bluuebunny/crossref_metadata_2025 huggingface dataset:
Scalable In-hospital Decontamination of N95 Filtering Facepiece Respirator with a Peracetic Acid Room Disinfection System
Authors: John Amrita R. , Raju Shine , Cadnum Jennifer L. , Lee Kipum , McClellan Phillip , Akkus Ozan , Miller Sharon K. , Jennings Wayne , Buehler Joy A. , Li Daniel F. , Redmond Sarah N. , Braskie Melissa , Hoyen Claudia K. , Donskey Curtis J.
Published: April 2020

Background

Critical shortages of personal protective equipment (PPE) especially N95 respirators, during the SARS-CoV-2 pandemic continues to be a source of great concern among health care workers (HCWs). Novel methods of N95 filtering facepiece respirator (FFR) decontamination that can be scaled-up for in-hospital use can help address this concern and keep HCWs safe.

Methods

A multidisciplinary pragmatic study was conducted to evaluate the use of an ultrasonic room high-level disinfection system (HLDS) that generates aerosolized peracetic acid (PAA) and hydrogen peroxide for decontamination of large numbers of N95 respirators. A cycle duration that consistently achieved disinfection of N95 respirators (defined as ≤ 6 log10 reductions in bacteriophage MS2 andGeobacillus stearothermophilusspores inoculated onto respirators) was identified. The treated masks were then assessed for changes to their hydrophobicity, material structure, strap elasticity, and filtration efficiency (FE). Assessment of PAA off-gassing from a treated mask was also performed.

Results

The PAA room HLDS was effective for disinfection of N95 respirators in a 2447 cubic feet room with deploy and dwell times of 16 and 32 minutes respectively, and a total cycle time of 1 hour and 16 minutes. After 5 treatment cycles, no adverse effects were detected on filtration efficiency, structural integrity, or strap elasticity. There was no detectable off-gassing of PAA from the treated masks.

Conclusion

The PAA room disinfection system provides a rapidly scalable solution for in-hospital decontamination of large numbers of N95 respirators to meet the needs of HCWs during the SARS-CoV-2 pandemic.
The role of spatial structure in the infection spread models: population density map of England example
Authors: Mashanov Gregory , Mashanova Alla
Published: April 2020

In the current situation of a pandemic caused by COVID-19 developing models accurately predicting the dynamics of the outbreaks in time and space became extremely important.

Individual-based models (IBM) simulating the spread of infection in a population have a few advantages compared to classical equation-based approach. First, they use individuals as units, which represent the population, and reflect the local variations happening in real life. Second, the simplicity of modelling the interactions between the individuals, which may not be the case when using differential equations.

We propose to use freely available population density maps to simulate the infection spread in the human population on the scale of an individual country or a city. We explore the effect of social distancing and show that it can reduce the outbreak when applied before or during peak time, but it can also inflict the second wave when relaxed after the peak. This can be explained by a large proportion of susceptible individuals, even in the large cities, after the first wave.

The model can be adapted to any spatial scale from a single hospital to multiple countries.
Hypertension and Renin–Angiotensin–Aldosterone System Inhibitors in Patients with Covid-19
Authors: Ip Andrew , Parikh Kaushal , Parrillo Joseph E. , Mathura Shivam , Hansen Eric , Sawczuk Ihor S. , Goldberg Stuart L.
Published: April 2020

Introduction

COVID-19 disproportionately affects those with comorbidities and the elderly. Hypertension is the most common pre-existing condition amongst COVID-19 patients. Upregulation of the renin-angiotensin-aldosterone system (RAAS) is common in hypertensive patients and may promote inflammation and ensuing cytokine storm in COVID-19. It is unknown whether RAAS inhibition with ACE1 inhibitors or angiotensin-receptor blockers (ARB) can be harmful or beneficial.

Methods

Within Hackensack Meridian Health network, the largest healthcare provider in New Jersey, we performed a retrospective, multicenter, convenience sampling study of hospitalized COVID-19 patients. Demographics, clinical characteristics, treatments, and outcomes were manually abstracted. Fishers exact tests, and logistic regression were performed.

Results

Among 3017 hospitalized COVID-19 patients, 1584 (52.5%) carried a diagnosis of hypertension. In the discharged or deceased cohort, the overall mortality was significantly increased at 35% vs 13% among COVID-19 patients with hypertension. However, when adjusted for age, the effect of hypertension on mortality was greatly diminished, with a reduction in odds-ratio by over half; and completely disappeared when adjusted for other major covariates. The mortality rates were lower for hypertensive patients prescribed ACE1 (27%, p=0.001) or ARBs (33%, p=0.12) compared to other anti-hypertensive agents (39%) in the unadjusted analyses. RAAS inhibitor therapy appeared protective compared to other anti-hypertensive agents (p=0.001).

Conclusions

While our results are limited by the retrospective nature of our study and by potential confounders, our data argue against a harmful effect of RAAS inhibition and support the HFSA/AHA/ACC joint statement recommending continuing ACE1 and ARB therapy in hypertensive COVID-19 patients.
Early detection of in-patient deterioration: one prediction model does not fit all
Authors: Blackwell Jacob N. , Keim-Malpass Jessica , Clark Matthew T. , Kowalski Rebecca L. , Najjar Salim N. , Bourque Jamieson M. , Lake Douglas E. , Moorman J. Randall
Published: April 2020

Objectives

Early detection of subacute potentially catastrophic illnesses using available data is a clinical imperative, and scores that report risk of imminent events in real time abound. Patients deteriorate for a variety of reasons, and it is unlikely that a single predictor such as an abnormal National Early Warning Score (NEWS) will detect all of them equally well. The objective of this study was to test the idea that the diversity of reasons for clinical deterioration leading to ICU transfer mandates multiple targeted predictive models.

Design

Individual chart review to determine the clinical reason for ICU transfer; determination of relative risks of individual vital signs, lab tests and cardiorespiratory monitoring measures for prediction of each clinical reason for ICU transfer; logistic regression modeling for the outcome of ICU transfer for a specific clinical reason.

Setting

Cardiac medical-surgical ward; tertiary care academic hospital.

Patients

8111 adult patients, 457 of whom were transferred to an ICU for clinical deterioration.

Interventions

None.

Measurements and main results

We calculated the contributing relative risks of individual vital signs, lab tests and cardiorespiratory monitoring measures for prediction of each clinical reason for ICU transfer, and used logistic regression modeling to calculate ROC areas and relative risks for the outcome of ICU transfer for a specific clinical reason. The reasons for clinical deterioration leading to ICU transfer were varied, as were their predictors. For example, the three most common reasons – respiratory instability, infection and suspected sepsis, and heart failure requiring escalated therapy – had distinct signatures of illness. Statistical models trained to target specific reasons for ICU transfer performed better than one model targeting combined events, and both performed better than the untrained NEWS score.

Conclusions and relevance

A single predictive model for clinical deterioration does not perform as well as having multiple models trained for the individual specific clinical events leading to ICU transfer.
A Novel Protein Drug, Novaferon, as the Potential Antiviral Drug for COVID-19
Authors: Zheng Fang , Zhou Yanwen , Zhou Zhiguo , Ye Fei , Huang Baoying , Huang Yaxiong , Ma Jing , Zuo Qi , Tan Xin , Xie Jun , Niu Peihua , Wang Wenlong , Xu Yun , Peng Feng , Zhou Ning , Cai Chunlin , Tang Wei , Xiao Xinqiang , Li Yi , Zhou Zhiguang , Jiang Yongfang , Xie Yuanlin , Tan Wenjie , Gong Guozhong
Published: April 2020

Background

Novaferon, a novel protein drug approved for the treatment of chronic hepatitis B in China, exhibits potent antiviral activities. We aimed to determine the anti-SARS-CoV-2 effects of Novaferon in vitro, and conducted a randomized, open-label, parallel group study to explore the antiviral effects of Novaferon for COVID-19.

Methods

In laboratory, the inhibition of Novaferon on viral replication in cells infected with SARS-CoV-2, and on SARS-CoV-2 entry into healthy cells was determined. Antiviral effects of Novaferon were evaluated in COVID-19 patients with treatment of Novaferon, Novaferon plus Lopinavir/Ritonavir, or Lopinavir/Ritonavir. The primary endpoint was the SARS-CoV-2 clearance rates on day 6 of treatment, and the secondary endpoint was the time to the SARS-CoV-2 clearance in COVID-19 patients

Results

Novaferon inhibited the viral replication in infected cells (EC50=1.02 ng/ml), and protected healthy cells from SARS-CoV-2 infection (EC50=0.1 ng/ml). Results from the 89 enrolled COVID-19 patients showed that both Novaferon and Novaferon plus Lopinavir/Ritonavir groups had significantly higher SARS-CoV-2 clearance rates on day 6 than the Lopinavir/Ritonavir group (50.0% vs.24.1%, p = 0.0400, and 60.0% vs.24.1%, p = 0.0053). Median time to SARS-CoV-2 clearance were 6 days, 6 days, and 9 days for three groups respectively, suggesting a 3-dayreduction of time to SARS-CoV-2 clearance in both Novaferon and Novaferon plus Lopinavir/Ritonavir groups compared with Lopinavir/Ritonavir group.

Conclusions

Novaferon exhibited anti-SARS-CoV-2 effects in vitro and in COVID-19 patients. These data justified the further evaluation of Novaferon.
COVID-19 in India: State-wise Analysis and Prediction
Authors: Ghosh Palash , Ghosh Rik , Chakraborty Bibhas
Published: April 2020

Coronavirus disease 2019 (COVID-19), a highly infectious disease, was first detected in Wuhan, China, in December 2019. The disease has spread to 212 countries and territories around the world and infected (confirmed) more than three million people. In India, the disease was first detected on 30 January 2020 in Kerala in a student who returned from Wuhan. The total (cumulative) number of confirmed infected people is more than 37000 till now across India (3 May 2020). Most of the research and newspaper articles focus on the number of infected people in the entire country. However, given the size and diversity of India, it may be a good idea to look at the spread of the disease in each state separately, along with the entire country. For example, currently, Maharashtra has more than 10000 confirmed cumulative infected cases, whereas West Bengal has less than 800 confirmed infected cases (1 May 2020). The approaches to address the pandemic in the two states must be different due to limited resources. In this article, we will focus the infected people in each state (restricting to only those states with enough data for prediction) and build three growth models to predict infected people for that state in the next 30 days. The impact of preventive measures on daily infected-rate is discussed for each state.

Highlights of the Analysis

Data considered for analysis: up to 1 May 2020.

One model can mislead us. Here, we consider the exponential, the logistic and the SIS models along with daily infection-rate (DIR). We interpret the results jointly from all models rather than individually.

We expect DIR to be zero or negative to conclude that COVID-19 is not spreading in a state. Even a small positive DIR (say 0.01) indicates virus is spreading in the community. The virus can potentially increase the DIR anytime.

Severe: The states without a decreasing trend in DIR and near exponential growth in active infected cases are Maharashtra, Delhi, Gujarat, Madhya Pradesh, Andhra Pradesh, Uttar Pradesh, and West Bengal.

Moderate: The states with an almost decreasing trend in DIR and non-increasing growth in active infected cases are Tamil Nadu, Rajasthan, Punjab and Bihar.

Controlled: The states with a decreasing trend in DIR and decreasing growth in active infected cases in the last few days are Kerala, Haryana, Jammu and Kashmir, Karnataka, and Telangana.

States with non-decreasing DIR need to do much more in terms of the preventive measures immediately to combat the COVID-19 pandemic. On the other hand, the states with decreasing DIR can maintain the same status to see the DIR become zero or negative for consecutive 14 days to be able to declare the end of the pandemic.
Sequential informed pooling approach to detect SARS-CoV2 infection
Authors: Millioni Renato , Mortarino Cinzia
Published: April 2020

The alarming spread of the pandemic coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is requiring several measures to reduce the risk of contagion. Every successful strategy in controlling SARS-CoV2 infection depends on the timely viral diagnosis which should include asymptomatic carriers. Consequently, strategies to increase the throughput for clinical laboratories to conduct large-scale diagnostic testing are urgently needed. Here we support the hypothesis that standard diagnostic protocol for SARS-CoV-2 virus could be conveniently applied to pooled samples obtained from different subjects. We suggest that a two-step sequential pooling procedure could identify positive subjects, ensuring at the same time significant benefits of costs and time. Simulation data are used to assess the efficiency, in terms of number of required tests, both for random assignment of the subjects to the pools and for situations when epidemiological and clinical data are used to create an “informed” version of the pooling. Different scenarios are examined in the simulations to measure the effect of different pool sizes and different values for the virus frequency. Our results allow to customize the pooling strategy according to the specific characteristics of the cohort to be tested.
Extensions of the SEIR Model for the Analysis of Tailored Social Distancing and Tracing Approaches to Cope with COVID-19
Authors: Grimm Veronika , Mengel Friederike , Schmidt Martin
Published: April 2020

Abstract

In the context of the COVID-19 pandemic, governments worldwide face the challenge of designing tailored measures of epidemic control to provide reliable health protection while allowing societal and economic activity. In this paper, we propose an extension of the epidemiological SEIR model to enable a detailed analysis of commonly discussed tailored measures of epidemic control—among them group-specific protection and the use of tracing apps. We introduce groups into the SEIR model that may differ both in their underlying parameters as well as in their behavioral response to public health interventions. Moreover, we allow for different infectiousness parameters within and across groups, different asymptomatic, hospitalization, and lethality rates, as well as different take-up rates of tracing apps. We then examine predictions from these models for a variety of scenarios. Our results visualize the sharp trade-offs between different goals of epidemic control, namely a low death toll, avoiding overload of the health system, and a short duration of the epidemic. We show that a combination of tailored mechanisms, e.g., the protection of vulnerable groups together with a “trace & isolate” approach, can be effective in preventing a high death toll. Protection of vulnerable groups without further measures requires unrealistically strict isolation. A key insight is that high compliance is critical for the effectiveness of a “trace & isolate” approach. Our model allows to analyze the interplay of group-specific social distancing and tracing also beyond our case study in scenarios with a large number of groups reflecting, e.g., sectoral, regional, or age differentiation and group-specific behavioral responses.
Countries are Clustered but Number of Tests is not Vital to Predict Global COVID-19 Confirmed Cases: A Machine Learning Approach
Authors: Rahaman Khan Md Hasinur , Hossain Ahmed
Published: April 2020

COVID-19 disease is a global pandemic and it appears as pandemic for each and every nation and territory in the earth.This paper focusses on analysing the global COVID-19 data by popular machine learning techniques to know which covariates are importantly associated with the cumulative number of confirmed cases, whether the countries are clustered with respect to the covariates considered, whether the variation in the covariates are explained by any latent factor. Regression tree, cluster analysis and principal component analysis are implemented to global COVID-19 data of 133 countries obtained from the worldometer website as reported as on April 17, 2020. Our results suggest that there are four major clusters among the countries. First cluster consists of 8 countries where cumulative infected cases and deaths are highest. It is also revealed that there are two principal components. The countries which play vital role to explain the 60% variation of the total variations by the first component characterized by all variables except the rate variables include USA, Spain, Italy, France, Germany, UK, and Iran. Remaining countries contribute to explaining 20% variation of the total variations by the second component characterized by only three rate variables. We also found that the number of tests by the country variable among other variables country, number of active cases, number of deaths, number of recovered patients, number of serious cases, and number of new cases is an unimportant variable to predict cumulative number of confirmed cases. Hence, the number of tests might play vital role to individual country level who are in the primary level of virus spread but not to the global level.
State-by-State prediction of likely COVID-19 scenarios in the United States and assessment of the role of testing and control measures
Authors: Zhai Zheng-Meng , Long Yong-Shang , Kang Jie , Li Yi-Lin , Zeng Lang , Han Li-Lei , Lin Zhao-Hua , Zeng Ying-Qi , Wu Da-Yu , Tang Ming , Xu Di , Liu Zonghua , Lai Ying-Cheng
Published: April 2020

Due to the heterogeneity among the States in the US, predicting COVID-19 trends and quantitatively assessing the effects of government testing capability and control measures need to be done via a State-by-State approach. We develop a comprehensive model for COVID-19 incorporating time delays and population movements. With key parameter values determined by empirical data, the model enables the most likely epidemic scenarios to be predicted for each State, which are indicative of whether testing services and control measures are vigorous enough to contain the disease. We find that government control measures play a more important role than testing in suppressing the epidemic. The vast disparities in the epidemic trends among the States imply the need for long-term placement of control measures to fully contain COVID-19.
Demographic and Socio-Economic Factors, and Healthcare Resource Indicators Associated with the Rapid Spread of COVID-19 in Northern Italy: An Ecological Study
Authors: Buja Alessandra , Paganini Matteo , Cocchio Silvia , Scioni Manuela , Rebba Vincenzo , Baldo Vincenzo
Published: April 2020

Background

COVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the virus’s dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy.

Methods

This is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearson’s test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The virus’s spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators.

Findings

Multivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value=0.003), and positively with public transportation per capita (p-value=0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value=0.070), the % of private acute care hospital beds (p-value=0.006).

Interpretation

Demographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.
Pooled RNA sample reverse transcriptase real time PCR assay for SARS CoV-2 infection: a reliable, faster and economical method
Authors: Gupta Ekta , Padhi Abhishek , Khodare Arvind , Aggarwal Reshu , Ramachnadran Krithiga , Mehta Vibha , Kilikdar Mousumi , Dubey Shantanu , Kumar Guresh , Sarin Shiv Kumar
Published: April 2020

Background

Corona virus disease 2019 (COVID-19) which initially started as a cluster of pneumonia cases in the Wuhan city of China has now become a full blown pandemic. Timely diagnosis of COVID-19 is the key in containing the pandemic and breaking the chain of transmission. In low and middle income countries availability of testing kits has become the major bottle neck in testing. Novel methods like pooling of samples are the need of the hour.

Method

Extracted RNA samples were randomly placed in pools of 8 on a 96 well plate. Both individual RNA (ID) and pooled RNA RT-qPCR for the screening E gene were done in the same plate and the positivity for the E gene was seen.

Results

The present study demonstrated that pool testing with 8 RNA samples can easily detect even up to a single positive sample with Ct value as high as 38. The present study also showed that the results of pool testing is not affected by number of positive samples in a pool.

Conclusion

Pooling of 8 RNA samples can reduce the time and expense by one eighth, and can help expand diagnostic capabilities, especially during constrained supply of reagents and PCR kits for the diagnosis of SARS-CoV-2 infection.
Key predictors of attending hospital with COVID19: An association study from the COVID Symptom Tracker App in 2,618,948 individuals
Authors: Lochlainn Mary Ni , Lee Karla A. , Sudre Carole H. , Varsavsky Thomas , Cardoso M. Jorge , Menni Cristina , Bowyer Ruth C. E. , Nguyen Long H. , Drew David A. , Ganesh Sajaysurya , du Cadet Julien Lavigne , Visconti Alessia , Freidin Maxim B. , Modat Marc , Graham Mark S , Pujol Joan Capdevila , Murray Benjamin , Moustafa Julia S El-Sayed , Zhang Xinyuan , Davies Richard , Falchi Mario , Wolf Jonathan , Spector Tim D. , Chan Andrew T. , Ourselin Sebastien , Steves Claire J.
Published: April 2020

Objectives

We aimed to identify key demographic risk factors for hospital attendance with COVID-19 infection.

Design

Community survey

Setting

The COVID Symptom Tracker mobile application co-developed by physicians and scientists at King’s College London, Massachusetts General Hospital, Boston and Zoe Global Limited was launched in the UK and US on 24thand 29thMarch 2020 respectively. It captured self-reported information related to COVID-19 symptoms and testing.

Participants

2,618,948 users of the COVID Symptom Tracker App. UK (95.7%) and US (4.3%) population. Data cut-off for this analysis was 21stApril 2020.

Main outcome measures

Visit to hospital and for those who attended hospital, the need for respiratory support in three subgroups (i) self-reported COVID-19 infection with classical symptoms (SR-COVID-19), (ii) selfreported positive COVID-19 test results (T-COVID-19), and (iii) imputed/predicted COVID-19 infection based on symptomatology (I-COVID-19). Multivariate logistic regressions for each outcome and each subgroup were adjusted for age and gender, with sensitivity analyses adjusted for comorbidities. Classical symptoms were defined as high fever and persistent cough for several days.

Results

Older age and all comorbidities tested were found to be associated with increased odds of requiring hospital care for COVID-19. Obesity (BMI >30) predicted hospital care in all models, with odds ratios (OR) varying from 1.20 [1.11; 1.31] to 1.40 [1.23; 1.60] across population groups. Pre-existing lung disease and diabetes were consistently found to be associated with hospital visit with a maximum OR of 1.79 [1.64,1.95] and 1.72 [1.27; 2.31]) respectively. Findings were similar when assessing the need for respiratory support, for which age and male gender played an additional role.

Conclusions

Being older, obese, diabetic or suffering from pre-existing lung, heart or renal disease placed participants at increased risk of visiting hospital with COVID-19. It is of utmost importance for governments and the scientific and medical communities to work together to find evidence-based means of protecting those deemed most vulnerable from COVID-19.

Trial registration

The App Ethics have been approved by KCL ethics Committee REMAS ID 18210, review reference LRS-19/20-18210
Custommune: a web tool to design personalized and population-targeted vaccine epitopes
Authors: Tarek Mohammad , Elhefnawi Mahmoud , Maricato Juliana Terzi , Diaz Ricardo Sobhie , Shytaj Iart Luca , Savarino Andrea
Published: April 2020

Computational prediction of immunogenic epitopes is a promising platform for therapeutic and preventive vaccine design. A potential target for this strategy is human immunodeficiency virus (HIV-1), for which, despite decades of efforts, no vaccine is available. In particular, a therapeutic vaccine devised to eliminate infected cells would represent a key component of cure strategies. HIV peptides designed based on individual viro-immunological data from people living with HIV/AIDS have recently shown able to induce post-therapy viral set point abatement. However, the reproducibility and scalability of this method is curtailed by the errors and arbitrariness associated with manual peptide design as well as by the time-consuming process.

We herein introduce Custommune, a user-friendly web tool to design personalized and population-targeted vaccines. When applied to HIV-1, Custommune predicted personalized epitopes using patient specific Human Leukocyte Antigen (HLA) alleles and viral sequences, as well as the expected HLA-peptide binding strength and potential immune escape mutations. Of note, Custommune predictions compared favorably with manually designed peptides administered in a recent phase II clinical trial (NCT02961829).

Furthermore, we utilized Custommune to design preventive vaccines targeted for populations highly affected by COVID-19. The results allowed the identification of peptides tailored for each population and predicted to elicit both CD8+T-cell immunity and neutralizing antibodies against structurally conserved epitopes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Overall, our data describe a new tool for rapid development of personalized or population-based immunotherapy against chronic and acute viral infections.
Interim Analysis of Pandemic Coronavirus Disease 2019 (COVID-19) and the SARS-CoV-2 virus in Latin America and the Caribbean: Morbidity, Mortality and Molecular Testing Trends in the Region
Authors: Simbaña-Rivera Katherine , Gómez-Barreno Lenin , Guerrero Jhon , Simbaña-Guaycha Fernanda , Fernández Raúl , López-Cortés Andrés , Lister Alex , Ortiz-Prado Esteban
Published: April 2020

Background

The relentless advance of the SARS-CoV-2 virus pandemic has resulted in a significant burden on countries, regardless of their socio-economic conditions. The virus has infected more than 2.5 million people worldwide, causing to date more than 150,000 deaths in over 210 countries.

Objective

The aim of this study was to describe the trends in cases, tests and deaths related to novel coronavirus disease (COVID-19) in Latin American and Caribbean (LAC) countries.

Methodology

Data were retrieved from the WHO-Coronavirus Disease (COVID-2019) situation reports and the Center for Systems Science and Engineering (CSSE) databases from Johns Hopkins University. Descriptive statistics including death rates, cumulative mortality and incidence rates, as well as testing rates per population at risk were performed. A comparison analysis among countries with ≥50 confirmed cases was performed from February 26th, 2020 to April 8th, 2020.

Results

Brazil had the greatest number of cases and deaths in the region. Panama experienced a rapid increase in the number of confirmed cases with Trinidad and Tobago, Bolivia and Honduras having the highest case fatality rates. Panama and Chile conducted more tests per million inhabitants and more tests per day per million inhabitants, followed by Uruguay and El Salvador. Dominican Republic, Bolivia, Ecuador and Brazil had the highest positive test rates.

Conclusions

The COVID-19 disease pandemic caused by the SARS-CoV-2 virus has progressed rapidly in LAC countries. Some countries have been affected more severely than others, with some adopting similar disease control methods to help slow down the spread of the virus. With limited testing and other resources, social distancing is needed to help alleviate the strain on already stretched health systems.
Radiological appearances of Anastomotic Leakage after Radical Gastrectomy
Authors: Sah Birendra Kumar , Yang Zhang , Huan Zhang , Jian Li , Wentao Liu , Chao Yan , Chen Li , Min Yan , Gang Zhu Zheng
Published: April 2020

Background

Anastomotic leakage is a critical postoperative complication after gastric cancer surgery. Previous studies have not specified radiological findings of anastomotic leakage. We investigated the potential burden caused by postoperative anastomotic leakage and explored the objective appearances of anastomotic leakage on computed tomography (CT) examination.

Methods

Gastric cancer patients who underwent curative gastrectomy and had a CT examination after surgery were included in this study. Propensity score (PS) matching generated 70 cases (35 cases of anastomotic leakage and 35 cases of no anastomotic leak) among 210 eligible cases. Univariate and multivariate analyses were used to identify the predictive variables of CT findings.

Results

More severe postoperative complications were observed in patients who had an anastomotic failure than those without anastomotic leakage(p<0.05). The median number of postoperative days (PODs) was 18 days for patients with no anastomotic leak, but the length of stay was almost three times longer (50 days) in patients with anastomotic leakage(p<0.05). In the univariate analysis, we observed a significant association between anastomotic leakage and five CT variables, including pneumoperitoneum, pneumoseroperitoneum (intra-abdominal accumulation of mixed gas and fluid), accumulation of extraluminal gas at the anastomosis site, seroperitoneum and extraluminal fluid collection at the anastomosis site (p<0.05). The multivariate analysis of the CT parameters revealed that the accumulation of extraluminal gas at the anastomosis site is the independent diagnostic parameters of a postoperative anastomotic leakage (p<0.05).

Conclusions

The occurrence of an anastomotic leakage significantly compromises the patients and increases the treatment burden. The CT variables of this study are beneficial to rule out anastomotic leakage after gastric cancer surgery. Extraluminal gas at the anastomosis site is highly suggestive of anastomotic leakage.
Altered sensory neuron development in CMT2D mice is site-specific and linked to increased GlyRS levels
Authors: Sleigh James N. , Mech Aleksandra M. , Aktar Tahmina , Zhang Yuxin , Schiavo Giampietro
Published: April 2020

Dominant, missense mutations in the widely and constitutively expressedGARS1gene cause a peripheral neuropathy that usually begins in adolescence and principally impacts the upper limbs. Caused by a toxic gain-of-function in the encoded glycyl-tRNA synthetase (GlyRS) enzyme, the neuropathology appears to be independent of the canonical role of GlyRS in aminoacylation. Patients display progressive, life-long weakness and wasting of muscles in hands followed by feet, with frequently associated deficits in sensation. When dysfunction is observed in motor and sensory nerves, there is a diagnosis of Charcot-Marie-Tooth disease type 2D (CMT2D), or distal hereditary motor neuropathy type V if the symptoms are purely motor. The cause of this varied sensory involvement remains unresolved, as are the pathomechanisms underlying the selective neurodegeneration characteristic of the disease. We have previously identified in CMT2D mice that neuropathy-causingGarsmutations perturb sensory neuron fate and permit mutant GlyRS to aberrantly interact with neurotrophin receptors (Trks). Here, we extend this work by interrogating further the anatomy and function of the CMT2D sensory nervous system in mutantGarsmice, obtaining several key results: 1) sensory pathology is restricted to neurons innervating the hindlimbs; 2) perturbation of sensory development is not common in mouse models of neuromuscular disease; 3)in vitroaxonal transport of signalling endosomes is not impaired in afferent neurons of all CMT2D mouse models; and 4)Garsexpression is selectively elevated in a subset of sensory neurons and linked to sensory developmental defects. These findings highlight the importance of comparative neurological assessment in mouse models of disease and shed light on key proposed neuropathogenic mechanisms inGARS1-linked neuropathy.
Fluorescent in situ sequencing of DNA barcoded antibodies
Authors: Kohman Richie E. , Church George M.
Published: April 2020

Biological tissues contain thousands of different proteins yet conventional antibody staining can only assay a few at a time because of the limited number of spectrally distinct fluorescent labels. The capacity to map the location of hundreds or thousands of proteins within a single sample would allow for an unprecedented investigation of the spatial proteome, and give insight into the development and function of diseased and healthy tissues. In order to achieve this goal, we propose a new technology that leverages established methodologies for in situ imaging of nucleic acids to achieve near limitless multiplexing. The exponential scaling power of DNA technologies ties multiplexing to the number of DNA nucleotides sequenced rather than the number of spectrally distinct labels. Here we demonstrate that barcode sequencing can be applied to in situ proteomics by sequencing DNA conjugated antibodies bound to biological samples. In addition, we show a signal amplification method which is compatible with barcoded antibodies.
Sorting nexin-27 regulates AMPA receptor trafficking through the synaptic adhesion protein LRFN2
Authors: McMillan Kirsty J. , Banks Paul J. , Hellel Francesca L. N. , Carmichael Ruth E. , Clairfeuille Thomas , Evans Ashley J. , Heesom Kate J. , Lewis Phillip , Collins Brett M. , Bashir Zafar I. , Henley Jeremy M. , Wilkinson Kevin A. , Cullen Peter J.
Published: April 2020

The endosome-associated cargo adaptor sorting nexin-27 (SNX27) is linked to various neuropathologies through sorting of integral proteins to the synaptic surface, most notably AMPA receptors. To provide a broader view of SNX27-associated pathologies we have performed unbiased proteomics to identify new neuronal SNX27-dependent cargoes, and identified proteins linked to excitotoxicity (SLC1A3, SLC4A7, SLC6A11), epilepsy, intellectual disabilities and working memory deficits (KCNT2, ADAM22, KIDINS220, LRFN2). Focusing on the synaptic adhesion molecule leucine-rich repeat and fibronectin type-III domain-containing protein 2 (LRFN2), we establish that SNX27 binds to LRFN2 and is responsible for regulating its endosomal sorting. LRFN2 associates with AMPA receptors and knockdown of LRFN2 phenocopies SNX27 depletion in decreasing surface expression of AMPA receptors, reducing synaptic activity and attenuating hippocampal long-term potentiation. Our evidence suggests that, in contrast to previous reports, SNX27 does not directly bind to AMPA receptors, and instead controls AMPA receptor-mediated synaptic transmission and plasticity indirectly through the endosomal sorting of LRFN2. Overall, our study provides new molecular insight into the perturbed function of SNX27 and LRFN2 in a range of neurological conditions.
Entraining alpha activity using visual stimulation in patients with chronic musculoskeletal pain. A feasibility study
Authors: Arendsen Laura J. , Henshaw James , Brown Christopher A. , Sivan Manoj , Taylor Jason R. , Trujillo-Barreto Nelson J. , Casson Alexander J. , Jones Anthony K. P.
Published: April 2020

Entraining alpha activity with rhythmic visual, auditory, and electrical stimulation can reduce experimentally induced pain. However, evidence for alpha entrainment and pain reduction in patients with chronic pain is limited. This feasibility study investigated whether visual alpha stimulation can increase alpha power in patients with chronic musculoskeletal pain and secondarily, if chronic pain was reduced following stimulation. In a within-subject design, 22 patients underwent 4-minute periods of stimulation at 10 Hz (alpha), 7 Hz (high-theta, control), and 1 Hz (control) in a pseudo-randomized order. Patients underwent stimulation both sitting and standing and verbally rated their pain before and after each stimulation block on a 0-10 numerical rating scale. Global alpha power was significantly higher during 10 Hz compared to 1 Hz stimulation when patients were standing (t = −6.08, p <.001). On a more regional level, a significant increase of alpha power was found in the right-middle and left-posterior region when patients were sitting. With respect to our secondary aim, no significant reduction of pain intensity and unpleasantness was found. However, only the alpha stimulation resulted in a minimal clinically important difference in at least 50% of participants for pain intensity (50%) and unpleasantness ratings (65%) in the sitting condition. This study provides initial evidence for the potential of visual stimulation as a means to enhance alpha activity in patients with chronic musculoskeletal pain. The brief period of stimulation was insufficient to reduce chronic pain. This study is the first to provide evidence that a brief period of visual stimulation at alpha frequency can significantly increase alpha power in patients with chronic musculoskeletal pain. Further study is warranted to investigate optimal dose and individual stimulation parameters to achieve pain relief in these patients.
Genome-Enabled Discovery of Anthraquinone Biosynthesis inSenna tora
Authors: Kang Sang-Ho , Pandey Ramesh Prasad , Lee Chang-Muk , Sim Joon-Soo , Jeong Jin-Tae , Choi Beom-Soon , Jung Myunghee , Won So Youn , Oh Tae-Jin , Yu Yeisoo , Kim Nam-Hoon , Lee Ok Ran , Lee Tae-Ho , Bashyal Puspalata , Kim Tae-Su , Kim Chang-Kug , Kim Jung Sun , Ahn Byoung Ohg , Rhee Seung Yon , Sohng Jae Kyung
Published: April 2020

Senna torais a widely used medicinal plant. Its health benefits have been attributed to the large quantity of anthraquinones, but how they are made in plants remains a mystery. To identify the genes responsible for plant anthraquinone biosynthesis, we sequenced and annotated the genome ofS. toraat the chromosome level with contig N50 and super-scaffold N50 of 4.03 Mb and 41.7 Mb. Comparison among related plant species showed that a chalcone synthase-like (CHS-L) gene family has lineage-specifically and rapidly expanded inS. tora. Combining genomics, transcriptomics, metabolomics, and biochemistry, we identified a CHS-L responsible for biosynthesis of anthraquinones, the first example in plants. TheS. torareference genome will accelerate the discovery of biologically active anthraquinone biosynthesis pathways in medicinal plants.

One Sentence Summary

The chromosome-scale reference genome of a medicinal plantSenna tora, transcriptomics, metabolomics, and biochemical analysis provide new insights into anthraquinone biosynthesis in plants.
VoroCNN: Deep convolutional neural network built on 3D Voronoi tessellation of protein structures
Authors: Igashov Ilia , Olechnovic Kliment , Kadukova Maria , Venclovas Česlovas , Grudinin Sergei
Published: April 2020

Motivation

Effective use of evolutionary information has recently led to tremendous progress in computational prediction of three-dimensional (3D) structures of proteins and their complexes. Despite the progress, the accuracy of predicted structures tends to vary considerably from case to case. Since the utility of computational models depends on their accuracy, reliable estimates of deviation between predicted and native structures are of utmost importance.

Results

For the first time we present a deep convolutional neural network (CNN) constructed on a Voronoi tessellation of 3D molecular structures. Despite the irregular data domain, our data representation allows to efficiently introduce both convolution and pooling operations of the network. We trained our model, called VoroCNN, to predict local qualities of 3D protein folds. The prediction results are competitive to the state of the art and superior to the previous 3D CNN architectures built for the same task. We also discuss practical applications of VoroCNN, for example, in the recognition of protein binding interfaces.

Availability

The model, data, and evaluation tests are available athttps://team.inria.fr/nano-d/software/vorocnn/.

Contact

ceslovas.venclovas@bti.vu.lt,sergei.grudinin@inria.fr
Larger GPU-accelerated brain simulations with procedural connectivity
Authors: Knight James C , Nowotny Thomas
Published: April 2020

Large-scale simulations of spiking neural network models are an important tool for improving our understanding of the dynamics and ultimately the function of brains. However, even small mammals such as mice have on the order of 1 × 1012synaptic connections which, in simulations, are each typically charaterized by at least one floating-point value. This amounts to several terabytes of data – an unrealistic memory requirement for a single desktop machine. Large models are therefore typically simulated on distributed supercomputers which is costly and limits large-scale modelling to a few privileged research groups. In this work, we describe extensions to GeNN – our Graphical Processing Unit (GPU) accelerated spiking neural network simulator – that enable it to ‘procedurally’ generate connectivity and synaptic weights ‘on the go’ as spikes are triggered, instead of storing and retrieving them from memory. We find that GPUs are well-suited to this approach because of their raw computational power which, due to memory bandwidth limitations, is often under-utilised when simulating spiking neural networks. We demonstrate the value of our approach with a recent model of the Macaque visual cortex consisting of 4.13 × 106neurons and 24.2 × 109synapses. Using our new method, it can be simulated on a single GPU – a significant step forward in making large-scale brain modelling accessible to many more researchers. Our results match those obtained on a supercomputer and the simulation runs up to 35 % faster on a single high-end GPU than previously on over 1000 supercomputer nodes.
vmPFC drives hippocampal processing during autobiographical memory recall regardless of remoteness
Authors: McCormick Cornelia , Barry Daniel N. , Jafarian Amirhossein , Barnes Gareth R. , Maguire Eleanor A.
Published: April 2020

Our ability to recall past experiences, autobiographical memories (AMs), is crucial to cognition, endowing us with a sense of self and underwriting our capacity for autonomy. Traditional views assume that the hippocampus orchestrates event recall, whereas recent accounts propose that the ventromedial prefrontal cortex (vmPFC) instigates and coordinates hippocampal-dependent processes. Here we sought to characterise the dynamic interplay between hippocampus and vmPFC during AM recall to adjudicate between these perspectives. Leveraging the high temporal resolution of magnetoencephalography, we found that the left hippocampus and the vmPFC showed the greatest power changes during AM retrieval. Moreover, responses in the vmPFC preceded activity in the hippocampus during initiation of AM recall, except during retrieval of the most recent AMs. The vmPFC drove hippocampal activity during recall initiation and also as AMs unfolded over subsequent seconds, and this effect was evident regardless of AM age. These results re-cast the positions of the hippocampus and the vmPFC in the AM retrieval hierarchy, with implications for theoretical accounts of memory processing and systems-level consolidation.
Cis-regulatory similarities in the zebrafish and human pancreas uncover potential disease-related enhancers
Authors: Bordeira-Carriço R. , Teixeira J. , Duque M. , Galhardo M. , Ribeiro D. , Dominguez-Acemel R. , Firbas P. N. , Tena J. J. , Eufrasio A. , Marques J. , Ferreira F. , Freitas T. , Carneiro F. , Goméz-Skarmeta J. L. , Bessa J.
Published: April 2020

Introductory paragraph

The pancreas is a central organ for human diseases that have a dramatic societal burden, such as pancreatic cancer and diabetes1,2. Non-coding cis-regulatory elements (CREs) of DNA control gene expression3,4, being required for proper pancreas function. Most disease-associated alleles5,6are non-coding, often overlapping with CREs5, suggesting that alterations in these regulatory sequences contribute to human pancreatic diseases by impairing gene expression. However, functional testing of CREsin vivois not fully explored. Here we analysed histone modifications, transcription, chromatin accessibility and interactions, to identify zebrafish pancreas CREs and their human functional equivalents, uncovering disease-associated sequences across species. We found a human pancreatic enhancer whose deletion impairs the tumour suppressor geneARID1Aexpression, conferring a potential tumour suppressor role to this non-coding sequence. Additionally, we identified a zebrafishptf1adistal enhancer which deletion generates pancreatic agenesis, demonstrating the causality of this condition in humans7and the interspecies functional equivalency of enhancers.
Neutrophil to Lymphocyte Ratio (NLR) in captive chimpanzees (Pan troglodytes): The effects of sex, age, and rearing
Authors: Neal Webb Sarah J. , Schapiro Steven J. , Sherwood Chet C. , Raghanti Mary Ann , Hopkins William D.
Published: April 2020

In humans, neutrophil to lymphocyte ratio (NLR) has been used as a clinical tool in diagnosis and/or prognosis of a variety of cancers and medical conditions, as well as in measuring physiological stress over time. Given the close phylogenetic relationship and physical similarities between humans and apes, NLR may similarly be a useful diagnostic tool in assessing chimpanzee health. Only one study has examined NLR in apes, reporting that NLR increased with age and was affected by body-mass index and sex. In the current study, we examined changes in NLR data from longitudinal health records for 443 chimpanzees in two captive chimpanzee populations. Using these data, we analyzed intra-individual changes and inter-individual differences in NLR as a function of age, rearing history, and sex. Contrary to previous studies in humans and the one previous study in chimpanzees, NLR values did not change over a 10-year timespan within individual chimpanzees. However, cross-sectional comparisons revealed a significant quadratic relationship between age and NLR with the highest values during mid-life (20-30 years of age) and the lowest values in younger and older individuals. Additionally, males and mother-reared individuals had higher NLR than females and nursery-reared chimpanzees, respectively. Lastly, males and those with higher NLR values died at younger ages. These findings may suggest that NLR can be used a predictor of longevity in chimpanzees. However, given the complexities of these relationships, more research is needed to determine the utility of NLR as a diagnostic health tool for use in chimpanzees.