bluuebunny/crossref_metadata_2025 huggingface dataset:
The Potential role of Particulate Matter in the Spreading of COVID-19 in Northern Italy: First Evidence-based Research Hypotheses
Authors: Setti Leonardo , Passarini Fabrizio , De Gennaro Gianluigi , Barbieri Pierluigi , Perrone Maria Grazia , Piazzalunga Andrea , Borelli Massimo , Palmisani Jolanda , Di Gilio Alessia , Piscitelli Prisco , Miani Alessandro
Published: April 2020

Background

An epidemic model based only on respiratory droplets and close contact could not fully explain the regional differences in the spread of the recent severe acute respiratory syndrome COVID-19 in Italy, which was fast and dramatic only in Lombardy and Po Valley. On March 16th 2020, we presented a Position Paper proposing a research hypothesis concerning the association between higher mortality rates due to COVID-19 observed in Northern Italy and the peaks of particulate matter concentrations, frequently exceeding the legal limit of 50 µg/m3 as PM10 daily average

Methods

To assess environmental factors related to the spread of the COVID-19 in Italy from February 24th to March 13th (the date when the lockdown has been imposed over Italy), official daily data relevant to ambient PM10 levels were collected from all Italian Provinces between February 9th and February 29th, taking into account the average time (estimated in 17 days) elapsed between the initial infection and the recorded COVID positivity. In addition to the number of exceedances of PM10 daily limit value, we considered also population data and daily travelling information per each Province.

Results

PM10 daily limit value exceedances appear to be a significant predictor (p < .001) of infection in univariate analyses. Less polluted Provinces had a median of 0.03 infection cases over 1000 residents, while most polluted Provinces had a median of 0.26 cases over 1000 residents. Thirty-nine out of 41 Northern Italian Provinces resulted in the category with highest PM10 levels, while 62 out of 66 Southern Provinces presented low PM10 concentrations (p< 0.001). In Milan, the average growth rate before the lockdown was significantly higher than Rome (0.34 vs. 0.27 per day, with a doubling time of 2.0 days vs. 2.6), suggesting a basic reproductive number R0>6.0, comparable with the highest values estimated for China.
The Estimated Time-Varying Reproduction Numbers during the Ongoing Epidemic of the Coronavirus Disease 2019 (COVID-19) in China
Authors: Hu Fu-Chang , Wen Fang-Yu
Published: April 2020

Background

How could we anticipate the progression of the ongoing epidemic of the coronavirus disease 2019 (COVID-19) in China? As a measure of transmissibility, we aimed to estimate concurrently the time-varying reproduction number over time during the COVID-19 epidemic in China.

Methods

We extracted the epidemic data from the “Tracking the Epidemic” website of the Chinese Center for Disease Control and Prevention for the duration of January 19, 2020 and March 14, 2020. Then, we specified two plausible distributions of serial interval to apply the novel estimation method implemented in the incidence and EpiEstim packages to the data of daily new confirmed cases for robustly estimating the time-varying reproduction number in the R software.

Results

The epidemic curve of daily new confirmed cases in China peaked around February 4–6, 2020, and then declined gradually, except the very high peak on February 12, 2020 owing to the added clinically diagnosed cases of the Hubei Province. Under two specified plausible scenarios for the distribution of serial interval, both curves of the estimated time-varying reproduction numbers fell below 1.0 around February 17–18, 2020. Finally, the COVID-19 epidemic in China abated around March 7–8, 2020, indicating that the prompt and aggressive control measures of China were effective.

Conclusion

Seeing the estimated time-varying reproduction number going downhill speedily was more informative than looking for the drops in the daily number of new confirmed cases during an ongoing epidemic of infectious disease. We urged public health authorities and scientists to estimate time-varying reproduction numbers routinely during an epidemic of infectious diseases and to report them daily to the public until the end of the epidemic.
Estimating Burden of Disease among blind individuals with Non-24-Hour Sleep-Wake Disorder
Authors: Van Draanen Lauren , Xiao Derek , Polymeropoulos Mihael H.
Published: April 2020

Purpose

To quantify the burden of disease in blind patients with Non-24-Hour Sleep-Wake Disorder (N24HSWD), utilizing longitudinal sleep diary data. N24HSWD is a circadian disorder characterized by a cyclical pattern of aberrant circadian and sleep-wake cycles that are associated with increased frequency of sleep episodes during the school/work day hours. Daytime sleep episodes will decrease the opportunity of school/work participation significantly impacting the quality of life of the patient.

Methods

We used the day time sleep diary data from a period of approximately 90 days in blind individuals with a sleep complaint, which were identified from a group of blind individuals with N24HSWD (n=121) and a control group of blind individuals without N24HSWD (n=57).

Results

N24HSWD patients had more frequent and longer episodes of daytime sleep as compared to a control group. N24HSWD patients also had significantly fewer healthy days, defined by daytime sleep free days (DSFD), as compared to the control group.

Conclusion

Daytime sleep free day (DSFD) is a useful and specific measure of disease burden in patients with N24HSWD and it is predicted to be correlated with the standardized HRQOL-4, Healthy Days measurement.
Nasal microbiota exhibit neither reproducible nor orderly dynamics following rhinoviral infection
Authors: Nimmagadda Sai N. , Midani Firas S. , Durand Heather , Reese Aspen T. , Murdoch Caitlin C. , Nicholson Bradley P. , Veldman Timothy , Burke Thomas W. , Zaas Aimee K. , Woods Christopher W. , Ginsburg Geoffrey S. , David Lawrence A.
Published: April 2020

Background

How human-associated microbial communities resist and respond to perturbations remains incompletely understood. Viral challenge provides one opportunity to test how human microbiota respond to disturbance.

Methods

Using an experimental human rhinovirus infection challenge model, we explored how viral infection may alter microbiota of the upper respiratory tract (URT). Healthy human volunteers were inoculated with HRV serotype 39. Samples were collected by lavage before and after inoculation from healthy (sham inoculated, n=7) and infected (n=15) individuals and subjected to 16S rRNA gene sequencing through amplification of the V4 hypervariable region.

Results

No evidence for differences in community alpha-diversity between cohorts was observed. The composition of microbiota of sham-treated and infected subjects did not appear distinguishable and no taxa were significantly associated with infection status. We did not observe support for a correlation between microbial dynamics and counts of specific monocytes. Subject identity was found to be the strongest determinant of community structure in our dataset.

Conclusions

Overall, our findings do not suggest a consistent nasopharyngeal microbiota response to rhinovirus challenge. We support the conclusion that this microbial community is individualized. Broadly, our findings contribute to our understanding of how and when immune responses to viruses affect bacterial communities in the URT.
Coronavirus epidemic: prediction and controlling measures
Authors: Pejman Mohammad Mehdi , Fereidooni Armaghan
Published: April 2020

The COVID-19 outbreak has caused over 1.7 million (still increasing) confirmed cases globally as of April 10th, 2020. The levels of spread and severity of the virus lead to a wide-spread political and economic turmoil. We believe that two critical contributing factors need to be taken into account by the authorities to make effective decisions for controlling the spread of the virus: (i) being familiar with the most effective controlling measures and (ii) having a mathematical model to predict the spread of the virus. In this study, we provided information regarding both of these crucial factors. First, we investigated the importance of different measures such as quarantine, isolation, face mask, social distancing, etc. in controlling the virus in various countries. We then present a mathematical model to predict the spread of the virus in different countries. Our prediction shows an excellent match with the actual data up to now.
Ad-hoc Assembly of Lean Extracorporeal Membrane Oxygenation Systems for COVID-19
Authors: Hunziker Patrick , Zenklusen Urs
Published: April 2020

Background

The COVID-19 epidemic is overwhelming intensive care units with bilateral pneumonia patients requiring respiratory assistance. Bottlenecks in availability of ventilators and extracorporeal membrane oxygenation may contribute to mortality, implying ethically difficult rationing decisions. It is unclear if accelerated equipment production will meet demand, calling for fallback solutions for life support in worst-case scenarios.

Methods

Veno-venous extracorporeal gas exchange (VV-ECMO) can provide vital support in bilateral lung failure. VV-ECMO essentially comprises large flow venous accesses, membrane gas exchange, and a blood pump. As thousands of FDA and CE certified Impella blood pumps and consoles are distributed globally for cardiac support, we explored ad-hoc assembly of lean ECMO systems by embedding Impella pumps coaxially in tubes in combination with standard gas exchangers.

Results

Ad-hoc integration of Impella blood pumps with gas exchange modules, standard cannulas for large bore venous access, regular ECMO tubing, Y-pieces and connectors led to lean ECMO systems with stable performance over several days. Oxygenation of 2.5-5 L of blood/minute is realistic. Benefit/risk analysis appears favorable if a patient requires respiratory support but cannot be supported because of lack of ventilators or unavailability of a required ECMO system.

Conclusion

Ad-hoc assembly of veno-venous ECMOs using Impella pumps is feasible and results in stable blood flow across gas exchange modules. However, such off-label use of the devices calls for specific ethical and regulatory considerations prior to their use as last resort in patients for whom no other treatment modalities are available.
Steroid-responsive encephalitis in Covid-19 disease
Authors: Pilotto Andrea , Odolini Silvia , Masciocchi S Stefano , Comelli Agnese , Volonghi Irene , Gazzina Stefano , Nocivelli Sara , Pezzini Alessandro , Focà Emanuele , Caruso Arnaldo , Leonardi Matilde , Pasolini Maria Pia , Gasparotti R Roberto , Castelli F Francesco , Ashton Nicholas J. , Blennow Kaj , Zetterberg Henrik , Padovani Alessandro
Published: April 2020

Covid-19 infection has the potential for targeting the central nervous system and several neurological symptoms have been described in patients with severe respiratory distress. Here we described the case of a 60-year old subject with SARS-CoV-2 infection but only mild respiratory abnormalities who developed an akinetic mutism due to encephalitis. MRI was negative whereas EEG showed generalized theta slowing. CSF analyses during the acute stage were negative for SARS-CoV-2, positive for pleocytosis and hyperproteinorrachia, and showed increased IL-8 and TNF-α concentrations while other infectious or autoimmune disorders were excluded. A progressive clinical improvement along with a reduction of CSF parameters was observed after high-dose steroid treatment, thus arguing for an inflammatory-mediated brain involvement related to Covid-19.
Shut it down: a cross country panel analysis on the efficacy of lockdown measures
Authors: Alfano Vincenzo , Ercolano Salvatore
Published: April 2020

Coronavirus pandemic outbreak from China in the December 2019 and since then has quickly spread all over the world. National governments introduced policies aimed to reduce the probability to contract the virus, such as lockdown measures, in order to limit the outbreak. Lockdown fostered a debate about the effective need and the optimal duration of such measures. Indeed, these policies have a high price, being characterized by the alt of many productive activities. The aim of this note is to provide preliminary evidences about the efficacy of lockdown measures all over the world, by the means of a panel data quantitative analysis. Our results confirm the efficacy of such measures, and that the average time to have effects in terms of a reduction of cases is of about ten days. Furthermore the beneficial effects of a lockdown keep reducing the new cases with a linear trend for at least the ten successive days.
COVID-19 pandemic: A Hill type mathematical model predicts the US death number and the reopening date
Authors: Aboelkassem Yasser
Published: April 2020

A mathematical model that can be used to estimate the total number of cases and deaths due to COVID-19 pandemic is presented in this study. The parameters and the associated uncertainty in the model are optimized and quantified using various reported data sets reported from different countries. The results suggest that, by the mid of June or early July 2020, the outbreak will strongly decay and the US will have about 800K confirmed cases and less than 50K deaths.

Significance Statement

This study presents a mathematical model that can be used to estimate the total number of cases and deaths in the US due to COVID-19. The model forecasting about < 800K cases and < 50K total numbers of deaths in the United States. The results suggest that late May or early June, 2020 is probably a good time to end the shutdown order and reopen the country for the daily routine business.
Analysis of the SARS-Cov-2 epidemic in Lombardy (Italy) in its early phase. Are we going in the right direction?
Authors: Riccio Angelo
Published: April 2020

BACKGROUND

We described the epidemiological features of the codiv-19 outbreak, and evaluated the impact of interventions measures on the epidemic in the Lombardy region, Italy.

METHODS

Laboratory-confirmed covid-19 cases reported through the beginning of April were extracted from the Italian Civil Protection database. Based on key events and interventions, we divided the epidemic into three periods: before February 21, from February 22 to early March, after early March. We compared epidemiological characteristics across periods and developed a modified susceptible-exposed-infectious-recovered model to study the epidemic and evaluate the impact of interventions. We explicitly took into account for unascertained cases (positive cases with no symptoms or mild symptoms that have not been accounted for in official statistics).

RESULTS

Currently, the number of positive active cases has increased to around 30,000 in the Lombardy region. Due to restriction measures, the effective reproduction number dropped from 3.33 (95% CI: 2.03–3.69) during the first period, to 2.36 (95% CI: 2.21–2.70) during the second period. In the third period, the effective reproduction number is estimated to have dropped to 1.49 (95% CI: 1.35–1.62). The model estimates a great proportion of unascertained cases, about 90% of infected people has not been accounted for in official statistics.

CONCLUSIONS

Considerable countermeasures have slowed down the covid-19 outbreak in the Lombardy region. However, notwithstanding the long-lasting lockdown period, the epidemic is still not under control. The effective reproduction number, according to the model used in this work, is still greater than 1.0. Estimation of unascertained cases has important implications on continuing surveillance and interventions.
Markovian Random Walk Modeling and Visualization of the Epidemic Spread of COVID-19
Authors: Akay Haluk , Barbastathis George
Published: April 2020

Abstract

The epidemic spread of CoVID-19 has resulted in confirmed cases of viral respiratory illness in more than 1.4 million people around the world as of April 7th, 2020 [1]. However, different regions have experienced the spread of this disease differently. Here, we develop a Markovian random-walk spatial extension of a quarantine-enhanced SIR model to measure, visualize and forecast the effect of susceptible population density, testing rate, and social distancing and quarantine policies on epidemic spreading. The model is used to simulate the spread of CoVID-19 in the regions of Hubei, China; South Korea; Iran; and Spain. The model allows for evaluating the results of different policies both quantitatively and visually as means of better understanding and controlling the spread of the disease.
Long-term Coexistence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) with Antibody Response in Coronavirus Disease 2019 (COVID-19) Patients
Authors: Wang Bin , Wang Li , Kong Xianggen , Geng Jin , Xiao Di , Ma Chunhong , Jiang Xue-Mei , Wang Pei-Hui
Published: April 2020

Severe acute respiratory syndrome coronavirus 2 infection causing coronavirus disease 2019 has spread worldwide. Whether antibodies are important for the adaptive immune responses against SARS-CoV-2 infection needs to be determined. Here, 26 cases of COVID-19 in Jinan, China, were examined and shown to be mild or with common clinical symptoms and no cases of severe symptoms were found among these patients. A striking feature of some patients is that SARS-CoV-2 could exist in patients who have virus-specific IgG antibodies for a very long period, with two cases for up to 50 days. One COVID-19 patient who did not produce any SARS-CoV-2-bound IgG successfully cleared SARS-CoV-2 after 46 days of illness, revealing that without antibody-mediated adaptive immunity, innate immunity may still be powerful enough to eliminate SARS-CoV-2. Overall, this report may provide a basis for further analysis of both innate and adaptive immunity in SARS-CoV-2 clearance, especially in non-severe cases. This study also has implications for understanding the pathogenesis and treatment of SARS-CoV-2.
Age could be driving variable SARS-CoV-2 epidemic trajectories worldwide
Authors: Ayoub Houssein H. , Chemaitelly Hiam , Seedat Shaheen , Mumtaz Ghina R. , Makhoul Monia , Abu-Raddad Laith J.
Published: April 2020

Background

Current geographic spread of documented severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections shows heterogeneity. This study explores the role of age in potentially driving differentials in infection spread, epidemic potential, and rates of disease severity and mortality across countries.

Methods

An age-stratified deterministic mathematical model that describes SARS-CoV-2 transmission dynamics was applied to 159 countries and territories with a population ≥1 million.

Results

Assuming worst-case scenario for the pandemic, the results indicate that there could be stark regional differences in epidemic trajectories driven by differences in the distribution of the population by age. In the African Region (median age: 18.9 years), the median R0 was 1.05 versus 2.05 in the European Region (median age: 41.7 years), and the median (per 100 persons) for the infections rate was 22.5 (versus 69.0), for severe and/or critical disease cases rate was 3.3 (versus 13.0), and for death rate was 0.5 (versus 3.9).

Conclusions

Age could be a driver of variable SARS-CoV-2 epidemic trajectories worldwide. Countries with sizable adult and/or elderly populations and smaller children populations may experience large and rapid epidemics in absence of interventions. Meanwhile, countries with predominantly younger age cohorts may experience smaller and slower epidemics. These predictions, however, should not lead to complacency, as the pandemic could still have a heavy toll nearly everywhere.
Public policy and economic dynamics of COVID-19 spread: a mathematical modeling study
Authors: Goldsztejn Uri , Schwartzman David , Nehorai Arye
Published: April 2020

With the COVID-19 pandemic infecting millions of people, large-scale isolation policies have been enacted across the globe. To assess the impact of isolation measures on deaths, hospitalizations, and economic output, we create a mathematical model to simulate the spread of COVID-19, incorporating effects of restrictive measures and segmenting the population based on health risk and economic vulnerability. Policymakers make isolation policy decisions based on current levels of disease spread and economic damage. For 76 weeks in a population of 330 million, we simulate a baseline scenario leaving strong isolation restrictions in place, rapidly reducing isolation restrictions for non-seniors shortly after outbreak containment, and gradually relaxing isolation restrictions for non-seniors. We used 76 weeks as an approximation of the time at which a vaccine will be available. In the baseline scenario, there are 235,724 deaths and the economy shrinks by 34.0%. With a rapid relaxation, a second outbreak takes place, with 525,558 deaths, and the economy shrinks by 32.3%. With a gradual relaxation, there are 262,917 deaths, and the economy shrinks by 29.8%. We also show that hospitalizations, deaths, and economic output are quite sensitive to disease spread by asymptomatic people. Strict restrictions on seniors with very gradual lifting of isolation for non-seniors results in a limited number of deaths and lesser economic damage. Therefore, we recommend this strategy and measures that reduce non-isolated disease spread to control the pandemic while making isolation economically viable.
Onsite virtual classroom versus physical classroom: A comparative study of learning and student perception in orthopaedic training
Authors: Puthezhath Kishore
Published: April 2020

Introduction

More students are posted in the orthopaedic out-patient departments than before. Lack of clinical space to accommodate students is a frequently cited problem. Virtual learning allows for an adjustable location and is scalable. We aimed to compare both the effectiveness and student satisfaction level between onsite virtual classroom and physical classroom in teaching orthopaedics to a group of undergraduate medical students.

Methods

A quasi-experimental non-equivalent group design study was conducted with 49 final-year medical students participating in orthopaedic training between November 2019 to January 2020. These students were randomly allocated into two groups, experimental (virtual classroom) and comparison (physical learning). The experimental group received an onsite virtual learning environment, whereas the control group received the same content in a physical classroom. Pre and post-tests that consisted of multiple choice questions were administered. At the end of the class, the students completed a 5-point Likert scale satisfaction level evaluation questionnaire.

Results

The post-test knowledge scores between virtual classroom (M=78.2,SD=12.74) and Physical classroom (M=77.92,SD=10.31) were not different (z= 0.00, p=1.00). Though the overall perceptions of learning were positive, some frustrations were apparent and the student satisfaction was significantly better (z=-4.60, p value=0.00) with the physical classroom (M=3.83,SD=0.16) compared to virtual classroom (M=3.5,SD=0.23).

Conclusions

Onsite virtual activities are not as satisfying as physical classroom in the opinion of the students, but they are successful strategies in learning that can be used in outpatient orthopaedic clinics to address the problem of lack of space. Students learn content focused on orthopaedic clinical learning objectives as well using onsite virtual classroom as they do in the traditional classroom setting.
Analysis of COVID-19 spread in South Korea using the SIR model with time-dependent parameters and deep learning
Authors: Jo Hyeontae , Son Hwijae , Hwang Hyung Ju , Jung Se Young
Published: April 2020

Mathematical modeling is a process aimed at finding a mathematical description of a system and translating it into a relational expression. When a system is continuously changing over time (e.g., infectious diseases) differential equations, which may include parameters, are used for modeling the system. The process of finding those parameters that best fit the given data from the system is called an inverse problem. This study aims at analyzing the novel coronavirus infection (COVID-19) spread in South Korea using the susceptible-infected-recovered (SIR) model. We collect the data from Korea Centers for Disease Control & Prevention (KCDC). We assume that each parameter in the SIR model is a function of time so that we can compute important parameters, such as the basic reproduction number (R0), more delicately. Using neural networks, we propose a method to find the best time-varying parameters and the solution for the model simultaneously. Moreover, using time-dependent parameters, we find that traditional numerical algorithms, such as the Runge-Kutta methods, can successfully approximate the SIR model while fitting the COVID-19 data, thus modeling the propagation patterns of COVID-19 more precisely.
The Coronavirus Disease (COVID-19) Pandemic: Simulation-Based Assessment of Outbreak Responses and Post Peak Strategies
Authors: Struben Jeroen
Published: April 2020

It is critical to understand the impact of distinct policy interventions to the ongoing coronavirus disease pandemic. I develop a flexible behavioral, dynamic, and sectorial epidemic policy model comprising both endogenous virus transmission and public health and citizen responses. Applicable to the full epidemic cycle including confinement, deconfinement, and resurgence, the model allows exploring the multivariate impact of distinct policy interventions, including general and targeted testing and social contact reduction efforts. Using a cross-sectional calibration to data on the ongoing coronavirus disease outbreak about reported cases and deaths, tests performed, and social interactions from six countries (South Korea, Germany, Italy, France, Sweden, and the United States), I demonstrate how early, rapid, and extensive buildup of testing and social contact reduction efforts interplay to suppress the outbreak. I then use the model to show and quantify limits to the extent of deconfinement and illustrate the critical role of targeted approaches for managing post peak deconfinement and resurgence. To aid necessary public and expert understanding of outbreak control strategies the model is accessible in the form of a web-based management flight simulator.
Initial stage of the COVID-19 infection process in human population
Authors: Trigger S.A.
Published: April 2020

The simplest approximation for the first stages of the infection spread is considered. The specific feature of the COVID-19 characterized by its long latent period is taken into account. Exponential increase of numbers of infected people is determined by the half period of the maximal latent time for the COVID-19. The averaging over latent period leads to additional increase of the infected numbers.

PACS number(s)

02.50.-r, 05.60.-k, 82.39.-k, 87.19.Xx
A COVID-19 Risk Assessment for the US Labor Force
Authors: Maher Samantha , Hill Alexandra E , Britton Peter , Fenichel Eli P. , Daszak Peter , Zambrana-Torrelio Carlos , Bayham Jude
Published: April 2020

The consequences of COVID-19 infection varies substantially based on individual social risk factors and predisposing health conditions. Understanding this variability may be critical for targeting COVID-19 control measures, resources and policies, including efforts to return people back to the workplace. We compiled individual level data from the National Health Information Survey and Quarterly Census of Earnings and Wages to estimate the number of at-risk workers for each US county and industry, accounting for both social and health risks. Nearly 80% of all workers have at least one health risk and 11% are over 60 with an additional health risk. We document important variation in the at-risk population across states, counties, and industries that could provide a strategic underpinning to a staged return to work.

One Sentence Summary

There is important variability in the proportion of the US workforce at risk for COVID-19 complications across regions, counties, and industries that should be considered when targeting control and relief policies, and a staged return to work.
An evaluation of the fracture resistance of endodontically treated extracted teeth restored with Titanium, Carbon and Fibre posts : An in-vitro randomized control trial
Authors: Behera Sonali Suvadarsini , Choudhury Gopal Krishna , Mohapatra Abhilash , Panigrahi Sandeep Kumar
Published: April 2020

Post and core enforcement is done for Root Canal Treated (RCT) tooth as per need. Several posts and core systems are available claiming superiority. The usual post and core enforcement used in set up in India include that based on titanium and fiber. An unbiased in-vitro randomized control trial to compare the fracture resistance of RCT teeth with those restored with Titanium, Carbon and Fibre posts was hence conducted. The trial was conducted in a tertiary care dental institute in the eastern part of India. A total of 40 normal samples of extracted first mandibular were randomized to four groups (A through D) of ten samples each. Block random design was used, random number sequence was generated through computer centrally. The process was blinded, also during analysis. Group A (control) was RCT teeth with intact coronal structure while group B, C and D (interventional) were RCT teeth restored with titanium, carbon and fiber posts respectively. Universal Testing Machine (‘Tinius Olsen, H50KS’) was used for testing fracture resistance. The data were analyzed using Kruskal Wallis test followed by pairwise comparison in Stata v 12.1 SE. All statistical interpretations were done at p= 0.05 levels. The median fracture resistance among the groups was significantly different (p=0.000). Median fracture resistance of control, titanium, and fiber groups were similar (p >0.05). The median fracture resistance of the carbon group was inferior to all other groups (p<0.05). It was concluded that fiber and titanium post and core systems similar in strength to only root canal treated tooth, and scored better as compared to carbon post and core system.
Impact of lockdown on COVID-19 epidemic in Île-de-France and possible exit strategies
Authors: Domenico Laura Di , Pullano Giulia , Sabbatini Chiara E. , Boëlle Pierre-Yves , Colizza Vittoria
Published: April 2020

Background

More than half of the global population is under strict forms of social distancing. Estimating the expected impact of lockdown and exit strategies is critical to inform decision makers on the management of the COVID-19 health crisis.

Methods

We use a stochastic age-structured transmission model integrating data on age profile and social contacts in Île-de-France to (i) assess the epidemic in the region, (ii) evaluate the impact of lockdown, and (iii) propose possible exit strategies and estimate their effectiveness. The model is calibrated to hospital admission data before lockdown. Interventions are modeled by reconstructing the associated changes in the contact matrices and informed by mobility reductions during lockdown evaluated from mobile phone data. Different types and durations of social distancing are simulated, including progressive and targeted strategies, with large-scale testing.

Results

We estimate the reproductive number at 3.18 [3.09, 3.24] (95% confidence interval) prior to lockdown and at 0.68 [0.66, 0.69] during lockdown, thanks to an 81% reduction of the average number of contacts. Model predictions capture the disease dynamics during lockdown, showing the epidemic curve reaching ICU system capacity, largely strengthened during the emergency, and slowly decreasing. Results suggest that physical contacts outside households were largely avoided during lockdown. Lifting the lockdown with no exit strategy would lead to a second wave overwhelming the healthcare system, if conditions return to normal. Extensive case-finding and isolation are required for social distancing strategies to gradually relax lockdown constraints.

Conclusions

As France experiences the first wave of COVID-19 pandemic in lockdown, intensive forms of social distancing are required in the upcoming months due to the currently low population immunity. Extensive case-finding and isolation would allow the partial release of the socio-economic pressure caused by extreme measures, while avoiding healthcare demand exceeding capacity. Response planning needs to urgently prioritize the logistics and capacity for these interventions.
Epigenetic profiling of Italian patients identified methylation sites associated with hereditary Transthyretin amyloidosis
Authors: De Lillo Antonella , Pathak Gita , De Angelis Flavio , Di Girolamo Marco , Luigetti Marco , Sabatelli Mario , Perfetto Federico , Frusconi Sabrina , Manfellotto Dario , Fuciarelli Maria , Polimanti Renato
Published: April 2020

Hereditary Transthyretin (TTR) Amyloidosis (hATTR) is a rare life-threatening disorder caused by amyloidogenic coding mutations located in TTR gene. To understand the high phenotypic variability observed among carriers of TTR disease-causing mutations, we conducted an epigenome-wide association study (EWAS) assessing more than 700,000 methylation sites and testing epigenetic difference of TTR coding mutation carriers vs. non-carriers, We observed a significant methylation change at cg09097335 site located in Beta-secretase 2 (BACE2) gene (beta =-0.60, p=6.26x10-8). This gene is involved in a protein interaction network enriched for biological processes and molecular pathways related to amyloid-beta metabolism (Gene Ontology:0050435, q=0.007), amyloid fiber formation (Reactome HSA-977225, q=0.008), and Alzheimers disease (KEGG hsa05010, q=2.2x10-4). Additionally, TTR and BACE2 share APP (Amyloid-beta precursor protein) as a validated protein interactor. Within TTR gene region, we observed that Val30Met disrupts a methylation site, cg13139646, causing a drastic hypomethylation in carriers of this amyloidogenic mutation (beta=-2.18, p=3.34x10-11). Cg13139646 showed co-methylation with cg19203115 (r2=0.32), which showed significant epigenetic differences between symptomatic and asymptomatic carriers of amyloidogenic mutations (beta=-0.56, p=8.6x10-4). In conclusion, we provide novel insights related to the molecular mechanisms involved in the complex heterogeneity of hATTR, highlighting the role of epigenetic regulation in this rare disorder.
Population simulations of COVID-19 outbreaks provide tools for risk assessment and continuity planning
Authors: Peng Bo , Amos Christopher I.
Published: April 2020

Essential industrial sectors, healthcare systems, and government agencies must continue operations despite the risk of COVID-19 infection. They need tools to assess risks associated with operations, so they can devise emergency plans. We developed a population-based simulator to study COVID-19 outbreaks in enclosed environments and evaluate the effectiveness of preventative measures and action plans, such as pre-dispatch quarantine and removal of symptomatic cases.

Availability

The simulation tool is publicly available at http://github.com/ictr/covid19-outbreak-simulator and is free for non-commercial use.
Genetic Architecture of Maize Rind Strength Revealed by the Analysis of Divergently Selected Populations
Authors: Kumar Rohit , Gyawali Abiskar , Morrison Ginnie D. , Saski Christopher A. , Robertson Daniel J. , Tharayil Nishanth , Schaefer Robert J. , Beissinger Timothy M. , Sekhon Rajandeep S.
Published: April 2020

Stalk lodging, breakage of the stalk at or below the ear, causes substantial yield losses in maize. The strength of the stalk rind, commonly measured as rind penetrometer resistance (RPR), is an important contributor to stalk lodging resistance. To enhance RPR genetic architecture, we conducted selection mapping on populations developed by 15 cycles of divergent selection for high (C15-H) and low (C15-L) RPR. We also performed time-course transcriptome and metabolic analyses on developing stalks of high (Hrpr1) and low (Lrpr1) RPR inbred lines derived from the C15-H and C15-L populations, respectively. Divergent selection significantly altered allele frequencies at 3,656 and 3,412 single nucleotide polymorphisms (SNP) in the C15-H and C15-L populations, respectively. While the majority of the SNPs under selection were unique, 110 SNPs were common in both populations indicating the fixation of alleles with alternative effects. Remarkably, preferential selection on the genomic regions associated with lignin and polysaccharide biosynthesis genes was observed in C15-H and C15-L populations, respectively. This observation was supported by higher lignification and lower extractability of cell wall-bound sugars in Hrpr1 compared to Lrpr1. Tricin, a monolignol important for incorporation of lignin in grass cell walls, emerged as a key determinant of the different cell wall properties of Hrpr1 and Lrpr1. Integration of selection mapping with transcriptomics and previous genetic studies on RPR identified 40 novel candidate genes including ZmMYB31, ZmNAC25, ZmMADS1, twoPALparalogues, two lichenases,ZmEXPA2, ZmIAA41, andCaleosin. Enhanced mechanistic and genetic understanding of RPR provides a foundation for improved stalk lodging resistance.
Telomere length in young patients with acute myocardial infarction without conventional risk factors: a pilot study from a South Asian population
Authors: Gupta Mohit , Jain Vardhmaan , Miglani Manjula , Girish M. P. , Pasha Q. , Virani Salim S. , Kalra Ankur
Published: April 2020

Background

Myocardial infarction (MI) in the young South Asian population is rising alarmingly. There is an urgent need to identify novel markers to aid early risk estimation. Telomeres are long known to be markers of aging, and shorter telomeres have been reported in cardiovascular diseases (CVDs). Telomeres have been shown to be involved in modulating inflammation and oxidative stresses in other diseases. We aimed to identify the association of telomere length in young MI patients.

Methods & Results

In a case-control study of 77 subjects in each group, DNA extraction from peripheral blood leukocytes was carried out and the relative telomere length was estimated by quantitative PCR. The results were adjusted with various demographic parameters like age and gender. The correlation studies were carried out between Telomere length and lipid profile parameters (LDL, HDL, TG, TC), clinical and demographic parameters of the subjects using partial correlations.

Results

The relative telomere length was significantly shorter in Young MI patients (31-45 years) compared to matched healthy controls (p<0.0001). Interestingly, in a gender-based comparison, the female patients had shorter telomere length (p<0.01). Correlation analysis of the length with angiographic patterns and even the lipid profile did not reveal significance (p>0.05).

Conclusion

Our findings reveal the presence of shorter telomere length in patients of young MI in South Asia. Higher prevalence of stress and other factors may play a role in affecting telomere length. Larger studies are needed to confirm these findings.
Chest Computed Tomography for the Diagnosis of Patients with Coronavirus Disease 2019 (COVID-19): A Rapid Review and Meta-Analysis
Authors: Lv Meng , Wang Mengshu , Yang Nan , Luo Xufei , Li Wei , Chen Xin , Liu Yunlan , Ren Mengjuan , Zhang Xianzhuo , Wang Ling , Ma Yanfang , Lei Junqiang , Fukuoka Toshio , Ahn Hyeong Sik , Lee Myeong Soo , Luo Zhengxiu , Chen Yaolong , Liu Enmei , Tian Jinhui , Wang Xiaohui
Published: April 2020

Background

The outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations of patients with COVID-19.

Methods

We conducted a rapid review and meta-analysis on studies about the use of chest CT for the diagnosis of COVID-19. We comprehensively searched databases and preprint servers on chest CT for patients with COVID-19 between 1 January 2020 and 31 March 2020. The primary outcome was the sensitivity of chest CT imaging. We also conducted subgroup analyses and evaluated the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

Results

A total of 104 studies with 5694 patients were included. Using RT-PCR results as reference, a meta-analysis based on 64 studies estimated the sensitivity of chest CT imaging in COVID-19 was 99% (95% CI, 0.97-1.00). If case reports were excluded, the sensitivity in case series was 96% (95% CI, 0.93-0.99). The sensitivity of CT scan in confirmed patients under 18 years old was only 66% (95% CI, 0.11-1.00). The most common imaging manifestation was ground-glass opacities (GGO) which was found in 75% (95% CI, 0.68-0.82) of the patients. The pooled probability of bilateral involvement was 84% (95% CI, 0.81-0.88). The most commonly involved lobes were the right lower lobe (84%, 95% CI, 0.78-0.90) and left lower lobe (81%, 95% CI, 0.74-0.87). The quality of evidence was low across all outcomes.

Conclusions

In conclusion, this meta-analysis indicated that chest CT scan had a high sensitivity in diagnosis of patients with COVID-19. Therefore, CT can potentially be used to assist in the diagnosis of COVID-19.
The end of the social confinement in Spain and the COVID-19 re-emergence risk
Authors: López Leonardo , Rodó Xavier
Published: April 2020

After the spread of SARS-CoV-2 epidemic out of China, the world approaches the 2 million declared infected cases and death toll rises well above the 100 thousand. The course of pandemic evolution has shown great differences among countries and not much is yet known about the level of generated immunity, which might appear not to be long-lasting. In this situation, management of a recurrent disease seems to be a plausible scenario that countries worldwide will have to face, before effective drugs or a vaccine appear. Spain in Europe, appears to be the first country deciding to partly lift the strict social distancing regulations imposed. Whether this action may lead to further epidemic recrudescence, to a following second wave of cases or conversely, help return to previous normality, is a subject of great debate and interest to all other countries affected by COVID-19. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we had also incorporated effects of social confinement. We now modify this previous model configuration to mimic potential post-confinement scenarios, by simulating from instant massive liberation of different portions of the confined population, up to a more gradual incorporation of people to work. Results show how current lockdown conditions should be extended at least two weeks more to prevent a new escalation in cases and deaths, as well as a larger second wave occurring in just a few months. Conversely, best-case scenario in terms of lower COVID-19 incidence and casualties should gradually incorporate workers back in a daily proportion at most 30 percent higher than that of previous confinement. The former should begin not earlier than by the end of April and it would represent approximately 600 thousand people or a 3.75% rate for the whole of Spain.
How high and long will the COVID-19 wave be? A data-driven approach to model and predict the COVID-19 epidemic and the required capacity for the German health system
Authors: Klabunde Thomas , Giegerich Clemens
Published: April 2020

Background and objective

In March 2020 the SARS-CoV-2 outbreak has been declared as global pandemic. Most countries have implemented numerous “social distancing” measures in order to limit its transmission and control the outbreak. This study aims to describe the impact of these control measures on the spread of the disease for Italy and Germany, forecast the epidemic trend of COVID-19 in both countries and estimate the medical capacity requirements in terms of hospital beds and intensive care units (ICUs) for optimal clinical treatment of severe and critical COVID-19 patients, for the Germany health system.

Methods

We used an exponential decline function to model the trajectory of the daily growth rate of infections in Italy and Germany. A linear regression of the logarithmic growth rate functions of different stages allowed to describe the impact of the “social distancing” measures leading to a faster decline of the growth rate in both countries. We used the linear model to predict the number of diagnosed and fatal COVID-19 cases from April 10th until May 31st. For Germany we estimated the required daily number of hospital beds and intensive care units (ICU) using clinical observations on the average lengths of a hospital stay for the severe and critical COVID-19 patients.

Results

Analyzing the data from Germany and Italy allowed us to identify changes in the trajectory of the growth rate of infection most likely resulted from the various “social distancing” measures implemented. In Italy a stronger decline in the growth rate was observed around the week of March 17th, whereas for Germany the stronger decline occurred approximately a week later (the week of March 23rd). Under the assumption that the impact of the measures will last, the total size of the outbreak can be estimated to 155,000 cases in Germany (range 140,000-180,000) and to 185,000 cases in Italy (range 175,000-200,000). For Germany the total number of deaths until May 31st is calculated to 3,850 (range 3,500-4,450). Based on the projected number of new COVID-19 cases we expect that the hospital capacity requirements for severe and critical cases in Germany will decline from the 2nd week of April onwards from 13,500 to ∼2500 hospital beds (range 1500-4300) and from 2500 to ∼500 ICU beds in early May (range 300-800).

Conclusions

The modeling effort presented here provides a valuable framework to capture the impact of the “social distancing” measures on the COVID-19 epidemic in European countries and to forecast the future trend of daily COVID-19 cases. It provides a tool for medical authorities in Germany and other countries to help inform the required hospital capacity of the health care system. Germany appears to be in the middle of the (first) COVID-19 outbreak wave and the German health system is well prepared to handle it with the available capacities.