The epidemic of COVID-19 has grown to pandemic proportions and the preventive and mitigation measures have been widely spread through the media. The cardiologists are called as consultants for the cardiovascular pathologies and echocardiography is a fundamental examination in many clinical situations, but not without risks for health staff. Società Italiana di Ecocardiografia e CardioVascular Imaging Council has decided to formulate a document aimed to highlight the importance of a correct indication and execution procedure of the echocardiogram during a COVID-19 pandemic.


On the possibility of interrupting the coronavirus (COVID-19) epidemic based on the best available scientific evidence.


title: Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models

text: We present an approach to investigate SARS-CoV-2 virus sequences based on alignment-free methods for RNA sequence comparison. In particular, we verify a given clustering result for the GISAID data set, which was obtained analyzing the molecular differences in coronavirus populations by phylogenetic trees. For this purpose, we use alignment-free dissimilarity measures for sequences and combine them with learning vector quantization classifiers for virus type discriminant analysis and classification. Those vector quantizers belong to the class of interpretable machine learning methods, which, on the one hand side provide additional knowledge about the classification decisions like discriminant feature correlations, and on the other hand can be equipped with a reject option. This option gives the model the property of self controlled evidence if applied to new data, i.e. the models refuses to make a classification decision, if the model evidence for the presented data is not given. After training such a classifier for the GISAID data set, we apply the obtained classifier model to another but unlabeled SARS-CoV-2 virus data set. On the one hand side, this allows us to assign new sequences to already known virus types and, on the other hand, the rejected sequences allow speculations about new virus types with respect to nucleotide base mutations in the viral sequences. Author summary The currently emerging global disease COVID-19 caused by novel SARS-CoV-2 viruses requires all scientific effort to investigate the development of the viral epidemy, the properties of the virus and its types. Investigations of the virus sequence are of special interest. Frequently, those are based on mathematical/statistical analysis. However, machine learning methods represent a promising alternative, if one focuses on interpretable models, i.e. those that do not act as black-boxes. Doing so, we apply variants of Learning Vector Quantizers to analyze the SARS-CoV-2 sequences. We encoded the sequences and compared them in their numerical representations to avoid the computationally costly comparison based on sequence alignments. Our resulting model is interpretable, robust, efficient, and has a self-controlling mechanism regarding the applicability to data. This framework was applied to two data sets concerning SARS-CoV-2. We were able to verify previously published virus type findings for one of the data sets by training our model to accurately identify the virus type of sequences. For sequences without virus type information (second data set), our trained model can predict them. Thereby, we observe a new scattered spreading of the sequences in the data space which probably is caused by mutations in the viral sequences.


Covid-19: Questions of conscience and duty for scientific advisers


docid: zettmwfd

title: The hidden variable in the dynamics of transmission of COVID-19: A Henon map approach

text: We consider the transmission dynamics of COVID-19 which is characterized by two distinct features. One is the existence of asymptomatic carriers which is the hidden variable in the problem. The other is the issue of latency which means that among the symptomatic carriers there could be a fraction whose symptoms develop after a couple of days. We write down a Henon-like map to take these effects into account and find that the map has an unusual fixed point which corresponds to a very high ratio of asymptomatic to symptomatic infected persons. This fixed point has its own stability zone and influences the dynamics overall. Although a rather elementary model, we show that it is not totally devoid of reality.


title: Pooling of Nasopharyngeal Swab Specimens for SARS-CoV-2 detection by RT-PCR

text: Systematic testing of large population groups by RT-PCR is mandatory to Covid-19 case identification and contact tracing in order to minimize the likelyhood of resurgence in contagion. Sample pooling for RT-PCR has been effectively used to detect community transmission of SARS CoV-2. Nevertheless, this procedure may decrease the sensitivity of RT-PCR assays due to specimen dilution. We evaluated the efficacy of this strategy for diagnosis of Covid-19 using a sensitive commercially-available RT-PCR targeting SARS CoV-2 E and RdRp genes in a single reaction. A total of 20 mini-pools containing either 5 (n=10) or 10 (n=10) nasopharyngeal exudates collected in universal transport medium were made, each of which including a unique positive NP specimen. Positive specimens yielding CT <32 for the E gene (6 out of 10) or <35.2 for the RdRP gene (7 out of 10) were detected in mini-pools of both sizes. In contrast, most NP samples displaying CTs > 35.8 for the E gene or 35.7 for the RdRP gene remained undetected in mini-pools of 5 specimens (3/4 and 2/3, respectively) or in mini-pools of 10 samples (4/4 and 3/3, respectively.


title: Improving effectiveness of different deep learning-based models for detecting COVID-19 from computed tomography (CT) images

text: Computerized Tomography (CT )has a prognostic role in the early diagnosis of COVID-19 due to it gives both fast and accurate results. This is very important to help decision making of clinicians for quick isolation and appropriate patient treatment. In this study, we combine methods such as segmentation, data augmentation and the generative adversarial network (GAN) to improve the effectiveness of learning models. We obtain the best performance with 99% accuracy for lung segmentation. Using the above improvements we get the highest rates in terms of accuracy (99.8%), precision (99.8%), recall (99.8%), f1-score (99.8%) and roc acu (99.9979%) with deep learning methods in this paper. Also we compare popular deep learning-based frameworks such as VGG16, VGG19, Xception, ResNet50, ResNet50V2, DenseNet121, DenseNet169, InceptionV3 and InceptionResNetV2 for automatic COVID-19 classification. The DenseNet169 amongst deep convolutional neural networks achieves the best performance with 99.8% accuracy. The second-best learner is InceptionResNetV2 with accuracy of 99.65%. The third-best learner is Xception and InceptionV3 with accuracy of 99.60%.


title: CovProfile: profiling the viral genome and gene expressions of SARS-COV-2

text: The SARS-CoV-2 virus has infected more than one million people worldwide to date. Knowing its genome and gene expressions is essential to understand the virus’ mechanism. Here, we propose a computational tool CovProfile to detect the viral genomic variations as well as viral gene expressions from the sequences obtained from Nanopore devices. We applied CovProfile to 11 samples, each from a terminally ill patient, and discovered that all the patients are infected by multiple viral strains, which might affect the reliability of phylogenetic analysis. Moreover, the expression of viral genes ORF1ab gene, S gene, M gene, and N gene are high among most of the samples. While performing the tests, we noticed a consistent abundance of transcript segments of MUC5B, presumably from the host, across all the samples.


title: Prognostic value of NT-proBNP in patients with severe COVID-19

text: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China has been declared a public health emergency of international concern. The cardiac injury was dominate in the process. However, whether N terminal pro B type natriuretic peptide (NT-proBNP) predicted outcome of COVID-19 patients was unknown. The study initially enrolled 102 patients with severe COVID-19 pneumonia from a continuous sample. After screening out the ineligible cases, 54 patients were analyzed in this study. Results found that patients with higher NT-proBNP (above 88.64 pg/mL) level had more risks of in-hospital death. After adjusting for potential cofounders in separate modes, NT-proBNP presented as an independent risk factor of in-hospital death in patients with severe COVID-19.


title: An experimental and analytical model for force prediction in sheet metal forming process using perforated sheet and origami principles

text: Abstract In this work, we present a model for origami-based sheet metal (OSM) folding that can predict the required bending force. OSM folding is enabled by introducing bending features along the bending line, named material discontinuity (MD). Firstly, the introduced analysis in this work developed a bending setup for OSM that does not require a die then introduced a method to analytically derive the bending force for a regular sheet without any added folding features. The analytical approach is followed using an experimental setup identical to the developed OSM bending configuration. Secondly, the OSM bending experiment is conducted to measure the required bending force and to identify which parameters influence the OSM bending force significantly. Finally, an empirical model is proposed considering the analytical force in the first step and the influencing parameters defined in the second step. Regression analysis is carried out using one portion of experimental force measurement to determine the coefficients of the proposed empirical model. The other measurement set is used to validate the prediction model. The validation results of the proposed prediction model show good agreement between the developed prediction model and the experiment results. The prediction model provided a shape factor that represents the topology of each bending feature, as well.


title: Who dies from COVID-19? Post-hoc explanations of mortality prediction models using coalitional game theory, surrogate trees, and partial dependence plots

text: As of early June, 2020, approximately 7 million COVID-19 cases and 400,000 deaths have been reported. This paper examines four demographic and clinical factors (age, time to hospital, presence of chronic disease, and sex) and utilizes Shapley values from coalitional game theory and machine learning to evaluate their relative importance in predicting COVID-19 mortality. The analyses suggest that out of the 4 factors studied, age is the most important in predicting COVID-19 mortality, followed by time to hospital. Sex and presence of chronic disease were both found to be relatively unimportant, and the two global interpretation techniques differed in ranking them. Additionally, this paper creates partial dependence plots to determine and visualize the marginal effect of each factor on COVID-19 mortality and demonstrates how local interpretation of COVID-19 mortality prediction can be applicable in a clinical setting. Lastly, this paper derives clinically applicable decision rules about mortality probabilities through a parsimonious 3-split surrogate tree, demonstrating that high-accuracy COVID-19 mortality prediction can be achieved with simple, interpretable models.


title: Origin of Novel Coronavirus (COVID-19): A Computational Biology Study using Artificial Intelligence

text: Origin of the COVID-19 virus has been intensely debated in the scientific community since the first infected cases were detected in December 2019. The disease has caused a global pandemic, leading to deaths of thousands of people across the world and thus finding origin of this novel coronavirus is important in responding and controlling the pandemic. Recent research results suggest that bats or pangolins might be the original hosts for the virus based on comparative studies using its genomic sequences. This paper investigates the COVID-19 virus origin by using artificial intelligence (AI) and raw genomic sequences of the virus. More than 300 genome sequences of COVID-19 infected cases collected from different countries are explored and analysed using unsupervised clustering methods. The results obtained from various AI-enabled experiments using clustering algorithms demonstrate that all examined COVID-19 virus genomes belong to a cluster that also contains bat and pangolin coronavirus genomes. This provides evidences strongly supporting scientific hypotheses that bats and pangolins are probable hosts for the COVID-19 virus. At the whole genome analysis level, our findings also indicate that bats are more likely the hosts for the COVID-19 virus than pangolins.


title: Modes of transmission of COVID-19 outbreak- a mathematical study

text: The world has now paid a lot of attention to the outbreak of novel coronavirus (COVID-19). This virus mainly transmitted between humans through directly respiratory droplets and close contacts. However, there is currently some evidence where it has been claimed that it may be indirectly transmitted. In this work, we study the mode of transmission of COVID-19 epidemic system based on the susceptible-infected-recovered (SIR) model. We have calculated the basic reproduction number R0 by next-generation matrix method. We observed that if R0<1, then disease-free equilibrium point is locally as well as globally asymptotically stable but when $R0>1, the endemic equilibrium point exists and is globally stable. Finally, some numerical simulation is presented to validate our results.


title: Evaluating COVID-19 Public Health Messaging in Italy: Self-Reported Compliance and Growing Mental Health Concerns

text: Purpose: The COVID-19 death-rate in Italy continues to climb, surpassing that in every other country. We implement one of the first nationally representative surveys about this unprecedented public health crisis and use it to evaluate the Italian government's public health efforts and citizen responses. Findings: (1) Public health messaging is being heard. At this point, the Italian people understand how to keep themselves and others safe from the SARS-Cov-2 virus. This is true for all population groups we studied, with the partial exception of slightly lower compliance among young adults. Remarkably, even those who do not trust the government, and those who think the government has been untruthful about the crisis mostly believe the public health message and claim to be acting in accordance. (2) The quarantine is beginning to have serious negative effects on the population's mental health. Policy Recommendations: Public health messaging is being heard and understood. The focus now should move from explaining that citizens should stay at home to what they can do at home. We need interventions that make staying at home and following public health protocols more desirable, or possibly even fun. These interventions could include virtual social interactions, such as online social reading activities, classes, exercise routines, among others - all designed to reduce the boredom of being socially isolated for long periods of time and to increase the attractiveness of following public health recommendations. Interventions like these will grow in importance as the crisis wears on around the world, and staying inside wears on people.


title: Did the National lockdown lock COVID-19 down in India, and reduce pressure on health infrastructure?

text: Background & objectives: The spread of COVID19 in India has posed a major challenge for policy makers. Policy response in form of imposition of a prolonged national lockdown has imposed substantial costs on the entire population. But the extent to which it has contained the spread of the epidemic needs to be assessed. Methods: We use an Interrupted Time Series model to assess the success of lockdowns in containing COVID-19. In the second step, we use four variants of the SIR models to develop a counterfactual- what would have happened without the lockdown. These results are compared with actual data. The analysis is undertaken for India, and Maharashtra, Gujarat, Delhi, and Tamil Nadu. Results: Lockdown has reduced the number of COVID-19 cases by 23.65 to 337.73 lakh in Class I cities and towns, where COVID has mainly spread. It has averted about 0.01 to 0.10 lakh deaths. At the regional level, however, lockdown has averted a health crisis as existing ICU and ventilator facilities for critically ill patients would have been inadequate. Interpretation & conclusions: Overall, the results for three of the four models reveal that lockdown has a modest impact on spread of COVID-19; the health infrastructure at the national level is not over strained, even at the peak. At the regional level, on the other hand, lockdowns may have been justified. However, given that identification of new cases is limited by levels of daily testing that are low even by Asian standards, analysis based upon official data may have limitations and result in flawed decisions.


title: COVID-19 Risk Factors Among Health Workers: A Rapid Review

text: Coronavirus disease 2019 (Covid-19) poses an important occupational health risk to health workers (HWs) that has attracted global scrutiny. To date, several thousand HWs globally have been reported as infected with the severe acute respiratory syndrome coronavirus 2 virus that causes the disease. It is therefore a public health priority for policymakers to understand risk factors for this vulnerable group to avert occupational transmission. A rapid review was carried out on 20 April 2020 on Covid-19 risk factors among HWs in PubMed, Google Scholar, and EBSCOHost Web (Academic Search Complete, CINAHL Complete, MEDLINE with Full Text, CINAHL with Full Text, APA PsycInfo, Health Source—Consumer Edition, Health Source_ Nursing/Academic Edition) and WHO Global Database. We also searched for preprints on the medRxiv database. We searched for reports, reviews, and primary observational studies (case control, case cross-over, cross-sectional, and cohort). The review included studies conducted among HWs with Covid-19 that reported risk factors irrespective of their sample size. Eleven studies met the inclusion criteria. Lack of personal protective equipment, exposure to infected patients, work overload, poor infection control, and preexisting medical conditions were identified as risk factors for Covid-19 among HWs. In the context of Covid-19, HWs face an unprecedented occupational risk of morbidity and mortality. There is need for rapid development of sustainable measures that protect HWs from the pandemic.


Interventional Radiology and the Response to COVID-19


Spine Surgery: Precautions and Strategies to Minimize Perioperative Risks Amid COVID-19 Outbreak


title: FALSE-NEGATIVE RESULTS OF INITIAL RT-PCR ASSAYS FOR COVID-19: A SYSTEMATIC REVIEW

text: Background: Cases with negative reverse transcription-polymerase chain reaction (RT-PCR) results at initial testing for suspicion of SARS-CoV-2 infection, and found to be positive in a subsequent test, are considered as RT-PCR false-negative cases. False-negative cases have important implications for COVID-19 management, isolation, and risk of transmission. We aimed to review and critically appraise evidence about the proportion of RT-PCR false-negatives at initial testing for COVID-19. Methods: We performed a systematic review and critical appraisal of literature with high involvement of stakeholders in the review process. We searched on MEDLINE, EMBASE, LILACS, the WHO database of COVID-19 publications, the EPPI-Centre living systematic map of evidence about COVID-19, and the living systematic review developed by the University of Bern (ISPM). Two authors screened and selected studies according to the eligibility criteria and collected data of included studies (no-independent verification). Risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. We calculated the false-negative proportion with the corresponding 95% CI using a multilevel mixed-effect logistic regression model using STATA 16. Certainty of the evidence about false-negative cases was rated using the GRADE approach for tests and strategies. The information is current up to 6 April 2020. Findings: Five studies enrolling 957 patients were included. All studies were affected by several biases and applicability concerns. Pooled estimation of false-negative proportion was 0.085 (95% CI= 0.034 to 0.196; tau-squared = 1.08; 95% CI= 0.27 to 8.28; p<0.001); however, this estimation is highly affected by unexplained heterogeneity, and its interpretation should be avoided. The certainty of the evidence was judged as very low, due to the risk of bias, indirectness, and inconsistency issues. Conclusions: The collected evidence has several limitations, including risk of bias issues, high heterogeneity, and concerns about its applicability. Nonetheless, our findings reinforce the need for repeated testing in patients with suspicion of SARS-Cov-2 infection given that up to 29% of patients could have an initial RT-PCR false-negative result. Systematic review registration: Protocol available on OSF website: https://osf.io/gp38w/


Housing policy and the COVID-19 pandemic: the importance of housing research during this health emergency


title: Selection, biophysical and structural analysis of synthetic nanobodies that effectively neutralize SARS-CoV-2

text: The coronavirus SARS-CoV-2 is the cause of the ongoing COVID-19 pandemic. Therapeutic neutralizing antibodies constitute a key short-to-medium term approach to tackle COVID-19. However, traditional antibody production is hampered by long development times and costly production. Here, we report the rapid isolation and characterization of nanobodies from a synthetic library, known as sybodies (Sb), that target the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein. Several binders with low nanomolar affinities and efficient neutralization activity were identified of which Sb23 displayed high affinity and neutralized pseudovirus with an IC50 of 0.6 µg/ml. A cryo-EM structure of the spike bound to Sb23 showed that Sb23 binds competitively in the ACE2 binding site. Furthermore, the cryo-EM reconstruction revealed a novel conformation of the spike where two RBDs are in the ‘up’ ACE2-binding conformation. The combined approach represents an alternative, fast workflow to select binders with neutralizing activity against newly emerging viruses.


title: Covid-19: analysis of a modified SEIR model, a comparison of different intervention strategies and projections for India

text: Modeling accurately the evolution and intervention strategies for the Covid-19 pandemic is a challenging problem. We present here an analysis of an extended Susceptible-Exposed-Infected-Recovered (SEIR) model that accounts for asymptomatic carriers, and explore the effect of different intervention strategies such as social distancing (SD) and testing-quarantining (TQ). The two intervention strategies (SD and TQ) try to reduce the disease reproductive number R0 to a target value R0target < 1, but in distinct ways, which we implement in our model equations. We find that for the same target R0target < 1, TQ is more efficient in controlling the pandemic than lockdowns that only implement SD. However, for TQ to be effective, it has to be based on contact tracing and the ratio of tests/day to the number of new cases/day has to be scaled with the mean number of contacts of an infectious person, which would be high in densely populated regions with low levels of SD. We point out that, apart from R0, an important quantity is the largest eigenvalue of the linearised dynamics which provides a more complete understanding of the disease progression, both pre- and post- intervention, and explains observed data for many countries. Weak intervention strategies (that reduce R0 but not to a value less than 1) can reduce the peak values of infections and the asymptotic affected population. We provide simple analytic expressions for these in terms of the disease parameters and apply them in the Indian context to obtain heuristic projections for the course of the pandemic. We find that the predictions strongly depend on the assumed fraction of asymptomatic carriers.


title: Perceived vulnerability to COVID-19 infection from event attendance: Results from Louisiana, USA, two weeks preceding the national emergency declaration

text: In response to the mounting threat of COVID-19, we added questions to an ongoing food preference study held at Louisiana State University from March 3-12 of 2020. We asked 356 participants: (1) In your opinion, how likely is it that the spread of COVID-19 (the coronavirus) will cause a public health crisis in the United States? (2) How concerned are you that you will contract COVID-19 by attending events on campus? Participants' estimates of an impending national health crisis increased significantly during the study's second week (March 9-12) while concern about personally contracting COVID-19 from attending campus events increased only marginally during the study's final days. We find those expressing a higher likelihood of an impending national crisis were more concerned about contracting COVID-19 by attending campus events, suggesting a possible transmission from perceptions of national-level events to perceived personal vulnerability via local exposure. However, about 30% of participants perceived that COVID-19 would likely cause a public health crisis yet did not express concern about contracting COVID-19 from event attendance. These participants were significantly more likely to be younger students who agreed to participate in response to recruitment using same-day flyer distribution. Women expressed a higher likelihood of an emerging national health crisis, although they were not more concerned than men that attending campus events would result in virus contraction. Other groups (e.g., white, students younger than 25, highest income group) displayed similar concern about a national-level crisis, yet were significantly less concerned about contracting COVID-19 from attending campus events than others. Also, participants randomly assigned to information emphasizing the national impacts of food waste expressed significantly greater concern of contracting COVID-19 by attending campus events. These results provide some initial insight about how people perceived national and personal risks in the early stages of the COVID-19 crisis in Louisiana.


title: Preface to the Fourth Edition

text: Unknown


title: In-Ear SpO2: A Tool for Wearable, Unobtrusive Monitoring of Hypoxaemia in COVID-19

text: Non-invasive ambulatory estimation of blood oxygen saturation has emerged as an important clinical requirement to detect hypoxemia in the delayed post-infective phase of COVID-19, where dangerous hypoxia may occur in the absence of subjective breathlessness. This immediate clinical driver, combined with the general quest for more personalised health data, means that pulse oximetry measurement of capillary oxygen saturation (SpO2) will likely expand into both the clinical and consumer market of wearable health technology in the near future. In this study, we set out to establish the feasibility of SpO2 measurement from the ear canal as a convenient site for long term monitoring, and perform a comprehensive comparison with the right index finger - the conventional clinical measurement site. During resting SpO2 estimation, we found a root mean square difference of 1.47% between the two measurement sites, with a mean difference of 0.23% higher SpO2 in the right ear canal. Through the simultaneous recording of pulse oximetry from both the right ear canal and index finger during breath holds, we observe a substantial improvement in response time between the ear and finger that has a mean of 12.4 seconds and a range of 4.2 - 24.2 seconds across all subjects. Factors which influence this response time, termed SpO2 delay, such as the sex of a subject are also explored. Furthermore, we examine the potential downsides of ear canal blood oxygen saturation measurement, namely the lower photoplethysmogram amplitude, and suggest ways to mitigate this disadvantage. These results are presented in conjunction with previously discovered benefits such as robustness to temperature, making the case for measurement of SpO2 from the ear canal being both convenient and superior to conventional finger measurement sites for continuous non-intrusive long term monitoring in both clinical and everyday-life settings.


title: 3D Printing beyond Dentistry during COVID 19 Epidemic: A Technical Note for Producing Connectors to Breathing Devices

text: (1) Background: To mitigate the shortage of respiratory devices during the Covid-19 epidemic, dental professional volunteers can contribute to create printed plastic valves, adapting the dental digital workflow and converting snorkeling masks in emergency CPAP (continuous positive airways pressure) devices The objective of this report was to provide the specific settings to optimize printing with the 3D printers of the dental industry (2) Methods: In order to provide comprehensive technical notes to volunteer dental professionals interested in printing Charlotte and Dave connectors to breathing devices, the entire digital workflow is reported (3) Results: The present paper introduces an alternative use of the dental Computer Aided Design/Computer Aided Manufacturing (CAD/CAM) machinery, and reports on the fabrication of a 3D printed connection prototypes suitable for connection to face masks, thereby demonstrating the feasibility of this application (4) Conclusions: This call for action was addressed to dentists and dental laboratories who are willing to making available their experience, facilities and machinery for the benefit of patients, even way beyond dentistry


title: Ultra-High-Resolution CT Follow-Up in Patients with Imported Early-Stage Coronavirus Disease 2019 (COVID-19) Related Pneumonia

text: Background: An ongoing outbreak of mystery pneumonia in Wuhan was caused by coronavirus disease 2019 (COVID-19). The infectious disease has spread globally and become a major threat to public health. Purpose: We aim to investigate the ultra-high-resolution CT (UHR-CT) findings of imported COVID-19 related pneumonia from the initial diagnosis to early-phase follow-up. Methods: This retrospective study included confirmed cases with early-stage COVID-19 related pneumonia imported from the epicenter. Initial and early-phase follow-up UHR-CT scans (within 5 days) were reviewed for characterizing the radiological findings. The normalized total volumes of ground-glass opacities (GGOs) and consolidations were calculated and compared during the radiological follow-up by artificial-intelligence-based methods. Results: Eleven patients (3 males and 8 females, aged 32-74 years) with confirmed COVID-19 were evaluated. Subpleural GGOs with inter/intralobular septal thickening were typical imaging findings. Other diagnostic CT features included distinct margins (8/11, 73%), pleural retraction or thickening (7/11, 64%), intralesional vasodilatation (6/11, 55%). Normalized volumes of pulmonary GGOs (p=0.003) and consolidations (p=0.003) significantly increased during the CT follow-up. Conclusions: The abnormalities of GGOs with peripleural distribution, consolidated areas, septal thickening, pleural involvement and intralesional vasodilatation on UHR-CT indicate the diagnosis of COVID-19. COVID-19 cases could manifest significantly progressed GGOs and consolidations with increased volume during the early-phase CT follow-up.


title: A simple laboratory parameter facilitates early identification of COVID-19 patients

text: The total number of COVID-19 patients since the outbreak of this infection in Wuhan, China has reached 40000 and are still growing. To facilitate triage or identification of the large number of COVID-19 patients from other patients with similar symptoms in designated fever clinics, we set to identify a practical marker that could be conveniently utilized by first-line health-care workers in clinics. To do so, we performed a case-control study by analyzing clinical and laboratory findings between PCR-confirmed SARS-CoV-2 positive patients (n=52) and SARS-CoV-2 negative patients (n=53). The patients in two cohorts all had similar symptoms, mainly fever and respiratory symptoms. The rates of patients with leukocyte counts (normal or decreased number) or lymphopenia (two parameters suggested by current National and WHO COVID-19 guidelines) had no differences between these two cohorts, while the rate of eosinopenia (decreased number of eosinophils) in SARS-CoV-2 positive patients (79%) was much higher than that in SARS-CoV-2 negative patients (36%). When the symptoms were combined with eosinopenia, this combination led to a diagnosis sensitivity and specificity of 79% and 64%, respectively, much higher than 48% and 53% when symptoms were combined with leukocyte counts (normal or decreased number) and/ or lymphopenia. Thus, our analysis reveals that eosinopenia may be a potentially more reliable laboratory predictor for SARS-CoV-2 infection than leukocyte counts and lymphopenia recommended by the current guidelines.


Patient Handout: Managing the Stress of the Covid-19 Pandemic COVID19 –Nuclear Medicine Departments, be prepared!


title: Early assessment of knowledge, attitudes, anxiety and behavioral adaptations of Connecticut residents to COVID-19

text: Objectives. To assess knowledge, attitudes, anxiety and behavioral adaptations to COVID-19. Methods. A cross-sectional study was conducted among non-healthcare-related participants after a stringent stay-at-home directive was implemented. Multivariate logistic regression analysis was conducted to identify factors associated with anxiety, perceived seriousness of COVID-19 and loneliness. Results. A total of 464 participants responded to the survey. Most participants recognized cough, shortness of breath and fever as primary symptoms of COVID-19. Nearly 50% reported high levels of anxiety to COVID-19 and 48% reported being loneliness during the social isolation. Those with higher level of COVID-19 knowledge had 1.20 times higher levels with anxiety. Being married had 1.79 times higher levels of anxiety about COVID-19. Older age was associated with loneliness during the social isolation. Older age was also associated with taking the pandemic seriously. Females were less likely to report loneliness than males. Conclusions. It is crucial for the public health authorities not only provide accurate and scientific information about the COVID-19 promoting protective behavior changes but also to minimize anxiety through supportive messages and recommendations for positive coping strategies and timely offering of counseling services for those in need.


From the Editors: Covid-19 and race and Ethnic Studies


title: ASSESSING THE POTENTIAL IMPACT OF TRANSMISSION DURING PROLONGED VIRAL SHEDDING ON THE EFFECT OF LOCKDOWN RELAXATION ON COVID-19

text: A key parameter in epidemiological modeling which characterizes the spread of an infectious disease is the mean serial interval. There is increasing evidence supporting a prolonged viral shedding window for COVID-19, but the transmissibility in this phase is unclear. Based on this, we build a model including an additional compartment of infectious individuals who stay infectious for a longer duration than the reported serial interval, but with infectivity reduced to varying degrees. We find that such an assumption also yields a plausible model in explaining the data observed so far, but has different implications for the future predictions in case of a gradual easing on the lockdown measures. Considering the role of modeling in important decisions such as easing lockdown measures and adjusting hospital capacity, we believe that it is critically important to consider a chronically infectious population as an alternative modeling approach to better interpret the transmission dynamics of COVID-19.


docid: pughsygu

title: Understanding the asymmetric spread and case fatality rate (CFR) for COVID-19 among countries

text: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are rising rapidly every day in the world, causing the disease COVID-19 with around 2 million people infected and more than 100,000 people died so far, in more than 200 countries. One of the baffling aspects of this pandemic is the asymmetric increase in cases and case fatality rate (CFR) among countries. We analyze the time series of the infection and fatality numbers and found two interesting aspects. Firstly, the rate of spread in a region is directly connected to the population density of the region where the virus is spreading. For example, the high rate of increase in cases in the United States of America (USA) is related to the high population density of New York City. This is shown by scaling the cumulative number of cases with a measure of the population density of the affected region in countries such as Italy, Spain, Germany, and the USA and we see that the curves are coinciding. Secondly, we analyzed the CFR number as a function of the number of days, since the first death, and we found that there are two clear categories among countries: one category with high CFR numbers (around 10%) and the other category with low CFR numbers (2% to 4%). When we analyzed the results, we see that countries with lower CFR numbers more or less tend to have implemented active control measures such as aggressive testing, tracking down possible infections, effective quarantine measures, etc. Moreover, we did not see any convincing correlation between mortality rates and the median age of the population.


title: A call for governments to pause Twitter censorship: a cross-sectional study using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion

text: Objectives: To determine whether Twitter data can be used as social-spatial sensors to show how research on COVID-19/SARS-CoV-2 diffuses through the population to reach the people that are especially affected by the disease. Design: Cross-sectional bibliometric analysis conducted between 23rd March and 14th April 2020. Setting: Three sources of data were used in the analysis: (1) deaths per number of population for COVID-19/SARS-CoV-2 retrieved from Coronavirus Resource Center at John Hopkins University and Worldometer, (2) publications related to COVID-19/SARS-CoV-2 retrieved from WHO COVID-19 database of global publications, and (3) tweets of these publications retrieved from Altmetric.com and Twitter. Main Outcome(s) and Measure(s): To map Twitter activity against number of publications and deaths per number of population worldwide and in the USA states. To determine the relationship between number of tweets as dependent variable and deaths per number of population and number of publications as independent variables. Results: Deaths per one hundred thousand population for countries ranged from 0 to 104, and deaths per one million population for USA states ranged from 2 to 513. Total number of publications used in the analysis was 1761, and total number of tweets used in the analysis was 751,068. Mapping of worldwide data illustrated that high Twitter activity was related to high numbers of COVID-19/SARS-CoV-2 deaths, with tweets inversely weighted with number of publications. Poisson regression models of worldwide data showed a positive correlation between the national deaths per number of population and tweets when holding the country's number of publications constant (coefficient 0.0285, S.E. 0.0003, p<0.001). Conversely, this relationship was negatively correlated in USA states (coefficient -0.0013, S.E. 0.0001, p<0.001). Conclusions: This study shows that Twitter can play a crucial role in the rapid research response during the COVID-19/SARS-CoV-2 global pandemic, especially to spread research with prompt public scrutiny. Governments are urged to pause censorship of social media platforms during these unprecedented times to support the scientific community's fight against COVID-19/SARS-CoV-2.


title: Original research: How accurate are digital symptom assessment apps for suggesting conditions and urgency advice?: a clinical vignettes comparison to GPs

text: Objectives To compare breadth of condition coverage, accuracy of suggested conditions and appropriateness of urgency advice of 8 popular symptom assessment apps with each other and with 7 General Practitioners. Design Clinical vignettes study. Setting 200 clinical vignettes representing real-world scenarios in primary care. Intervention/comparator Condition coverage, suggested condition accuracy, and urgency advice performance was measured against the vignettes' gold-standard diagnoses and triage level. Primary outcome measures Outcomes included (i) proportion of conditions 'covered' by an app, i.e. not excluded because the patient was too young/old, pregnant, or comorbid, (ii) proportion of vignettes in which the correct primary diagnosis was amongst the top 3 conditions suggested, and, (iii) proportion of 'safe' urgency level advice (i.e. at gold standard level, more conservative, or no more than one level less conservative). Results Condition-suggestion coverage was highly variable, with some apps not offering a suggestion for many users: in alphabetical order, Ada: 99.0%; Babylon: 51.5%; Buoy: 88.5%; K Health: 74.5%; Mediktor: 80.5%; Symptomate: 61.5%; Your.MD: 64.5%. The top-3 suggestion accuracy (M3) of GPs was on average 82.1{+/-}5.2%. For the apps it was - Ada: 70.5%; Babylon: 32.0%; Buoy: 43.0%; K Health: 36.0%; Mediktor: 36.0%; Symptomate: 27.5%; WebMD: 35.5%; Your.MD: 23.5%. Some apps exclude certain user groups (e.g. younger users) or certain conditions - for these apps condition-suggestion performance is generally greater with exclusion of these vignettes. For safe urgency advice, tested GPs had an average of 97.0{+/-}2.5%. For the vignettes with advice provided, only three apps had safety performance within 1 S.D. of the GPs (mean) - Ada: 97.0%; Babylon: 95.1%; Symptomate: 97.8%. One app had a safety performance within 2 S.D.s of GPs - Your.MD: 92.6%. Three apps had a safety performance outside 2 S.D.s of GPs - Buoy: 80.0% (p< 0.001); K Health: 81.3% (p< 0.001); Mediktor: 87.3% (p=1.3x10-3). Conclusions The utility of digital symptom assessment apps relies upon coverage, accuracy, and safety. While no digital tool outperformed GPs, some came close, and the nature of iterative improvements to software offers scalable improvements to care.


title: Quantifying COVID-19 Content in the Online Health Opinion War Using Machine Learning

text: A huge amount of potentially dangerous COVID-19 misinformation is appearing online. Here we use machine learning to quantify COVID-19 content among online opponents of establishment health guidance, in particular vaccinations ('anti-vax'). We find that the anti-vax community is developing a less focused debate around COVID-19 than its counterpart, the pro-vaccination ('pro-vax') community. However, the anti-vax community exhibits a broader range of 'flavors' of COVID-19 topics, and hence can appeal to a broader cross-section of individuals seeking COVID-19 guidance online, e.g. individuals wary of a mandatory fast-tracked COVID-19 vaccine or those seeking alternative remedies. Hence the anti-vax community looks better positioned to attract fresh support going forward than the pro-vax community. This is concerning since a widespread lack of adoption of a COVID-19 vaccine will mean the world falls short of providing herd immunity, leaving countries open to future COVID-19 resurgences. We provide a mechanistic model that interprets these results and could help in assessing the likely efficacy of intervention strategies. Our approach is scalable and hence tackles the urgent problem facing social media platforms of having to analyze huge volumes of online health misinformation and disinformation.


title: SARS-CoV-2 is transmitted via contact and via the air between ferrets

text: SARS-CoV-2, a coronavirus that newly emerged in China in late 2019 1,2 and spread rapidly worldwide, caused the first witnessed pandemic sparked by a coronavirus. As the pandemic progresses, information about the modes of transmission of SARS-CoV-2 among humans is critical to apply appropriate infection control measures and to slow its spread. Here we show that SARS-CoV-2 is transmitted efficiently via direct contact and via the air (via respiratory droplets and/or aerosols) between ferrets. Intranasal inoculation of donor ferrets resulted in a productive upper respiratory tract infection and long-term shedding, up to 11 to 19 days post-inoculation. SARS-CoV-2 transmitted to four out of four direct contact ferrets between 1 and 3 days after exposure and via the air to three out of four independent indirect recipient ferrets between 3 and 7 days after exposure. The pattern of virus shedding in the direct contact and indirect recipient ferrets was similar to that of the inoculated ferrets and infectious virus was isolated from all positive animals, showing that ferrets were productively infected via either route. This study provides experimental evidence of robust transmission of SARS-CoV-2 via the air, supporting the implementation of community-level social distancing measures currently applied in many countries in the world and informing decisions on infection control measures in healthcare settings 3.


title: Supervision from Afar: trainees’ perspectives on telesupervision

text: Telesupervision, or supervision at a distance, has become more widely used due to its many practical and economic benefits, with research suggesting it is as satisfactory as traditional, in-person supervision processes. Particularly as a result of the global pandemic COVID-19 limiting in-person contact, use of telesupervision has even become mandatory for some training sites. In the current article, two doctoral-level clinical psychology student trainees provided their perspectives on participating in telesupervision during practicum training at a telepsychology clinic prior to COVID-19 and briefly highlighted how it has applied to their work in the current environment. Their experiences are discussed in conjunction with relevant supervision literature, as well as the impact on the trainees’ development. The trainees’ perspectives support the notion that telepsychology can be a positive component of training, irrespective of public health concerns, and specific positive factors of using telesupervision are discussed.


title: The effect of BCG vaccination on COVID-19 examined by a statistical approach: no positive results from the Diamond Princess and cross-national differences previously reported by world-wide comparisons are flawed in several ways

text: Recently, the controversial hypothesis that BCG (Bacillus Calmette-Guerin) vaccination reduces infection or severity of COVID-19 has been proposed. The present study examined this hypothesis using statistical approaches based on the public data. Three approaches were utilized: 1) comparing the infection and mortality ratio of people on the cruise ship Diamond Princess, 2) comparing the number of mortalities among nations, and 3) comparing the maximum daily increase rate of total mortalities among nations. The result of 1) showed that there is no significant difference in infection per person onboard and mortality-infection between Japanese citizens vs. other nationalities and BCG obligatory nations vs. non-BCG obligatory nations on the Diamond Princess. The result of 2) showed that the number of mortalities among nations is similar to the previous studies, but this analysis also considered the timing of COVID-19 arrival in each nation. After correcting for arrival time, previously reported effect of BCG vaccination on decreasing total mortality disappeared. This is because nations that lack BCG vaccination are concentrated in Western Europe, which is near an epicenter of COVID-19. Therefore some previous reports are now considered to be affected by this artifact; the result may have been flawed by on-land dispersal from an epicenter. However, some results showed weakly significant differences in the number of deaths at a particular time among BCG obligatory and non-BCG nations (especially the use of Japanese BCG strain Tokyo 172). However, these results are affected by the results of three countries and the effect of BCG vaccination remains inconclusive. The result of 3) showed that the maximum daily increasing rate in death among nations showed no significant difference among BCG vaccination policies. In the present study, although some results showed statistically significant differences among BCG vaccination policies, they may be affected by the impact of various other factors, such as national infection-control policies, social distancing, behavioral changes of people, possible previous local epidemics of closely related viruses, or inter-population differences in ACE2 or other genetic polymorphism. Further research is needed to better understand the underlying cause of the observed differences in infection and mortality of the disease among nations. Nevertheless, our results show that the effect of BCG vaccination, if any, can be masked by many other factors. Therefore, the possible effect might be relatively small. In fact, in Japan, where almost all citizens have been vaccinated, COVID-19 cases are constantly increasing. Given the importance of peoples behavior in preventing viral propagation, the spread of optimism triggered by this hypothesis would be harmful to BCG vaccination nations.


title: Association of Personal Protective Equipment Use with Successful Protection Against COVID-19 Infection Among Health Care Workers

text: The coronavirus disease 2019 (COVID-19) pandemic has posed a major challenge for protecting health care workers (HCWs) against the infection. Use of personal protective equipment (PPE) in health care workplace is recommended as a high priority. In order to investigate the relationship between PPE use and the number of COVID-19 cases among HCWs, we conducted a molecular epidemiological study among 142 HCWs who were dispatched from Hefei to work in Wuhan and 284 HCWs who remained in Hefei, China; both provided care for patients with COVID-19. Nucleic acid testing and SARS-CoV-2 specific antibody (IgM, IgG, IgA) detection were performed to confirm SARS-CoV-2 infection among those HCWs. We also extracted publicly released data on daily number of COVID-19 cases among HCWs, daily number of HCWs who were dispatched to Hubei province since January 24, and daily production of PPE in China and daily demand and supply of PPE in Hubei province. Our laboratory testing confirmed that none of the 142 HCWs who were dispatched to work in Wuhan and 284 HCWs who remained in Hefei were infected by SARS-CoV-2. Consistent with these findings, as of April 15, 2020, none of the 42,600 HCWs who were successively dispatched to Hubei province since January 24, 2020 was reported to have COVID-19. These HCWs were provided with adequate supply of PPE as committed by their original institutions or provinces. In contrast, during the early phase of COVID-19 epidemic in Hubei province, a substantial shortage of PPE and an increasing number of COVID-19 infection among HCWs were reported. With the continuing increase in domestic production of PPE in China, the PPE supply started to meet and then exceed the demand. This coincided with a subsequent reduction in the number of reported COVID-19 cases among HCWs. In conclusion, our findings indicate that COVID-19 infection among HCWs could be completely prevented. Appropriate and adequate PPE might play a crucial role in protecting HCWs against COVID-19 infection.


title: “Daily Work in the Fever Clinics of Wuhan Union Hospital During the Novel Coronavirus Pneumonia Epidemic: A Special Spring Festival in Wuhan, China”Medically Necessary Orthopaedic Surgery During the COVID-19 Pandemic: Safe Surgical Practices and a Classif

text: Background: Coronavirus disease 2019 (COVID-19) has rapidly evolved as a viral pandemic Countries worldwide have been affected by the recent outbreak caused by the SARS (severe acute respiratory syndrome)-CoV-2 virus As with prior viral pandemics, health-care workers are at increased risk Orthopaedic surgical procedures are common in health-care systems, ranging from emergency to elective procedures Many orthopaedic surgical procedures are life or limb-saving and cannot be postponed during the COVID-19 pandemic because of potential patient harm Our goal is to analyze how orthopaedic surgeons can perform medically necessary procedures during the pandemic and to help guide decision-making perioperatively Methods: We performed a review of the existing literature regarding COVID-19 and prior viral outbreaks to help guide clinical practice in terms of how to safely perform medically necessary orthopaedic procedures during the pandemic for both asymptomatic patients and high-risk (e g , COVID-19-positive) patients We created a classification system based on COVID-19 positivity, patient health status, and COVID-19 prevalence to help guide perioperative decision-making Results: We advocate that only urgent and emergency surgical procedures be performed By following recommendations from the American College of Surgeons, the Centers for Disease Control and Prevention, and the recent literature, safe orthopaedic surgery and perioperative care can be performed Screening measures are needed for patients and perioperative teams Surgeons and perioperative teams at risk for contracting COVID-19 should use appropriate personal protective equipment (PPE), including N95 respirators or powered air-purifying respirators (PAPRs), when risk of viral spread is high When preparing for medically necessary orthopaedic procedures during the pandemic, our classification system will help to guide decision-making A multidisciplinary care plan is needed to ensure patient safety with medically necessary orthopaedic procedures during the COVID-19 pandemic Conclusions: Orthopaedic surgery during the COVID-19 pandemic can be performed safely when medically necessary but should be rare for COVID-19-positive or high-risk patients Appropriate screening, PPE use, and multidisciplinary care will allow for safe medically necessary orthopaedic surgery to continue during the COVID-19 pandemic Level of Evidence: Prognostic Level V See Instructions for Authors for a complete description of levels of evidence Email address for I M Zeini: Ibrahim Zeini@orlandohealth com Investigation performed at Orlando Health Orthopedic Institute, Orlando, Florida, and Rothman Orthopaedics-New York, New York, NY Disclosure: The authors indicated that no external funding was received for any aspect of this work On the Disclosure of Potential Conflicts of Interest forms, which are provided with the online version of the article, one or more of the authors checked “yes” to indicate that the author had a relevant financial relationship in the biomedical arena outside the submitted work (http://links lww com/JBJS/F890) Copyright 2020 by The Journal of Bone and Joint Surgery, Incorporated


Les héros en blouse blanche et l’épidémie de coronavirus


title: The coronavirus pandemic – A critical discussion of a tourism research agenda

text: Unquestionable, the coronavirus (Covid-19) pandemic is one of the most impactful events of the 21st century and has tremendous effects on tourism. While many tourism researchers worldwide are currently ‘Covid-19 research gap spotting’, we call for more deliberateness and rigor. While we agree that the coronavirus pandemic is unique and relevant to research, we argue that not all effects are worth researching or novel to us. Previous research on crises and disasters do show similar patterns and existing theories can often very well explain the current phenomena. Thus, six illustrative examples are shown how a research agenda could look like. This includes parts where theoretical explanations from tourism are missing, as well as where we think existing knowledge might be subject to a tourism paradigm-shift due to the coronavirus pandemic.


title: Estimates of regional infectivity of COVID-19 in the United Kingdom following imposition of social distancing measures

text: We describe regional variation in the reproduction number of SARS-CoV-2 infections observed using publicly reported data in the UK, with a view to understanding both if there are clear hot spots in viral spread in the country, or if there are any clear spatial patterns. We estimate that the viral replication number remains slightly above 1 overall but that its trend is to decrease, based on case data up to the 8 April. This suggests the peak of the first wave of COVID-19 patients is imminent. We find that there is significant regional variation in different regions of the UK and that this is changing over time. Within England currently the reproductive ratio is lowest in the Midlands (1.11 95% CI 1.07; 1.14), and highest in the North East of England (1.38 95% CI 1.33-1.42). It remains unclear whether the overall reduction in the reproductive number is a result of social distancing measures, due to the long and variable time delays between infection and positive detection of cases. As we move forwards, if we are to prevent further outbreaks, it is critical that we can both reduce the time taken for detection and improve our ability to predict the regional spread of outbreaks


docid: ogrlidrs

title: Superspreading in Early Transmissions of COVID-19 in Indonesia

text: We estimate the basic reproduction number R0 and the overdispersion parameter K at two COVID-19 clusters in Indonesia: Jakarta-Depok and Batam. Based on the first 397 confirmed cases in both clusters, we find a high degree of individual-level variation in the transmission. The basic reproduction number R0 is estimated at 6.79 and 2.47, while the overdispersion parameter K of a negative-binomial distribution is estimated at 0.08 and 0.2 for Jakarta-Depok and Batam, respectively. This suggests that superspreading events played a key role in the early stage of the outbreak, i.e., a small number of infected individuals are responsible for large amounts of COVID-19 transmission.


Combating COVID-19-The role of robotics in managing public health and infectious diseases


title: Recomendaciones para el manejo de pacientes con COVID19 en el perioperatorio/ Recommendations for the management of patients with COVID19 in the perioperative period

text: En diciembre de 2019, una serie de casos de neumonía de causa desconocida surgieron en Wuhan, Hubei, China, con presentaciones clínicas muy parecidas a la neumonía viral. El análisis de secuenciación profunda de muestras del tracto respiratorio inferior indicó un nuevo coronavirus, que se denominó nuevo coronavirus 2019 (2019-nCoV o SARS-CoV2) [15]. La propagación del virus ha sido extremadamente rápida, tanto así que el 11 de marzo de 2020 y luego de más de 118.000 infectados en 114 países con 4.300 fallecidos a esa fecha, la organización mundial de la salud declaró a la enfermedad COVID-19, causada por 2019-nCoV, como una pandemia.


title: PriSeT: Efficient De Novo Primer Discovery

text: Motivation DNA metabarcoding is a commonly applied technique used to infer the species composition of environmental samples. These samples can comprise hundreds of organisms that can be closely or very distantly related in the taxonomic tree of life. DNA metabarcoding combines polymerase chain reaction (PCR) and next-generation sequencing (NGS), whereby a short, homologous sequence of DNA is amplified and sequenced from all members of the community. Sequences are then taxonomically identified based on their match to a reference database. Ideally, each species of interest would have a unique DNA barcode. This short, variable sequence needs to be flanked by relatively conserved regions that can be used as primer binding sites. Appropriate PCR primer pairs would match to a broad evolutionary range of taxa, such that we only need a few to achieve high taxonomic coverage. At the same time however, the DNA barcodes between primer pairs should be different to allow us to distinguish between species to improve resolution. This poses an interesting optimization problem. More specifically: Given a set of references ℛ = {R1, R2, …, Rm}, the problem is to find a primer set P balancing both: high taxonomic coverage and high resolution. This goal can be captured by filtering for frequent primers and ranking by coverage or variation, i.e. the number of unique barcodes. Here we present the software PriSeT, an offline primer discovery tool that is capable of processing large libraries and is robust against mislabeled or low quality references. It tackles the computationally expensive steps with linear runtime filters and efficient encodings. Results We first evaluated PriSeT on references (mostly 18S rRNA genes) from 19 clades covering eukaryotic organisms that are typical for freshwater plankton samples. PriSeT recovered several published primer sets as well as additional, more chemically suitable primer sets. For these new sets, we compared frequency, taxon coverage, and amplicon variation with published primer sets. For 11 clades we found de novo primer pairs that cover more taxa than the published ones, and for six clades de novo primers resulted in greater sequence (i.e., DNA barcode) variation. We also applied PriSeT to 19 SARS-CoV-2 genomes and computed 114 new primer pairs with the additional constraint that the sequences have no co-occurrences in other taxa. These primer sets would be suitable for empirical testing. Availability https://github.com/mariehoffmann/PriSeT Contact marie.hoffmann@fu-berlin.de


title: Predictive Model with Analysis of the Initial Spread of COVID-19 in India

text: The Coronavirus Disease 2019 (COVID-19) has currently ravaged through the world, resulting in over three million confirmed cases and over two hundred thousand deaths, a complete change in daily life as we know it, worldwide lockdowns, travel restrictions, as well as heightened hygiene measures and physical distancing. Being able to analyse and predict the spread of this epidemic-causing disease is hence of utmost importance now, especially as it would help in the reasoning behind important decisions drastically affecting countries and their people, as well as in ensuring efficient resource and utility management. However, the needs of the people and specific conditions of the spread are varying widely from country to country. In this article, we have conducted an in-depth analysis of the spread of COVID-19 in India, patient statistics, as well as proposed a mathematical prediction system that has succeeded in predicting the following day's number of cases with 83% accuracy, ever since the first COVID-19 case was declared in India.


title: Management of patients with COVID-19 in radiology departments, and indications regarding imaging studies – recommendations of the Polish Medical Society of Radiology

text: The pandemic involving COVID-19 caused by the SARS-CoV-2 coronavirus, due to its severe symptoms and high transmission rate, has gone on to pose a control challenge for healthcare systems all around the world. We present the second version of the Recommendations of the Polish Medical Society of Radiology, presuming that our knowledge on COVID-19 will advance further rapidly, to the extent that further supplementation and modification will prove necessary. These Recommendations involve rules of conduct, procedures, and safety measures that should be introduced in radiology departments, as well as indications for imaging studies.


title: Early and massive testing saves lives: COVID-19 related infections and deaths in the United States during March of 2020

text: To optimize epidemiologic interventions, predictors of mortality should be identified. The US COVID-19 epidemic data, reported up to 31 March 2020, were analyzed using kernel regularized least squares regression. Six potential predictors of mortality were investigated: (i) the number of diagnostic tests performed in testing week I; (ii) the proportion of all tests conducted during week I of testing; (iii) the cumulative number of (test-positive) cases through 3-31-2020, (iv) the number of tests performed/million citizens; (v) the cumulative number of citizens tested; and (vi) the apparent prevalence rate, defined as the number of cases/million citizens. Two metrics estimated mortality: the number of deaths and the number of deaths/million citizens. While both expressions of mortality were predicted by the case count and the apparent prevalence rate, the number of deaths/million citizens was {approx}3.5 times better predicted by the apparent prevalence rate than the number of cases. In eighteen states, early testing/million citizens/population density was inversely associated with the cumulative mortality reported by 31 March, 2020. Findings support the hypothesis that early and massive testing saves lives. Other factors --e.g., population density-- may also influence outcomes. To optimize national and local policies, the creation and dissemination of high resolution geo-referenced, epidemic data is recommended.


title: A longitudinal study of immune cells in severe COVID-19 patients.

text: Little is known about the time-dependent immune responses in severe COVID-19. Data of 15 consecutive patients were sequentially recorded from intensive care unit admission. Lymphocyte subsets and total monocyte and subsets counts were monitored as well as the expression of HLA-DR. For 5 patients, SARS-CoV-2-specific T-cell polyfunctionality was assessed against Spike and Nucleoprotein SARS-CoV-2 peptides. Non-specific inflammation markers were increased in all patients. Median monocyte HLA-DR expression was below the 8,000 AB/C threshold defining acquired immunodepression. A V trend curve for lymphopenia, monocyte numbers, and HLA-DR expression was observed with a nadir between days 11-14 after the onset of symptoms. Intermediate CD14++CD16+ monocytes increased early with a reduction in classic CD14++CD16- monocytes. Polyfunctional SARS-Cov-2-specific CD4 T-cells were present and functional, whereas virus-specific CD8 T-cells were less frequent and not efficient. We report a temporal variation of both innate and adaptive immunity in severe COVID-19 patients, helpful in guiding therapeutic decisions (e.g. anti-inflammatory vs. immunostimulatory ones). We describe a defect in virus-specific CD8 T-cells, a potential biomarker of clinical severity. These combined data also provide helpful knowledge for vaccine design.


title: Modelling daily infections with Covid-19 in Germany, France, and Sweden with a trend line based on day-to-day reproduction rates

text: The number of persons daily infected with Covid-19 as a function of time is fitted with a trend line based on an iterative power law (n = 1/4) with a day-to-day reproduction rate modelled with a polyline. From the trend line, an effective reproduction rate Reff of Covid-19 is calculated. In all three states, Reff decreases in the initial phase to one indicating that there is no exponential growth. In Sweden, a steady state with Reff around 1 and a high daily infection rates. In Germany, Reff = 1 is reached before public and private life is restricted. With these restrictions, Reff is reduced further to 0.87 (CI95 [0.83.; 0.91]) after 40 days so that, speculatively estimated, 9500 premature fatalities within two months may have been avoided. In France, it seems that only strongly restricting private life sends Reff down to 1 and further down to about 0.7 (CI95 [0.3; 1.1]) after 45 days. With Reff permanently below 1, an exponential decline of the number of daily infections is observed in Germany and France.


title: Small Diameter-Deep Hole Drilling for Hard-to-Machine Metals ― Drilling of ϕ1.0×400 mm for Ti6Al4V ―

text: Abstract Small diameter-deep hole drilling is indispensable when several main parts of which airplane, automobile, machine tool and metal mould are manufactured. Especially, medical appliances, medical implants and surgical operation tools for brain and bone invariably need small diameter-deep hole drilling for hard-to-machine metals such as stainless steel and Ti6Al4V. The authors newly designed and manufactured a small diameter-deep hole drilling machine by applying technological developments which consist of a direct drive servo spindle motor controlled more precisely, removable steady rests to prevent for a slender fluted hollow shaft of gun drill to be deflected and a highly pressure circulation system of cutting fluid to prevent being clogged with chips. By using the small diameter-deep hole drilling machine and a special gun drill (specially made to order in BOTEK) a drilling of ϕ1.0×400 mm (L/D=400) for Ti6Al4V was carried out. As a result, it was ascertained that the drilled hole has high accuracy in the items of hole diameter, concentricity, roundness and inner surface roughness.


title: Modelling Capacity on London Underground Carriages in Light of UK Government Mandated Social Distancing Rules in Response to the Covid-19 Pandemic.

text: The UK has been affected by the COVID-19 pandemic and London in particular has experienced a large number of cases. The London Underground is a key part of the transport for London. The UK Government has implemented social distancing rules meaning that people should be 2 metres from each other. The current paper models the impact of the social distancing on the carrying capacity of 10 different underground and overground carriages. The model determines the optimal standing and seating capacity for the different carriages and identifies logistical approaches to the seating and standing arrangements.


title: A brief overview of current drug repurposing approaches for COVID-19 management

text: This brief overview is intended to shed light on the current drug repositioning (also called drug repurposing) in the therapeutics of the novel coronavirus disease which emerged in 2019 (COVID-19) In this sense, the repositioning drugs for new indications can offer a better risk versus-reward trade-off when compared to other drug development strategies, given that it makes use of drugs whose safety profile are already understood Nonetheless, this approach allows healthcare professionals to promptly tackle the disease by investigating readily available drugs against it


title: The socio-economic determinants of the coronavirus disease (COVID-19) pandemic

text: The magnitude of the coronavirus disease (COVID-19) pandemic has an enormous impact on the social life and the economic activities in almost every country in the world. Besides the biological and epidemiological factors, a multitude of social and economic criteria also govern the extent of the coronavirus disease spread in the population. Consequently, there is an active debate regarding the critical socio-economic determinants that contribute to the resulting pandemic. In this paper, we contribute towards the resolution of the debate by leveraging Bayesian model averaging techniques and country level data to investigate the potential of 35 determinants, describing a diverse set of socio-economic characteristics, in explaining the coronavirus pandemic outcome.


title: COVID-19: Mandatory institutional isolation v. Voluntary home self-isolation

text: Since community transmission of COVID-19 became established in South Africa, individuals who test positive for COVID-19 and who do not require hospitalisation have been permitted to self-isolate in their homes to reduce the burden on the health system. The Premier of KwaZulu-Natal Province has since announced that self-isolation will no longer be permitted in the province. Instead, mandatory isolation in state-designated isolation sites would apply. This policy change marks a dangerous departure from the country's prevailing position on home-based self-isolation and should not be replicated elsewhere.


title: Computers against COVID-19

text: It took scientists only a few days in January to deduce the genome of the novel coronavirus, SARS-CoV-2, giving researchers around the world blueprints to the virus’s molecular tools and machinery But for computational chemists and biophysicists, the hard work is just beginning They have spent the past 2 months using those blueprints to build computer models of the virus’s proteins These models could help them figure out how the proteins interact with human cells and could help them find therapies to prevent infections or treat COVID-19, the disease caused by the virus The scientists are now beginning to deploy these carefully crafted models Accurately modeling the thousands of atoms in proteins like the polymerase that SARS-CoV-2 uses to replicate its RNA can require significant computing power The need for computing power increases further when scientists want to simulate interactions between proteins or between proteins and molecules, and it increases


title: Modeling quarantine during epidemics and mass-testing using drones

text: We extend the classical SIR epidemic spread model by introducing the "quarantined" compartment. We solve (numerically) the differential equations that govern the extended model and quantify how quarantining "flattens the curve" for the proportion of infected population over time. Furthermore, we explore the potential of using drones to deliver tests, enabling mass-testing for the infection; we give a method to estimate the drone fleet needed to deliver the tests in a metropolitan area. Application of our models to COVID-19 spread in Sweden shows how the proposed methods could substantially decrease the peak number of infected people, almost without increasing the duration of the epidemic.


docid: ryibszjm

title: Who should we test for COVID-19?A triage model built from national symptom surveys

text: The gold standard for COVID-19 diagnosis is detection of viral RNA in a reverse transcription PCR test. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential. Here, we devised a model that estimates the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions regarding age, gender, presence of prior medical conditions, general feeling, and the symptoms fever, cough, shortness of breath, sore throat and loss of taste or smell, all of which have been associated with COVID-19 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel over the past 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive. The model provides statistically significant predictions on held-out individuals and achieves a positive predictive value (PPV) of 46.3% at a 10% sensitivity. As our tool can be used online and without the need of exposure to suspected patients, it may have worldwide utility in combating COVID-19 by better directing the limited testing resources through prioritization of individuals for testing, thereby increasing the rate at which positive individuals can be identified and isolated.


title: A new era for the therapeutic management of the ongoing COVID-19 pandemic

text: Three zoonotic coronaviruses emerged at the beginning of the XXI century: SARS-CoV (Severe Acute Respiratory Syndrome coronavirus), Middle-East respiratory syndrome coronavirus (MERS-CoV) and SARS-CoV2 (previously known as 2019-nCoV), the etiologic agent of COVID 19 (Coronavirus disease) pandemic. The outbreak of the COVID-19 started in Wuhan, Hubei province, China, in December 2019 and has spread extremely fast worldwide. The World Health Organization declared it a pandemic on 11 March 2020. The present study is reviewing the background of human coronaviruses, the potential viral reservoirs, the main genomic and pathogenic aspects of SARS-CoV-2 and the actual data on the immunopathological mechanisms of COVID 19, looking towards therapeutic approaches for SARS-CoV2 infection.


title: Predication of Pandemic COVID-19 situation in Maharashtra, India

text: Presently, the world is infected by COVID 19 virus which has created an emergency public health. For controlling the spreading of the virus, we have to prepare for precaution and futuristic calculation for infection spreading. The coronavirus affects the population of the world including Inia. Here, we are the study the virus spreading rate on the Maharashtra state which is part of India. We are predicting the infected people by the SIR model. SIR model is one of the most effective models which can predict the spreading rate of the virus. We have validated the model with the current spreading rate with this SIR model. This study will help to stop the epidemic spreading because it is in the early stage in the Maharashtra region.


title: TRACKing Excess Deaths (TRACKED): an interactive online tool to monitor excess deaths associated with COVID-19 pandemic in the United Kingdom

text: Aim: We aimed to describe trends of excess mortality in the United Kingdom (UK) stratified by nation and cause of death, and to develop an online tool for reporting the most up to date data on excess mortality. Methods: Population statistics agencies in the UK including the Office for National Statistics (ONS), National Records of Scotland (NRS), and Northern Ireland Statistics and Research Agency (NISRA) publish weekly data on deaths. We used mortality data up to 22nd May in the ONS and the NISRA and 24th May in the NRS. Crude mortality for non-COVID deaths (where there is no mention of COVID-19 on the death certificate) calculated. Excess mortality defined as difference between observed mortality and expected average of mortality from previous 5 years. Results: There were 56,961 excess deaths and 8,986 were non-COVID excess deaths. England had the highest number of excess deaths per 100,000 population (85) and Northern Ireland the lowest (34). Non-COVID mortality increased from 23rd March and returned to the 5-year average on 10th May. In Scotland, where underlying cause mortality data besides COVID-related deaths was available, the percentage excess over the 8-week period when COVID-related mortality peaked was: dementia 49%, other causes 21%, circulatory diseases 10%, and cancer 5%. We developed an online tool (TRACKing Excess Deaths - TRACKED) to allow dynamic exploration and visualisation of the latest mortality trends. Conclusions: Continuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.


Experience of augmenting critical care capacity in Daegu during COVID-19 incident in South Korea


title: Immunochromatographic test for the detection of SARS-CoV-2 in saliva

text: We evaluated the rapid immunochromatographic test for SARS-CoV-2 antigen detection using 16 saliva specimens collected from 6 COVID-19 hospitalized patients, and detected N-antigen in 4 of 7 RT-PCR positive specimens. The POCT antigen test using saliva is highly considered to be a game-changer for COVID-19 diagnosis.


title: Cities and Immigrants: The Local in Anti‐Immigration Federal Policies

text: Few Americans would guess that from 2014 to 2017, Baton Rouge, Louisiana, Cincinnati, Ohio, and Greenville, South Carolina, were among the top ten metropolitan areas where population growth was attributable to immigrants (New American Economy [NAE] [27]) New York City, home to at least 3 million immigrants (Office of Immigrant Affairs [28]), is still the dominant end destination for immigrants and refugees, but not for refugees in their first placement Table 1 shows the placement of refugees by New York State metropolitan areas, the number of refugees settled in each city, and how the cities were ranked nationally by the number of refugees resettled in each from 2007 to 2016 The onslaught of the COVID-19 pandemic in the spring of 2020 will continue to slow the number of refugees entering Buffalo;the combined reaction of the federal government regarding refugee policy and the coronavirus will be felt for decades at the local level [Extracted from the article] Copyright of City & Community is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission However, users may print, download, or email articles for individual use This abstract may be abridged No warranty is given about the accuracy of the copy Users should refer to the original published version of the material for the full abstract (Copyright applies to all Abstracts )


title: Results of Multilevel Containment Measures to Better Protect Lung Cancer Patients From COVID-19: The IEO Model

text: A novel coronavirus causing severe acute respiratory syndrome (SARS), named SARS-CoV-2, was identified at the end of 2019. The spread of coronavirus disease 2019 (COVID-19) has progressively expanded from China, involving several countries throughout the world, leading to the classification of the disease as a pandemic by the World Health Organization (WHO). According to published reports, COVID-19 severity and mortality are higher in elderly patients and those with active comorbidities. In particular, lung cancer patients were reported to be at high risk of pulmonary complications related to SARS-CoV2 infection. Therefore, the management of cancer care during the COVID-19 pandemic is a crucial issue, to which national and international oncology organizations have replied with recommendations concerning patients receiving anticancer treatments, delaying follow-up visits and limiting caregiver admission to the hospitals. In this historical moment, medical oncologists are required to consider the possibility to delay active treatment administration based on a case-by-case risk/benefit evaluation. Potential risks associated with COVID-19 infection should be considered, considering tumor histology and natural course, disease setting, clinical conditions, and disease burden, together with the expected benefit, toxicities (e.g., myelosuppression or interstitial lung disease), and response obtained from the planned or ongoing treatment. In this study, we report the results of proactive measures including social media, telemedicine, and telephone triage for screening patients with lung cancer during the COVID-19 outbreak in the European Institute of Oncology (Milan, Italy). Proactive management and containment measures, applied in a structured and daily way, has significantly aided the identification of advance patients with suspected symptoms related to COVID-19, limiting their admission to our cancer center; we have thus been more able to protect other patients from possible contamination and at the same time guarantee to the suspected patients the immediate treatment and evaluation in referral hospitals for COVID-19.


docid: zduueski

title: 2019-NCOV/COVID-19 - Approaches to viral vaccine development and preventive measures

text: The severity assessment of COVID-19 and transmissibility of newly emerged novel-Coronavirus (2019-nCoV) can effectively help and support to quantify the ongoing pandemic risks. Among several epidemiological measures against COVID-19 severity, the case fatality risk (CFR) assessment is an important measure to track record the overall proportion/ratio of the cumulative number of infected patients with the known outcome (confirmed, recovered, or deceased). Considering the ongoing fatality rate, several case-based preventive measures, Coronavirus protein visualization, and approaches to viral vaccine development are discussed herein. The prompt identification of high-risk entities to confront the uncertainty in the risk of death using the approaches highlighted, herein, is of utmost requirement to tackle the current COVID-19 severity. Moreover, the protein visualization available at the viral surface/ body can give further insight into the appropriate vaccine development.


docid: piwowtxa

title: Hypertransaminasemia in the course of infection with SARS-CoV-2: Incidence and pathogenetic hypothesis

text: In patients infected with severe acute respiratory syndrome coronavirus 2, the respiratory symptoms, such as fever, cough and dyspnea, are the most frequent clinical manifestations. These patients may also present with less well-defined symptoms like diarrhea, nausea, vomiting and/or abdominal discomfort both at the time of diagnosis and during the clinical course. In a few cases, these symptoms may also present before the appearance of respiratory symptoms. To penetrate the body, Severe acute respiratory syndrome coronavirus 2 uses ACE2 receptors, which are present not only in respiratory epithelium but also in gastrointestinal mucosa and liver cholangiocytes. In several cases, viral RNA is detectable in the stool of patients with coronavirus disease 2019 (COVID-19). The liver damage seems to show a multifactorial origin. About 2%-11% of patients with COVID-19 have known underlying hepatic pathologies. In 14%-53% of COVID-19 cases, there is an alteration of the indices of liver cytolysis and is more frequently observed in severe forms of COVID-19, especially during hospitalization.


title: Nature of transmission of Covid19 in India

text: We examine available data on the number of individuals infected by the Covid-19 virus, across several different states in India, over the period January 30, 2020 to April 10, 2020. It is found that the growth of the number of infected individuals $N(t)$ can be modeled across different states with a simple linear function $N(t)=\gamma+\alpha t$ beyond the date when reasonable number of individuals were tested (and when a countrywide lockdown was imposed). The slope $\alpha$ is different for different states. Following recent work by Notari (arxiv:2003.12417), we then consider the dependency of the $\alpha$ for different states on the average maximum and minimum temperatures, the average relative humidity and the population density in each state. It turns out that like other countries, the parameter $\alpha$, which determines the rate of rise of the number of infected individuals, seems to have a weak correlation with the average maximum temperature of the state. In contrast, any significant variation of $\alpha$ with humidity or minimum temperature seems absent with almost no meaningful correlation. Expectedly, $\alpha$ increases (slightly) with increase in the population density of the states; however, the degree of correlation here too is negligible. These results seem to barely suggest that a natural cause like a hot summer (larger maximum temperatures) may contribute towards reducing the transmission of the virus, though the role of minimum temperature, humidity and population density remains somewhat obscure from the inferences which may be drawn from presently available data.


title: COVID-19 Fatality and Comorbidity Risk Factors among Confirmed Patients in Mexico

text: As of April 18, 2020, 2.16 million patients in the world had been tested positive with Coronavirus (COVID-19) and 146,088 had died, which accounts for a case fatality rate of 6.76%. In Mexico, according to official statistics (April 18), 7,497 cases have been confirmed with 650 deaths, for a case fatality rate of 8.67%. These estimates, however, may not reflect the final fatality risk among COVID-19 confirmed patients, because they are based on cross-sectional counts of diagnosed and deceased patients, and therefore are not adjusted by time of exposure and right-censorship. In this paper we estimate fatality risks based on survival analysis methods, calculated from individual-level data on symptomatic patients confirmed with COVID-19 recently released by the Mexican Ministry of Health. The estimated fatality risk after 35 days of onset of symptoms is 12.38% (95% CI: 11.37-13.47). Fatality risks sharply rise with age, and significantly increase for males (59%) and individuals with comorbidities (38%-168%, depending on the disease). Two reasons may explain the high COVID-19 related fatality risk observed in Mexico, despite its younger age structure: the high selectivity and self-selectivity in testing and the high prevalence of chronic-degenerative diseases.


title: Evaluation of hepatic enzymes changes and association with prognosis in COVID-19 patients

text: Background: One of the most critical health issues in the world is the COVID-19 pandemic from the Coronaviridae family. There is a lack of knowledge regarding the disease, and liver involvement is controversial. Objectives: We aimed to analyze the laboratory investigations of COVID-19 patients focusing on liver enzymes and association with outcomes. Methods: We enrolled 93 patients with COVID-19 referring to the Mazandaran University of Medical Sciences’ hospitals and 186 people from the normal population of Tabari Cohort. The laboratory tests included CBC, Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT), Alkaline Phosphatase (ALP), direct bilirubin, and total bilirubin. The lengths of hospital stay, critical care transfers, and deaths were the outcome measures investigated with lab results. Results: The counts of lymphocytes (833.3 ± 564.4 vs. 2465.1 ± 796.6 per mm 3, P < 0.001) and platelets (209.4 ± 62.7 vs. 255.2 ± 63.8 per mm 3, P < 0.001) were significantly lower in patients than in controls. Also, AST (39.5 ± 34.9 vs. 19.9 ± 7.5 U/L, P < 0.001), ALT (40.4 ± 46.5 vs. 21.6 ± 12.7 U/L, P < 0.001), and ALP (192.6 ± 91.2 vs. 222.2 ± 70.6 U/L, P = 0.004) were higher in patients than in controls. The most common hepatic impairment events were increased direct bilirubin (45.8%), ALT (30.3%), AST (29.2%), ALP (17%), and total bilirubin (10.2%), in sequence. The risk of transfer to intensive and critical care units was strongly associated with elevated levels of AST and direct bilirubin, and AST = 30.5 (U/L) had a sensitivity of 71.4% and specificity of 68.5% for critical and intensive care transfer. The mortality rate significantly increased with increased AST levels (P = 0.023). Conclusions: Abnormal liver enzymes are frequent in COVID-19 patients. As AST is not specific for liver damage, the systemic inflammation induced by the virus might be responsible for these findings.


title: CD13 is a Critical Regulator of Cell-cell Fusion in Osteoclastogenesis

text: In vertebrates, bone formation is dynamically controlled by the activity of two specialized cell types: the bone-generating osteoblasts and bone-degrading osteoclasts. Osteoblasts produce the soluble receptor activator of NFκB ligand (RANKL) that binds to its receptor RANK on the surface of osteoclast precursor cells to promote osteoclastogenesis, a process that involves cell-cell fusion and assembly of molecular machinery to ultimately degrade the bone. CD13 is a transmembrane aminopeptidase that is highly expressed in cells of myeloid lineage has been shown to regulate dynamin-dependent receptor endocytosis and recycling and is a necessary component of actin cytoskeletal organization. In the present study, we show that CD13-deficient mice display a normal distribution of osteoclast progenitor populations in the bone marrow, but present a low bone density phenotype. Further, the endosteal bone formation rate is similar between genotypes, indicating a defect in osteoclast-specific function in vivo. Loss of CD13 led to exaggerated in vitro osteoclastogenesis as indicated by significantly enhanced fusion of bone marrow-derived multinucleated osteoclasts in the presence of M-CSF and RANKL, resulting in abnormally large cells with remarkably high numbers of nuclei with a concomitant increase in bone resorption activity. Similarly, we also observed increased formation of multinucleated giant cells (MGC) in CD13KO bone marrow progenitor cells stimulated with IL-4 and IL-13, suggesting that CD13 may regulate cell-cell fusion events via a common pathway, independent of RANKL signaling. Mechanistically, while expression levels of the fusion-regulatory proteins dynamin and DC-STAMP are normally downregulated as fusion progresses in fusion-competent mononucleated progenitor cells, in the absence of CD13 they are uniformly sustained at high levels, even in mature multi-nucleated osteoclasts. Taken together, we conclude that CD13 may regulate cell-cell fusion by controlling expression and localization of key fusion proteins that are critical for both osteoclast and MGC fusion.


title: Role of changes in SARS-CoV-2 spike protein in the interaction with the human ACE2 receptor: An in silico analysis

text: Many human viral diseases are a consequence of a zoonotic event. Some of the diseases caused by these zoonotic events have affected millions of people around the world, some of which have resulted in high rates of morbidity/mortality in humans. Changes in the viral proteins that function as ligands of the host receptor may promote the spillover between species. The most recent of these zoonotic events that have caused an ongoing epidemic of high magnitude is the Covid-19 epidemics caused by SARS-CoV-2. The aim of this study was to determine the mutation(s) in the sequence of the spike protein of the SARS-CoV-2 that might be favoring human to human transmission. An in silico approach was performed, and changes were detected in the S1 subunit of the receptor-binding domain of spike. The observed changes have significant effect on SARS-CoV-2 spike/ACE2 interaction and produce a reduction in the binding energy, compared to the one of the Bat-CoV to this receptor. The data presented in this study suggest a higher affinity of the SARS-Cov-2 spike protein to the human ACE2 receptor, compared to the one of Bat-CoV spike and ACE2. This could be the cause of the rapid viral spread of SARS-CoV-2 in humans.


title: SARS-CoV-2 exhibits intra-host genomic plasticity and low-frequency polymorphic quasispecies

text: In December 2019, an outbreak of atypical pneumonia (Coronavirus disease 2019 - COVID-19) associated with a novel coronavirus (SARS-CoV-2) was reported in Wuhan city, Hubei province, China. The outbreak was traced to a seafood wholesale market and human to human transmission was confirmed. The rapid spread and the death toll of the new epidemic warrants immediate intervention. The intra-host genomic variability of SARS-CoV-2 plays a pivotal role in the development of effective antiviral agents and vaccines, but also in the design of accurate diagnostics. We analyzed NGS data derived from clinical samples of three Chinese patients infected with SARS-CoV-2, in order to identify small- and large-scale intra-host variations in the viral genome. We identified tens of low- or higher-frequency single nucleotide variations (SNVs) with variable density across the viral genome, affecting 7 out of 10 protein-coding viral genes. The majority of these SNVs corresponded to missense changes. The annotation of the identified SNVs but also of all currently circulating strain variations revealed colocalization of intra-host but also strain specific SNVs with primers and probes currently used in molecular diagnostics assays. Moreover, we de-novo assembled the viral genome, in order to isolate and validate intra-host structural variations and recombination breakpoints. The bioinformatics analysis disclosed genomic rearrangements over poly-A / poly-U regions located in ORF1ab and spike (S) gene, including a potential recombination hot-spot within S gene. Our results highlight the intra-host genomic diversity and plasticity of SARS-CoV-2, pointing out genomic regions that are prone to alterations. The isolated SNVs and genomic rearrangements, reflect the intra-patient capacity of the polymorphic quasispecies, which may arise rapidly during the outbreak, allowing immunological escape of the virus, offering resistance to anti-viral drugs and affecting the sensitivity of the molecular diagnostics assays.


title: Deep learning for detecting corona virus disease 2019 (COVID-19) on high-resolution computed tomography: A pilot study

text: Background: To evaluate the diagnostic efficacy of Densely Connected Convolutional Networks (DenseNet) for detection of COVID-19 features on high resolution computed tomography (HRCT). Methods: The Ethic Committee of our institution approved the protocol of this study and waived the requirement for patient informed consent. Two hundreds and ninety-five patients were enrolled in this study (healthy person: 149; COVID-19 patients: 146), which were divided into three separate non-overlapping cohorts (training set, n=135, healthy person, n=69, patients, n=66; validation set, n=20, healthy person, n=10, patients, n=10; test set, n=140, healthy person, n=70, patients, n=70). The DenseNet was trained and tested to classify the images as having manifestation of COVID-19 or as healthy. A radiologist also blindly evaluated all the test images and rechecked the misdiagnosed cases by DenseNet. Receiver operating characteristic curves (ROC) and areas under the curve (AUCs) were used to assess the model performance. The sensitivity, specificity and accuracy of DenseNet model and radiologist were also calculated. Results: The DenseNet algorithm model yielded an AUC of 0.99 (95% CI: 0.958-1.0) in the validation set and 0.98 (95% CI: 0.972-0.995) in the test set. The threshold value was selected as 0.8, while for validation and test sets, the accuracies were 95% and 92%, the sensitivities were 100% and 97%, the specificities were 90% and 87%, and the F1 values were 95% and 93%, respectively. The sensitivity of radiologist was 94%, the specificity was 96%, while the accuracy was 95%. Conclusions: Deep learning (DL) with DenseNet can accurately classify COVID-19 on HRCT with an AUC of 0.98, which can reduce the miss diagnosis rate (combined with radiologists' evaluation) and radiologists' workload.