bluuebunny/crossref_metadata_2025 huggingface dataset:
Psychological Distress Among People Losing Work During the COVID-19 Pandemic in Australia
Authors: Collie Alex , Sheehan Luke , Vreden Caryn van , Grant Genevieve , Whiteford Peter , Petrie Dennis , Sim Malcolm R
Published: May 2020

Introduction

This study estimated the extent of psychological distress among people losing work during the coronavirus disease of 2019 (COVID-19) pandemic in Australia, and examined associations between distress, nature of work loss and degree of social interaction.

Methods

Data were from a baseline online survey of an inception cohort recruited in the weeks following the introduction of physical distancing and movement restrictions to contain the spread of COVID-19 in Australia. These restrictions resulted in widespread unemployment and working hour reduction. Psychological distress was measured using the Kessler-6 scale. Data on nature of work loss, social interactions, demographic, job and occupational characteristics were also collected. Regression modelling was conducted to determine the relationship between work loss, social interactions and psychological distress, accounting for confounders.

Results

Among the 551 study participants 31% reported severe psychological distress, 35% in those with job loss and 28% in those still employed but working less. Those who had significantly greater odds of high psychological distress were younger, female, had lost their job and had lower social interactions. The relationship between job loss and distress became non-significant when financial stress, and occupation were included in the regression model, but the protective effect of higher social interactions remained significant.

Discussion

There was a high prevalence of psychological distress in people losing work during the coronavirus pandemic. Age, gender, job loss and social interactions were strongly associated with distress. Interventions that promote social interaction may help to reduce distress during among people losing work during the COVID-19 pandemic.
Predicted success of prophylactic antiviral therapy to block or delay SARS-CoV-2 infection depends on the drug’s mechanism of action
Authors: Czuppon Peter , Débarre Florence , Gonçalves Antonio , Tenaillon Olivier , Perelson Alan S. , Guedj Jérémie , Blanquart François
Published: May 2020

Repurposed drugs that are immediately available and safe to use constitute a first line of defense against new viral infections. Despite limited antiviral activity against SARS-CoV-2, several drugs are being tested as medication or as prophylaxis to prevent infection. Using a stochastic model of early phase infection, we find that a critical efficacy above 87% is needed to block viral establishment. This can be improved by combination therapy. Below the critical efficacy, establishment of infection can sometimes be prevented, most effectively with drugs blocking viral entry into cells or enhancing viral clearance. Even when a viral infection cannot be prevented, antivirals delay the time to detectable viral loads. This delay flattens the within-host viral dynamic curve, possibly reducing transmission and symptom severity. Thus, antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk.
Systematic Review and Meta-analysis of the Effectiveness and Safety of Hydroxychloroquine in COVID-19
Authors: Yang Tzu-Han , Chou Chian-Yin , Yang Yi-Fan , Yang Yi-Ping , Chien Chian-Shiu , Yarmishyn Aliaksandr A. , Yang Tzu-Ying , Chiou Shih-Hwa , Chang Yuh-Lih
Published: May 2020

Backgrounds

Since COVID-19 outbreak, various agents have been tested but no proven effective therapies have been identified. This has led to a lot of controversies among associated researches. Hence, in order to address the issue of using hydroxychloroquine in treating COVID-19 patients, we conducted a systematic review and meta-analysis.

Methods

A thorough search was carried out to find relevant studies in MEDLINE, medRxiv, PubMed, Cochrane Database, China Academic Journals Full-text Database and Web of Science. Two investigators independently reviewed 274 abstracts and 23 articles. The trials which evaluated hydroxychloroquine for treatment of COVID-19 were included for this systematic review. Two investigators assessed quality of the studies and data extraction was done by one reviewer and cross checked by the other.

Results

Five trials involving 677 patients were included while conducting the meta-analysis. Compared with the control group, hydroxychloroquine with or without azithromycin showed benefits in positive-to-negative conversion of SARS-CoV-2 (odds ratio [OR], 1.95 [95% CI,0.19 to 19.73] and a reduction in progression rate (OR, 0.89 [95% CI, 0.58 to 1.37]), but without demonstrating any statistical significance. This systematic review has also suggested a possible synergistic effect of the combination therapy which included hydroxychloroquine and azithromycin. However, the use of hydroxychloroquine alone was associated with increased mortality in COVID-19 patients.

Conclusion

The use of hydroxychloroquine with or without azithromycin for treatment of COVID-19 patients, seems to be effective. The combination of hydroxychloroquine and azithromycin has shown synergic effects. However, mortality rate was increased when the treatment was conducted with hydroxychloroquine.
Remdesivir in treatment of COVID-19: A systematic benefit-risk assessment
Authors: Davies Miranda , Osborne Vicki , Lane Samantha , Roy Debabrata , Dhanda Sandeep , Evans Alison , Shakir Saad
Published: May 2020

Background

There is a need to identify effective, safe treatments for COVID-19 (coronavirus disease) rapidly, given the current, ongoing pandemic. A systematic benefit-risk assessment was designed and conducted to strengthen the ongoing understanding of the benefit-risk balance for remdesivir in COVID-19 treatment by using a structured method which uses all available data.

Methods

The Benefit-Risk Action Team (BRAT) framework was used to assess the overall benefit-risk of the use of remdesivir as a treatment for COVID-19 compared to standard of care, placebo or other treatments. We searched PubMed,Google Scholar and government agency websites to identify literature reporting clinical outcomes in patients taking remdesivir for COVID-19. A value tree was constructed and key benefits and risks were ranked by two clinicians in order of considered importance.

Results

Several key benefits and risks for use of remdesivir in COVID-19 compared to placebo have been identified. In one trial, the benefit of time to clinical improvement was not statistically significant (21 vs 23 days, HR=1.23, 95% CI: 0.87, 1.75), although the study was underpowered. In another trial, a shorter time to recovery in patients treated with remdesivir was observed (11 vs 15 days), with non-significant reduced mortality risk (8% vs 12%). Risk data were only available from one trial. This trial reported fewer serious adverse events in patients taking remdesivir (18%) comparted to the placebo group (26%), however more patients in the remdesivir group discontinued treatment as a result of an adverse event compared to those patients receiving placebo (12% vs 5%).

Conclusions

Preliminary clinical trial results suggest a favourable benefit-risk profile for remdesivir compared to placebo, however there is limited safety data available at the current time. The current framework summarises the key anticipated benefits and risks for which further data are needed. Ongoing clinical trial data can be incorporated into the framework when available to provide an updated benefit-risk assessment.
Systematic benefit-risk assessment for the use of chloroquine or hydroxychloroquine as a treatment for COVID-19: Establishing a dynamic framework for rapid decision-making
Authors: Osborne Vicki , Davies Miranda , Dhanda Sandeep , Roy Debabrata , Lane Samantha , Evans Alison , Shakir Saad
Published: May 2020

Objectives

Given the current pandemic, there is an urgent need to identify effective, safe treatments for COVID-19 (coronavirus disease). A systematic benefit-risk assessment was designed and conducted to strengthen the ongoing monitoring of the benefit-risk balance for chloroquine (CQ) and hydroxychloroquine (HCQ) in COVID-19 treatment.

Methods

The overall benefit-risk of the use of chloroquine or hydroxychloroquine as a treatment for COVID-19 compared to standard of care, placebo or other treatments was assessed using the Benefit-Risk Action Team (BRAT) framework. We searched PubMed and Google Scholar to identify literature reporting clinical outcomes in patients taking chloroquine or hydroxychloroquine for COVID-19. A value tree was constructed and key benefits and risks were ranked by two clinicians in order of considered importance.

Results

Several potential key benefits and risks were identified for use of hydroxychloroquine or chloroquine in COVID-19 treatment. Currently available results did not show an improvement in mortality risk; Cox proportional hazard ratio (HR) for death between patients who received HCQ alone vs. neither hydroxychloroquine or azithromycin was 1.08 (95% CI 0.63-1.85). A further study compared the incidence of intubation or death (composite outcome) in a time to event analysis between patients who received HCQ vs. those patients who did not (adjusted Cox proportional HR 1.00 (95% CI 0.76-1.32)). Risk of cardiac arrest, abnormal electrocardiogram (ECG) and QT prolongation was greater among patients taking HCQ (with or without azithromycin) compared to standard of care in the same study.

Conclusions

Overall, based on the available data there does not appear to be a favourable benefit-risk profile for chloroquine or hydroxychloroquine compared to standard of care in treatment of severe COVID-19. As further data from clinical trials and real world use on these benefits and risks becomes available, this can be incorporated into the framework for an ongoing benefit-risk assessment.
Automated recognition of ultrasound cardiac views based on deep learning with graph constraint
Authors: Gao Yanhua , Zhu Yuan , Liu Bo , Hu Yue , Guo Youmin
Published: May 2020

Objective

In Transthoracic echocardiographic (TTE) examination, it is essential to identify the cardiac views accurately. Computer-aided recognition is expected to improve the accuracy of the TTE examination.

Methods

This paper proposes a new method for automatic recognition of cardiac views based on deep learning, including three strategies. First, A spatial transform network is performed to learn cardiac shape changes during the cardiac cycle, which reduces intra-class variability. Second, a channel attention mechanism is introduced to adaptively recalibrates channel-wise feature responses. Finally, unlike conventional deep learning methods, which learned each input images individually, the structured signals are applied by a graph of similarities among images. These signals are transformed into the graph-based image embedding, which act as unsupervised regularization constraints to improve the generalization accuracy.

Results

The proposed method was trained and tested in 171792 cardiac images from 584 subjects. Compared with the known result of the state of the art, the overall accuracy of the proposed method on cardiac image classification is 99.10% vs. 91.7%, and the mean AUC is 99.36%. Moreover, the overall accuracy is 98.15%, and the mean AUC is 98.96% on an independent test set with 34211 images from 100 subjects.

Conclusion

The method of this paper achieved the results of the state of the art, which is expected to be an automated recognition tool for cardiac views recognition. The work confirms the potential of deep learning on ultrasound medicine.
Calcification of abdominal aorta is an underappreciated cardiovascular disease risk factor
Authors: Sethi Anurag , Taylor Leland , Ruby J Graham , Venkataraman Jagadish , Cule Madeleine , Melamud Eugene
Published: May 2020

Background

Calcification of the abdominal artery is an important contributor to cardiovascular disease in diabetic and chronic kidney disease (CKD) populations. However, prevalence of the pathology, risk factors, and long term disease outcomes in a general population have not been systematically analyzed.

Method

We developed machine learning models to quantify levels of abdominal aortic calcification (AAC) in 29,957 whole body dual-energy X-ray absorptiometry (DEXA) scans from the UK Biobank cohort. Using regression techniques we associated severity of calcification across a wide range of physiological parameters, clinical biomarkers, and environmental risk factors (406 in total). We performed a common variant genetic association study spanning 9,572,557 single-nucleotide polymorphisms to identify genetic loci relevant to AAC. We evaluated the prognostic value of AAC across 151 disease classes using Cox proportional hazard models. We further examined an epidemiological model of calcification on cardiovascular morbidity with and without LDL interactions.

Findings

We find evidence for AAC in >10.4% of the cohort despite low prevalence of diabetes (2.5%) and CKD (0.5%). Increased level of AAC is a strong prognostic indicator of cardiovascular outcomes for stenosis of precerebral arteries (HR~1.5), Myocardial Infarction (HR~1.5), & Ischemic Heart Disease (HR~1.33). We find that AAC is genetically correlated with cardiovascular-related traits and that the genetic signals are enriched in vascular and adipose tissue. We report three loci associated with AAC, with the strongest association occuring at theTWIST1/HDAC9locus (beta=0.078, p-value=1.4e-11) in a region also associated with coronary artery disease. Surprisingly, we find that elevated but still within clinically normal levels of serum phosphate and glycated hemoglobin are linked to increased vascular calcification. Furthermore, we show AAC arises in the absence of hypercholesterolemia. By our estimate, AAC is an LDL-independent risk factor for cardiovascular outcomes, with risk similar to elevated LDL.

Data

This research has been conducted using the UK Biobank Resource.
Quantitative COVID-19 infectiousness estimate correlating with viral shedding and culturability suggests 68% pre-symptomatic transmissions
Authors: Prakash Meher K.
Published: May 2020

A person clinically diagnosed with COVID 19 can infect others for several days before and after the onset of symptoms. At the epidemiological level, this information on how infectious someone is lies embedded implicitly in the serial interval data. Other clinical indicators of infectiousness based on the temporal kinetics of the viral shedding from the nasopharyngeal swabs and sputum show the former decaying weeks sooner than the latter. In this work, we attempt to provide a better quantitative estimate for the temporal infectiousness profile using serial interval data from a combined 1251 individuals reported in the literature. We show that the infectiousness profile which we calculate correlates well with the viral shedding kinetics from nasopharyngeal swabs (ρ=0.97, p=0.00) and culturability (ρ=0.83, p=0.01). The profile suggests that a 68.4% (95% CI: 67.0-69.7%) of the infections are caused by infections before the symptoms appear, which is a much stronger pre-symptomatic influence than what was predicted in the literature 44% (95% CI: 25-69%) using serial data from 77 individuals.
Outcomes among HIV-positive patients hospitalized with COVID-19
Authors: Karmen-Tuohy Savannah , Carlucci Philip M. , Zacharioudakis Ioannis M. , Zervou Fainareti N. , Rebick Gabriel , Klein Elizabeth , Reich Jenna , Jones Simon , Rahimian Joseph
Published: May 2020

Background

SARS-CoV-2 infection continues to cause significant morbidity and mortality worldwide. Preliminary data on SARS-CoV-2 infection suggests that some immunocompromised hosts experience worse outcomes. We performed a retrospective matched cohort study to characterize outcomes in HIV-positive patients with SARS-CoV-2 infection.

Methods

Leveraging data collected from electronic medical records for all patients hospitalized at NYU Langone Health with COVID-19 between March 2, 2020 and April 23, 2020, we matched 21 HIV-positive patients to 42 non-HIV patients using a greedy nearest neighbor algorithm. Admission characteristics, laboratory results, and hospital outcomes were recorded and compared between the two groups.

Results

While there was a trend toward increased rates of ICU admission, mechanical ventilation, and mortality in HIV-positive patients, these differences were not statistically significant. Rates for these outcomes in our cohort are similar to those previously published for all patients hospitalized with COVID-19. HIV-positive patients had significantly higher admission and peak CRP values. Other inflammatory markers did not differ significantly between groups, though HIV-positive patients tended to have higher peak values during their clinical course. Three HIV-positive patients had superimposed bacterial pneumonia with positive sputum cultures, and all three patients expired during hospitalization. There was no difference in frequency of thrombotic events or myocardial infarction between these groups.

Conclusion

This study provides evidence that HIV coinfection does not significantly impact presentation, hospital course, or outcomes of patients infected with SARS-CoV-2, when compared to matched non-HIV patients. A larger study is required to determine if the trends we observed apply to all HIV-positive patients.
Compassionate drug (mis)use during pandemics: lessons for COVID-19 from 2009
Authors: Rojek Amanda M , Martin Genevieve E , Horby Peter W
Published: May 2020

Background

New emerging infections have no known treatment. Assessing potential drugs for safety and efficacy enables clinicians to make evidence-based treatment decisions, and contributes to overall outbreak control. However, it is difficult to launch clinical trials in the unpredictable environment of an outbreak. We conducted a bibliometric systematic review for the 2009 influenza pandemic to determine the speed, and quality of evidence generation for treatments. This informs approaches to high-quality evidence generation in this and future pandemics.

Methods

We searched PubMed for all clinical data (including clinical trial, observational and case series) describing treatment for patients with influenza A(H1N1)pdm09 and ClinicalTrials.gov for research that aimed to enrol patients with the disease.

Findings

33869 treatment courses for patients hospitalised with A(H1N1)pdm09 were detailed in 160 publications. Most were retrospective observational studies or case series. 592 patients received treatment (or placebo) as participants in a registered interventional clinical trial with results publicly available. None of these registered trial results were available during the timeframe of the pandemic, and the median date of publication was 213 days after the Public Health Emergency of International Concern ended.

Interpretation

Patients were frequently treated for pandemic influenza with drugs not registered for this indication, but rarely under circumstances of high-quality data capture. The result was a reliance on use under compassionate circumstances, resulting in continued uncertainty regarding the potential benefits and harms of anti-viral treatment. Rapid scaling of clinical trials is critical for generating a quality evidence base during pandemics.

Funding

Wellcome Trust.
Gut microbiota impairs insulin clearance during obesity
Authors: Foley Kevin P. , Zlitni Soumaya , Duggan Brittany M. , Barra Nicole G. , Anhê Fernando F. , Cavallari Joseph F. , Henriksbo Brandyn D. , Chen Cassandra Y. , Huang Michael , Lau Trevor C. , Schertzer Jonathan D.
Published: May 2020

Hyperinsulinemia can be a cause and consequence of obesity and insulin resistance. Increased insulin secretion and reduced insulin clearance can contribute to hyperinsulinemia. The triggers for changes in insulin clearance during obesity are ill-defined. We found that oral antibiotics mitigated impaired insulin clearance in mice fed a high fat diet (HFD) for 12 weeks or longer. Short-term HFD feeding and aging did not alter insulin clearance in mice. Germ-free mice colonized with microbes from HFD-fed mice had impaired insulin clearance, but not C-peptide clearance, and only after mice were colonized for 6 weeks and then HFD-fed. Five bacterial taxa predicted >90% of the variance in insulin clearance. Our data indicate that gut microbes are an independent and transmissible factor that regulates obesity-induced changes in insulin clearance. A small cluster of microbes may be a target for mitigating defects in insulin clearance and the progression of obesity and Type 2 Diabetes. We propose that a small community in the gut microbiota can impair insulin clearance and increase insulin load and the risk of complications from hyperinsulinemia.
Drive-through testing for SARS-CoV-2 in symptomatic health and social care workers and household members: an observational cohort study in Tayside, Scotland
Authors: Parcell Benjamin , Brechin Kathryn , Allstaff Sarah , Park Meg , Third Wendy , Bean Susan , Hind Chris , Farmer Rajiv , Chalmers James D
Published: May 2020

It has been recognised that health and social care workers (HSCW) experience higher rates of infection with SARS-CoV-2. Widespread testing of HSCWs and their symptomatic household contacts (SHCs) has not been fully implemented in the United Kingdom. We describe the results of a testing programme for HSCWs and SHCs in a single UK region (Tayside, Scotland). The testing service was established 17 th March 2020 as the first in the country, and samples were collected at a drive-through testing hub based at a local community hospital. HSCWs with mild symptoms who were self-isolating and the SHCs of HSCWs who would therefore be absent from work attended for testing. From 17 th March 2020 to 11 th April, 1887 HSCWs and SHCs underwent testing. Clinical information was available for 1727 HSCWs and SHCs. 4/155 (2.6%) child contacts, 73/374 (19.5%) adult contacts and 325/1173 (27.7%) HSCWs tested positive for SARS-CoV-2. 15 of 188 undetermined cases were positive (8.0%). We estimate that testing prevented up to 3634 lost work days from HSCW testing, 2795 from adult SHC testing and 1402 lost work days from child SHC testing. The establishment of this testing programme has assisted the infection prevention and control team in their investigation of transmission and supported adequate staffing in health and social care sectors.
Estimation of the number of general anesthesia cases based on a series of nationwide surveys on Twitter during COVID-19 in Japan: A statistical analysis
Authors: Fujii Yosuke , Daijo Hiroki , Hirota Kiichi
Published: May 2020

Purpose

The coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to more than 200 other countries. In light of this situation, the Japanese Government declared a state of emergency in seven regions of Japan on April 7, 2020, under the provisions of the law. The medical care delivery system has been under pressure. Although various surgical societies have published guidelines on which to base their surgical decisions, it is not clear how general anesthesia has been performed and will be performed in Japan.

Methods

One of the services provided by Twitter is a voting function—Twitter Polls—through which anonymous surveys can be conducted. We used quadratic programming to analyze the results of a series of 17 surveys on Twitter, over the course of 22 weeks. The analysis focused on solving the mathematical optimizing problem on the status of operating restrictions. Public data provided by the Japanese Government were used to estimate the current changes in the number of general anesthesia performed in Japan.

Results

The minimum number of general anesthesia per week was estimated at 66.1%, compared to 2015, on April 27, 2020. The time series trend was compatible with the results reported by the Japanese Society of Anesthesiologists.

Conclusion

The number of general anesthesia was reduced by up to two-thirds during the COVID-19 pandemic in Japan, and was quantitatively estimated using the Twitter quick questionnaire.
Lactate arterial-central venous gradient among COVID-19 patients in ICU: a potential tool in the clinical practice
Authors: Nardi Giuseppe , Sanson Gianfranco , Tassinari Lucia , Guiotto Giovanna , Potalivo Antonella , Montomoli Jonathan , Schiraldi Fernando
Published: May 2020

Objective

In physiological conditions arterial blood lactate concentration is equal or lower than central venous. The aim of this study was to explore if the COVID-19 induced lung cells damage was mirrored by an arterial lactatemia higher than the central venous one; then if the administration of immunosuppressant drugs (i.e. canakinumab) could normalize such abnormal lactate a-cv difference.

Methods

Prospective cohort study started on March 25th 2020 for a duration of 10 days, enrolling 21 patients affected by severe COVID-19 pneumonia undergoing mechanical ventilation consecutively admitted to the ICU of the Rimini Hospital, Italy.

Arterial and central venous blood samples were contemporary collected to calculate the difference between arterial and central venous lactate (Delta a-cv lactate) concentration within 24 h from tracheal intubation (T0), and 24 hours after canakinumab administration (T1).

Results

At the T0 19/21 (90.5%) patients showed a pathologic Delta a-cv lactate (median 0.22 mmol/L; IQR 0.07–0.36), suggesting severe inflammation. In the 13 patients undergoing canakinumab administration, at the T1 Delta a-cv lactate decreased in 92.3% of cases, being the decrease statistically significant (T0: median 0.15, IQR 0.07–0.25 mmol/L; T1: median −0.01, IQR 0.09–0.04 mmol/L; p=0.002).

Conclusion

A reversed Delta a-cv lactate is likely to be one of the effects of COVID-19 related cytokine storm, that could reflect a derangement in the lung cells mitochondrial metabolism induced by inflammation or other uncoupling mediators. Delta a-cv lactate decrease may reflect the anti-inflammatory activity of canakinumab. Our preliminary findings need to be confirmed by larger outcome studies.
COVID-19 transmission risk factors
Authors: Notari Alessio , Torrieri Giorgio
Published: May 2020

We analyze risk factors correlated with the initial transmission growth rate of the recent COVID-19 pandemic in different countries. The number of cases follows in its early stages an almost exponential expansion; we chose as a starting point in each country the first daydiwith 30 cases and we fitted for 12 days, capturing thus the early exponential growth. We looked then for linear correlations of the exponentsαwith other variables, for a sample of 126 countries. We find a positive correlation,i.e. faster spread of COVID-19, with high confidence level with the following variables, with respectivep-value: low Temperature (4 · 10−7), high ratio of old vs. working-age people (3 · 10−6), life expectancy (8 · 10−6), number of international tourists (1· 10−5), earlier epidemic starting datedi(2· 10−5), high level of physical contact in greeting habits (6 · 10−5), lung cancer prevalence (6 · 10−5), obesity in males (1· 10−4), share of population in urban areas (2· 10−4), cancer prevalence (3· 10−4), alcohol consumption (0.0019), daily smoking prevalence (0.0036), UV index (0.004, 73 countries). We also find a correlation with low Vitamin D serum levels (0.002—0.006), but on a smaller sample, 50 countries, to be confirmed on a larger sample. There is highly significant correlation also with blood types: positive correlation with types RH-(3· 10−5) and A+ (3 ·10−3), negative correlation with B+ (2 ·10−4). We also find positive correlation with moderate confidence level (p-value of 0.02∼ 0.03) with: CO2/SO emissions, type-1 diabetes in children, low vaccination coverage for Tuberculosis (BCG). Several of the above variables are correlated with each other and so they are likely to have common interpretations. We thus performed a Principal Component Analysis, in order to find the significant independent linear combinations of such variables. We also analyzed the possible existence of a bias: countries with low GDP-per capita might have less intense testing and we discuss correlation with the above variables.
A two-wave epidemiological model of COVID-19 outbreaks using MS-Excel®
Authors: De Noni Agenor , da Silva Bernardo Araldi , Dal-Pizzol Felipe , Porto Luismar Marques
Published: May 2020

The emergence of the coronavirus SARS-CoV-2 has raised a global issue and a pandemic disease outbreak, COVID-19, was declared by the World Health Organization on March 12th, 2020. The new virus is rapidly spreading in humans and cases of severe acute respiratory syndromes are being reported worldwide. Health authority advisors and governments from small towns to large countries need to quickly manage and deal with growing epidemiological data on a daily basis. In this work, current available data from reported cases and deaths over time were analyzed and treated. Lethality has been calculated by finding linearization of death cases against reported ones, using a time-delayed data transposition. A two-wave statistical model, 2WM, based on the superposition of normal distributions was used to fit current data and to estimate the evolution of infections and deaths, using Microsoft® Excel. The model showed good agreement even for apparent single wave behavior in some countries and can easily be extended to any number of waves. A gamma distribution was used as a risk function to estimate death probability from patient admission to reported death. Evolution of fatality cases over time can then be estimated from the model with reasonable accuracy. Data from South Korea, China, Australia, Germany, Italy and Spain were used to validate the model. Data from The United States, United Kingdom and Brazil were used to study the epidemiology as the pandemic progresses. Additionally, the 2WM was applied to world data and to the Brazilian state of Santa Catarina. The model was implemented in MS-Excel, a popular and easy to use analytical tool. A template spreadsheet is provided as supplementary material. Constant lethality can be determined from the initial stage of the pandemic wave. Values ranged from 1.7% to 15.3%, depending on the degree of possible sub notification cases. Even for places with low testing, a linear relationship can be found. The two-wave model can be fine-tuned to properly adjust the data. The second wave pattern was estimated according to the first wave parameter. The accuracy for estimating COVID-19 evolution was compared to the classic SIR model with good agreement. According to the model, based on current trends, health protocols and policies, approximately 10,000,000 cases and 860,000 deaths will be recorded worldwide. Approximately 99% of that number would be reached by the end of July 2020 given constant conditions.
Tracking multi-site seizure propagation using ictal high frequency activity
Authors: Tobochnik Steven , Bateman Lisa M. , Akman Cigdem I. , Anbarasan Deepti , Bazil Carl W. , Bell Michelle , Choi Hyunmi , Feldstein Neil A. , Kent Paul F. , McBrian Danielle , McKhann Guy M. , Mendiratta Anil , Pack Alison M. , Sands Tristan T. , Sheth Sameer A. , Srinivasan Shraddha , Schevon Catherine A.
Published: May 2020

Objective

Characterization of progressive multi-site seizure recruitment using high frequency oscillations.

Methods

Ictal and interictal high frequency oscillations were identified in a series of 13 patients with 72 seizures recorded by stereotactic depth electrodes, using previously validated methods. Channels with ictal high frequency oscillations were assigned to distinct spatial clusters, and seizure hubs were identified by stereotypically recruited non-overlapping clusters. Clusters were correlated with asynchronous seizure terminations to provide supportive evidence for independent seizure activity at these sites. The spatial overlap of ictal and interictal high frequency oscillations were compared.

Results

Ictal high frequency oscillations were detected in 71% of seizures and 10% of implanted contacts, enabling tracking of contiguous and noncontiguous seizure recruitment. Multiple seizure hubs were identified in 54% of cases, including 43% of patients thought preoperatively to have unifocal epilepsy. Noncontiguous recruitment was associated with asynchronous seizure termination (Odds Ratio=10, 95% CI 2.9-41, p<0.001). Interictal high frequency oscillations demonstrated greater spatial overlap with ictal high frequency oscillations in cases with single seizure hubs than in those with multiple hubs (100% vs 66% per patient, p=0.03).

Significance

Analysis of ictal high frequency oscillations can serve as a useful adjunctive technique to distinguish contiguous seizure spread from propagation to remote seizure sites. This study demonstrated that multiple seizure hubs were commonly identified by spatial clustering of ictal high frequency oscillations, including in cases that were considered unifocal. The distinction between initially activated and delayed seizure hubs was not evident based on interictal high frequency analysis, but may provide important prognostic information.

Key Points

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Spatial clustering and temporal activation sequences of ictal HFOs were analyzed in a cohort of surgical epilepsy patients.

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Ictal HFOs revealed recruitment of multiple noncontiguous seizure hubs during seizure propagation, even in cases thought to be unifocal.

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The presence of multiple seizure hubs was associated with asynchronous seizure terminations.

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Interictal HFOs showed greater spatial overlap with ictal HFOs in cases with single compared to multiple seizure hubs.
Easing COVID-19 lockdown measures while protecting the older restricts the deaths to the level of the full lockdown
Authors: Fokas A.S. , Cuevas-Maraver J. , Kevrekidis P.G.
Published: May 2020

Guided by a rigorous mathematical result, we have earlier introduced a numerical algorithm, which using as input the cumulative number of deaths caused by COVID-19, can estimate the effect of easing of the lockdown conditions. Applying this algorithm to data from Greece, we extend it to the case of two subpopulations, namely, those consisting of individuals below and above 40 years of age. After supplementing the Greek data for deaths with the data for the number of individuals reported to be infected by SARS-CoV-2, we estimated the effect on deaths and infections in the case that the easing of the lockdown measures is different for these two subpopulations. We found that if the lockdown measures are partially eased only for the young subpopulation, then the effect on deaths and infections is small. However, if the easing is substantial for the older population, this effect may be catastrophic.
COVID-19: Predictive Mathematical Models for the Number of Deaths in South Korea, Italy, Spain, France, UK, Germany, and USA
Authors: Fokas Athanasios S. , Dikaios Nikolaos , Kastis George A.
Published: May 2020

We have recently introduced two novel mathematical models for characterizing the dynamics of the cumulative number of individuals in a given country reported to be infected with COVID-19. Here we show that these models can also be used for determining the time-evolution of the associated number of deaths. In particular, using data up to around the time that the rate of deaths reaches a maximum, these models provide estimates for the time that a plateau will be reached signifying that the epidemic is approaching its end, as well as for the cumulative number of deaths at that time. The plateau is defined to occur when the rate of deaths is 5% of the maximum rate. Results are presented for South Korea, Italy, Spain, France, UK, Germany, and USA. The number of COVID-19 deaths in other counties can be analyzed similarly.
Significant Relaxation of SARS-CoV-2-Targeted Non-Pharmaceutical Interventions Will Result in Profound Mortality: A New York State Modelling Study
Authors: Hoffman Benjamin U.
Published: May 2020

Abstract

Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is the most significant global health crisis of the 21st century. The aim of this study was to develop a model to estimate the effect of undocumented infections, seasonal infectivity, immunity, and non-pharmaceutical interventions (NPIs), such as social distancing, on the transmission, morbidity, and mortality of SARS-CoV-2 in New York State (NYS). Simulations revealed dramatic infectivity driven by undocumented infections, and a peak basic reproductive number in NYS of 5.7. NPIs have been effective, and relaxation >50% will result in tens-of-thousands more deaths. Endemic infection is likely to occur in the absence of profound sustained immunity. As a result, until an effective vaccine or other effective pharmaceutical intervention is developed, it will be critical to not reduce NPIs >50% below current levels. This study establishes fundamental characteristics of SARS-CoV-2 transmission, which can help policymakers navigate combating this virus in the coming years.
Modelling safe protocols for reopening schools during the COVID-19 pandemic in France
Authors: Di Domenico Laura , Pullano Giulia , Sabbatini Chiara E. , Boëlle Pierre-Yves , Colizza Vittoria
Published: May 2020

As countries in Europe implement strategies to control COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Île-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on children’s role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist that maintain the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace are required to maintain the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown.
Fast recurrent processing via ventral prefrontal cortex is needed by the primate ventral stream for robust core visual object recognition
Authors: Kar Kohitij , DiCarlo James J
Published: May 2020

Distributed neural population spiking patterns in macaque inferior temporal (IT) cortex that support core visual object recognition require additional time to develop for specific (“late-solved”) images suggesting the necessity of recurrent processing in these computations. Which brain circuit motifs are most responsible for computing and transmitting these putative recurrent signals to IT? To test whether the ventral prefrontal cortex (vPFC) is a critical recurrent circuit node in this system, here we pharmacologically inactivated parts of the vPFC and simultaneously measured IT population activity, while monkeys performed object discrimination tasks. Our results show that vPFC inactivation deteriorated the quality of the late-phase (>150 ms from image onset) IT population code, along with commensurate, specific behavioral deficits for “late-solved” images. Finally, silencing vPFC caused the monkeys’ IT activity patterns and behavior to become more like those produced by feedforward artificial neural network models of the ventral stream. Together with prior work, these results argue that fast recurrent processing through the vPFC is critical to the production of behaviorally-sufficient object representations in IT.
Mitochondrial fission is a critical modulator of mutant APP-induced neural toxicity
Authors: Shields Lauren Y. , Li Huihui , Nguyen Kevin , Kim Hwajin , Doric Zak , Gill T. Michael , Haddad Dominik , Vossel Keith , Calvert Meredith , Nakamura Ken
Published: May 2020

Alterations in mitochondrial fission may contribute to the pathophysiology of several neurodegenerative diseases, including Alzheimer’s disease (AD). However, we understand very little about the normal functions of fission, or how fission disruption may interact with AD-associated proteins to modulate pathogenesis. Here we show that loss of the central mitochondrial fission protein dynamin-related 1 (Drp1) in CA1 and other forebrain neurons markedly worsens the learning and memory of mice expressing mutant human amyloid-precursor protein (hAPP) in neurons. In cultured neurons, Drp1KO and hAPP converge to produce mitochondrial Ca2+(mitoCa2+) overload, despite decreasing mitochondria-associated ER membranes (MAMs) and cytosolic Ca2+. This mitoCa2+overload occurs independently of ATP levels. These findings reveal a potential mechanism by which mitochondrial fission protects against hAPP-driven pathology.
ATP-driven Non-equilibrium Activation of Kinase Clients by the Molecular Chaperone Hsp90
Authors: Xu Huafeng
Published: May 2020

The molecular chaperone 90-kDa heat-shock protein (Hsp90) assists the late-stage folding and activation of diverse types of protein substrates (called clients), including many kinases. Previous studies have established that the Hsp90 homodimer undergoes an ATP-driven cycle through open and closed conformations. Here I propose a model of client activation by Hsp90, which predicts that this cycle enables Hsp90 to use ATP energy to drive a client out of thermodynamic equilibrium toward its active conformation. My model assumes that an Hsp90-bound client can transition between a deactivating conformation and an activating conformation. It suggests that the cochaperone Cdc37 aids Hsp90 to activate kinase clients by differentiating between these two intermediate conformations. My model makes experimentally testable predictions, including how modulating the stepwise kinetics of the Hsp90 cycle—for example, by various cochaperones—affects the activation of different clients. My model may inform client-specific and cell-type-specific therapeutic intervention of Hsp90-mediated protein activation.
An Atlas of Gene Regulatory Elements in Adult Mouse Cerebrum
Authors: Li Yang Eric , Preissl Sebastian , Hou Xiaomeng , Zhang Ziyang , Zhang Kai , Fang Rongxin , Qiu Yunjiang , Poirion Olivier , Li Bin , Liu Hanqing , Wang Xinxin , Han Jee Yun , Lucero Jacinta , Yan Yiming , Kuan Samantha , Gorkin David , Nunn Michael , Mukamel Eran A. , Behrens M. Margarita , Ecker Joseph , Ren Bing
Published: May 2020

The mammalian cerebrum performs high level sensory, motor control and cognitive functions through highly specialized cortical networks and subcortical nuclei. Recent surveys of mouse and human brains with single cell transcriptomics1–3and high-throughput imaging technologies4,5have uncovered hundreds of neuronal cell types and a variety of non-neuronal cell types distributed in different brain regions, but the cell-type-specific transcriptional regulatory programs responsible for the unique identity and function of each brain cell type have yet to be elucidated. Here, we probe the accessible chromatin in >800,000 individual nuclei from 45 regions spanning the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to define 491,818 candidatecisregulatory DNA elements in 160 distinct sub-types. We link a significant fraction of them to putative target genes expressed in diverse cerebral cell types and uncover transcriptional regulators involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of non-coding risk variants associated with various neurological disease and traits in humans. To facilitate the dissemination of information, we have set up a web portal (http://catlas.org/mousebrain).
Phage infection and sub-lethal antibiotic exposure mediateEnterococcus faecalistype VII secretion system dependent inhibition of bystander bacteria
Authors: Chatterjee Anushila , Willett Julia L. E. , Dunny Gary M. , Duerkop Breck A.
Published: May 2020

Bacteriophages (phages) are being considered as alternative therapeutics for the treatment of multidrug resistant bacterial infections. Considering phages have narrow host-ranges, it is generally accepted that therapeutic phages will have a marginal impact on non-target bacteria. We have discovered that lytic phage infection induces transcription of type VIIb secretion system (T7SS) genes in the pathobiontEnterococcus faecalis. Membrane damage during phage infection induces T7SS gene expression resulting in cell contact dependent antagonism of different Gram positive bystander bacteria. Deletion ofessB, a T7SS structural component, abrogates phage-mediated killing of bystanders. A predicted immunity gene confers protection against T7SS mediated inhibition, and disruption of its upstream LXG toxin gene rescues growth ofE. faecalisandStaphylococcus aureusbystanders. Phage induction of T7SS gene expression and bystander inhibition requires IreK, a serine/threonine kinase, and OG1RF_11099, a predicted GntR-family transcription factor. Additionally, sub-lethal doses of membrane targeting and DNA damaging antibiotics activated T7SS expression independent of phage infection, triggering T7SS antibacterial activity against bystander bacteria. Our findings highlight how phage infection and antibiotic exposure of a target bacterium can affect non-target bystander bacteria and implies that therapies beyond antibiotics, such as phage therapy, could impose collateral damage to polymicrobial communities.

Author Summary

Renewed interest in phages as alternative therapeutics to combat multi-drug resistant bacterial infections, highlights the importance of understanding the consequences of phage-bacteria interactions in the context of microbial communities. Although it is well established that phages are highly specific for their host bacterium, there is no clear consensus on whether or not phage infection (and thus phage therapy) would impose collateral damage to non-target bacteria in polymicrobial communities. Here we provide direct evidence of how phage infection of a clinically relevant pathogen triggers an intrinsic type VII secretion system (T7SS) antibacterial response that consequently restricts the growth of neighboring bacterial cells that are not susceptible to phage infection. Phage induction of T7SS activity is a stress response and in addition to phages, T7SS antagonism can be induced using sub-inhibitory concentrations of antibiotics that facilitate membrane or DNA damage. Together these data show that a bacterial pathogen responds to diverse stressors to induce T7SS activity which manifests through the antagonism of neighboring non-kin bystander bacterial cells.
Spike frequency adaptation supports network computations on temporally dispersed information
Authors: Salaj Darjan , Subramoney Anand , Kraišniković Ceca , Bellec Guillaume , Legenstein Robert , Maass Wolfgang
Published: May 2020

For solving tasks such as recognizing a song, answering a question, or inverting a sequence of symbols, cortical microcircuits need to integrate and manipulate information that was dispersed over time during the preceding seconds. Creating biologically realistic models for the underlying computations, especially with spiking neurons and for behaviorally relevant integration time spans, is notoriously difficult. We examine the role of spike frequency adaptation in such computations and find that it has a surprisingly large impact. The inclusion of this well known property of a substantial fraction of neurons in the neocortex — especially in higher areas of the human neocortex — moves the performance of spiking neural network models for computations on network inputs that are temporally dispersed from a fairly low level up to the performance level of the human brain.