bluuebunny/crossref_metadata_2025 huggingface dataset:
“Your womb, your choice!” Making an informed decision regarding the timing of pregnancy following miscarriage
Authors: Shah Faizan , Bhattacharya Sohinee , Lamont Kathleen , Morgan Heather May
Published: September 2020

The ideal interpregnancy interval (IPI) following a miscarriage is controversial as the World Health Organization (WHO) advise women to delay pregnancy for at least six months. Subsequent research has found that IPI less than six months is beneficial for both mother and baby. The impact of this guidance on the decision-making process for couples/women in this predicament is unknown.

Views of women regarding the optimum IPI following miscarriage were investigated using a thematic framework applied to discussion threads from a popular online forum, Mumsnet (https://www.mumsnet.com). A systematic search of all online information was also undertaken to identify all relevant patient information regarding conceiving another pregnancy after a miscarriage. The findings from the search were tabulated and analysed in relation to the themes identified from the discussion threads on Mumsnet. Ninety-four discussion threads were included. Women saw no reason to wait if they felt ready. Women posted about their frustrations at the multiple sources of conflicting advice they received, at the lack of professional sympathy and felt that being told to wait before trying to conceive after a miscarriage was outdated advice. However, these findings were not corroborated by the patient information currently available online. All web-based patient information gave consistent advice – to wait for at least one normal period before trying to conceive again after a miscarriage and to try for another pregnancy when they felt physically mentally and emotionally ready. None advised waiting for six months. This study highlights that sometimes despite contradictory clinical advice, women are keen to make their own decisions regarding reproductive choice. These decisions are often empowered by peer support and advice which women trust over inconsistent information received from healthcare professionals. In this case, health information appears to have been updated in response to women’s choice rather than the other way around.

Research highlights

A knowledge gap exists in relation to the views of women regarding the ideal interpregnancy interval following miscarriage.

This study provides insights into the views and beliefs of women regarding the IPI following miscarriage

The dominant themes emerging from the study were: there is an array of conflicting advice being provided; there is no requirement to wait following a miscarriage; and the right time is when a couple feels physically, mentally and emotionally ready to try for another pregnancy.

Current web-based information for patients does not endorse the WHO’s guidance of waiting for at least six months before trying to conceive again after a miscarriage.
Seroprevalence of SARS-CoV-2 Antibodies Among 925 Staff Members in an Urban Hospital Accepting COVID-19 Patients in Osaka Prefecture, Japan
Authors: Nishida Tsuotmu , Iwahashi Hiromi , Yamauchi Kazuhiro , Kinoshita Noriko , Okauchi Yukiyoshi , Suzuki Norihiro , Inada Masami , Abe Kinya
Published: September 2020

Background

The subclinical severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rate in hospitals during the pandemic remains unclear. To evaluate the effectiveness of our hospital’s current nosocomial infection control, we conducted a serological survey of the anti-SARS-CoV-2 antibody (immunoglobulin G) among the staff of our hospital, which is treating coronavirus disease 2019 (COVID-19) patients.

Methods

The study design was cross-sectional. We measured anti-SARS-CoV-2 immunoglobulin G in the participants using a laboratory-based quantitative test (Abbott immunoassay), which has a sensitivity and specificity of 100% and 99.6%, respectively. To investigate the factors associated with seropositivity, we also obtained some information from the participants with an anonymous questionnaire.

Results

We invited 1133 staff members in our hospital, and 925 (82%) participated. The mean age of the participants was 40.0±11.8 years, and most were women (80.0%). According to job title, there were 149 medical doctors or dentists (16.0%), 489 nurses (52.9%), 140 medical technologists (14.2%), 49 healthcare providers (5.3%), and 98 administrative staff (10.5%). The overall prevalence of seropositivity for anti-SARS-CoV-2 IgG was 0.43% (4/925), which was similar to the control seroprevalence of 0.54% (16/2970)) in the general population in Osaka during the same period according to a government survey conducted with the same assay. Seropositive rates did not significantly differ according to job title, exposure to suspected or confirmed COVID-19 patients, or any other investigated factors.

Conclusion

The subclinical SARS-CoV-2 infection rate in our hospital was not higher than that in the general population under our nosocomial infection control measures.
Novel Coronavirus (COVID-19) health awareness among the United Arab Emirates Population
Authors: Qubais Saeed Balsam , Elbarazi Iffat , Barakat Mai
Published: September 2020

Background

In response to the global (COVID-19) epidemic, the United Arab Emirates (UAE) government is taking precautionary action to mitigate the spread of the virus and protect the safety and well-being of citizens, residents, and visitors. The knowledge and practices of individuals will probably have an important bearing on the course of the coronavirus disease 2019 pandemic. The aim of this study was to evaluate the knowledge and practices toward COVID-19 among the general public in the UAE during the current outbreak COVID-19.

Methods

A cross-sectional online survey of 1356 of respondents in the UAE we conducted during the epidemic outbreak between 9th to 24th June-2020. The questionnaire consisted of three sections: Socio-demographic, participants knowledge, and participants practices. Independent-samples t-test, one-way analysis of variance (ANOVA), chi-square, and binary logistic regression have used. A p-value of (p < 0.05) was considered statistically significant.

Results

Of the total sample, 72% were females, 47% % were aged between 30-49 years, 57.2% were from Sharjah, 65.6% had a college degree, and 40.6% were unemployed. The total correct score of knowledge and practices questions was high 85% and 90%, respectively.

Males gender, other marital status, and illiterate/primary educational levels had a lower level of knowledge and practices than others. participants aged 18-29 had little higher knowledge than other ages but had a lower level in practices, people who live in Abu Dhabi had better knowledge and practice than other emirates, employed people had a lower level of knowledge but higher in practice. Binary logistic regression analysis presented that females, 18-29 years, and married participants significantly associated with a higher score of knowledge, while female gender, over 30 years old, the martial status of singles, college-level and higher, unemployed, were significantly associated with high mean practice score.

Conclusions

To our knowledge, the current study is one of the first studies to evaluate the knowledge and practices of UAE population toward COVID-19. Most of the respondents demonstrate an excellent level of knowledge and awareness as well as proper conscious practices. Continuing to implement the health education programs pursued by the UAE is highly important to maintain the appropriate level of awareness among the public.
Evaluating the effects of cardiometabolic exposures on circulating proteins which may contribute to SARS-CoV-2 severity
Authors: Richardson Tom G , Fang Si , Mitchell Ruth E , Holmes Michael V , Smith George Davey
Published: September 2020

Background

Developing insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of critical importance to overcome the global pandemic caused by coronavirus disease 2019 (covid-19). In this study, we have applied Mendelian randomization (MR) to systematically evaluate the effect of 10 cardiometabolic risk factors and genetic liability to lifetime smoking on 97 circulating host proteins postulated to either interact or contribute to the maladaptive host response of SARS-CoV-2.

Methods

We applied the inverse variance weighted (IVW) approach and several robust MR methods in a two-sample setting to systemically estimate the genetically predicted effect of each risk factor in turn on levels of each circulating protein. Multivariable MR was conducted to simultaneously evaluate the effects of multiple risk factors on the same protein. We also applied MR using cis-regulatory variants at the genomic location responsible for encoding these proteins to estimate whether their circulating levels may influence SARS-CoV-2 severity.

Findings

In total, we identified evidence supporting 105 effects between risk factors and circulating proteins which were robust to multiple testing corrections and sensitivity analyses. For example, body mass index provided evidence of an effect on 23 circulating proteins with a variety of functions, such as inflammatory markers c-reactive protein (IVW Beta=0.34 per standard deviation change, 95% CI=0.26 to 0.41, P=2.19×10−16) and interleukin-1 receptor antagonist (IVW Beta=0.23, 95% CI=0.17 to 0.30, P=9.04×10−12). Further analyses using multivariable MR provided evidence that the effect of BMI on lowering immunoglobulin G, an antibody class involved in protecting the body from infection, is substantially mediated by raised triglycerides levels (IVW Beta=-0.18, 95% CI=-0.25 to -0.12, P=2.32×10−08, proportion mediated=44.1%). The strongest evidence that any of the circulating proteins highlighted by our initial analysis influence SARS-CoV-2 severity was identified for soluble glycoprotein 130 (odds ratio=1.81, 95% CI=1.25 to 2.62, P=0.002), a signal transductor for interleukin-6 type cytokines which are involved in the body’s inflammatory response. However, based on current case samples for severe SARS-CoV-2 we were unable to replicate findings in independent samples.

Interpretation

Our findings highlight several key proteins which are influenced by established exposures for disease. Future research to determine whether these circulating proteins mediate environmental effects onto risk of SARS-CoV-2 are warranted to help elucidate therapeutic strategies for covid-19 disease severity.

Funding

The Medical Research Council, the Wellcome Trust, the British Heart Foundation and UK Research and Innovation.
Estimating COVID-19 contribution to total excess mortality
Authors: Pimenoff Ville N. , Elfström Miriam , Baussano Iacopo , Björnstedt Mikael , Dillner Joakim
Published: September 2020

We compared the total excess mortality per week in relation to the reported Covid-19 related deaths in the Stockholm region (Sweden). Total excess mortality peaked under the weeks of high COVID-19-related mortality, but 25% of these deaths were not recognized as Covid-related. Most of these deaths occurred outside hospitals. Total all-cause mortality in excess to average all-cause mortality during the epidemic peak period may provide a comprehensive picture of the total burden of COVID19-related deaths.
External validation of the predictive performance of population pharmacokinetic models for phenobarbital in pediatric patients
Authors: Ryu Sunae , Jung Woo Jin , Jiao Zheng , Chae Jung-Woo , Yun Hwi-yeol
Published: September 2020

Aim

Several studies have reported population pharmacokinetic models for phenobarbital (PB), but the predictive performance of these models has not been well documented. This study aims to do external validation of the predictive performance in published pharmacokinetic models.

Methods

Therapeutic drug monitoring data collected in neonates and young infants treated with PB for seizure control, was used for external validation. A literature review was conducted through PubMed to identify population pharmacokinetic models. Prediction- and simulation-based diagnostics, and Bayesian forecasting were performed for external validation. The incorporation of size or maturity functions into the published models was also tested for prediction improvement.

Results

A total of 79 serum concentrations from 28 subjects were included in the external validation dataset. Seven population pharmacokinetic studies of PB were selected for evaluation. The model by Volleret al. [27] showed the best performance concerning prediction-based evaluation. In simulation-based analyses, the normalized prediction distribution error of two models (those of Shellhaaset al. [24] and Marsotet al. [25]) obeyed a normal distribution. Bayesian forecasting with more than one observation improved predictive capability. Incorporation of both allometric size scaling and maturation function generally enhanced the predictive performance, but with marked improvement for the adult pharmacokinetic model.

Conclusion

The predictive performance of published pharmacokinetic models of PB was diverse, and validation may be necessary to extrapolate to different clinical settings. Our findings suggest that Bayesian forecasting improves the predictive capability of individual concentrations for pediatrics.

What is already known about this subject

Pharmacokinetics of phenobarbital (PB) have been reported large inter-individual difference and treatment with PB required therapeutic drug monitoring.

Population pharmacokinetic models for PB have been studied by several researchers but predictive performance of these models has not been well documented.

What this study adds

Predictive performance of pharmacokinetic models of phenobarbital (PB) was various and required validation for extrapolation to different clinical settings.

Bayesian forecasting could improve the predictability for individual drug concentrations.

Imputation of both size and maturation functions could help to enhance the predictability of pharmacokinetic models for pediatric patients.
Modelling the first wave of the COVID-19 epidemic in the Czech Republic and the role of government interventions
Authors: Májek Ondřej , Ngo Ondřej , Jarkovský Jiří , Komenda Martin , Rážová Jarmila , Dušek Ladislav , Pavlík Tomáš
Published: September 2020

In the Czech Republic, the first COVID-19 cases were confirmed on 1 March 2020; early population interventions were adopted in the following weeks. A simple epidemiological model was developed to help decision-makers understand the course of the epidemic and perform short-term predictions. In this paper, we present the use of the model and estimated changes in the reproduction number (decrease from > 2.00 to < 1.00 over March and April) following adopted interventions.
SARS-CoV-2 Antibody Formation Among Healthcare Workers, September 2, 2020
Authors: Birch Thomas , Barkama Ravit , Georgescu Joanna Tyszkiewicz , Yamada Emma , Olsen Drew , Torres Ed , Sinclair Alison
Published: September 2020

Many frontline healthcare workers throughout the world have been exposed to COVID-19 infection in the workplace and the community. We describe the nature of infection and the durability of antibodies among various types of healthcare workers at an acute care community hospital in northern New Jersey adjacent to New York City, part of the epicenter of the first wave of the US epidemic. Exposure was concentrated among frontline workers and in clusters among support staff. The antibody response correlated with symptoms and job type.

Methods

Employees had Polymerase Chain Reaction testing using a variety of commercially available products based on availability. All screening and testing for diagnosis used the nasopharyngeal swab. Tests for SARS-CoV-2 were obtained at approximately 2, 3 and 4 months using Abbott IgG antibody assay. Results of community sero-prevalence were obtained from hospital and physician surveys as no government entity was monitoring sero-prevalence. Hospital associated employee COVID-19 infections were identified through testing and contact tracing.

Results

5179 patients with COVID-19 syndrome were managed through telehealth over 6 months. 3236 patients were admitted with COVID-19 disease during this time. 2514 out of 3100 employees were tested for antibody to SARS-CoV-2. Overall, 16% of employees tested positive for antibodies at some point. When divided by general job type, 17% of direct caregivers were positive. 16% of indirect contact such as receptionists, housekeeping and food service workers were positive. 16% of nonclinical workers with no patient contact tested positive. The community rate of sero-positivity in one study in Bergen County was 12.2. (1) In the midst of the epidemic, the rate among hospital workers in New York City was 13.7%. (2) The overall population rate in New York City, at the peak of the epidemic, was 21% with some communities as high as 68%. Long Island had 16.7% and Westchester/Rockland 11.7%. (3) Other hospital systems in Northern NJ had up to 25% sero-positive employees. (4)
Estimating the global reduction in transmission and rise in detection capacity of the novel coronavirus SARS-CoV-2 in early 2020
Authors: Belloir Antoine , Blanquart François
Published: September 2020

To better control the SARS-CoV-2 pandemic, it is essential to quantify the impact of control measures and the fraction of infected individuals that are detected. To this end we developed a deterministic transmission model based on the renewal equation and fitted the model to daily case and death data in the first few months of 2020 in 79 countries and states, representing 4.2 billions individuals. Based on a region-specific infection fatality ratio, we inferred the time-varying probability of case detection and the time-varying decline in transmissiblity. As a validation, the predicted total number of infected was close to that found in serosurveys; more importantly, the inferred probability of detection strongly correlated with the number of daily tests per inhabitant, with 50% detection achieved with 0.003 daily tests per inhabitants. Most of the decline in transmission was explained by the reductions in transmissibility (social distancing), which avoided 10 millions deaths in the regions studied over the first four months of 2020. In contrast, symptom-based testing and isolation of positive cases was not an efficient way to control the spread of the disease, as a large part of transmission happens before symptoms and only a small fraction of infected individuals was typically detected. The latter is explained by the limited number of tests available, and the fact that increasing test capacity increases the probability of detection less than proportionally. Together these results suggest that little control can be achieved by symptom-based testing and isolation alone.
Socio-economic disparities and COVID-19 in the USA
Authors: Paul Ayan , Englert Philipp , Varga Melinda
Published: September 2020

COVID-19 is not a universal killer. We study the spread of COVID-19 at the county level for the United States up until the 15th of August, 2020. We show that the prevalence of the disease and the death rate are correlated with the local socio-economic conditions often going beyond local population density distributions, especially in rural areas. We correlate the COVID-19 prevalence and death rate with data from the US Census Bureau and point out how the spreading patterns of the disease show asymmetries in urban and rural areas separately and is preferentially affecting the counties where a large fraction of the population is non-white. Our findings can be used for more targeted policy building and deployment of resources for future occurrence of a pandemic due to SARS-CoV-2. Our methodology, based on interpretable machine learning and game theory, can be extended to study the spread of other diseases.
Plasma P-tau 181, P-tau 217 and Other Blood-Based Alzheimer’s Disease Biomarkers in a Multi-Ethnic, Community Study
Authors: Brickman Adam M. , Manly Jennifer J. , Honig Lawrence S. , Sanchez Danurys , Reyes-Dumeyer Dolly , Lantigua Rafael A. , Lao Patrick J. , Stern Yaakov , Vonsattel Jean Paul , Teich Andrew F. , Airey David Charles , Proctor Nicholas Kyle , Dage Jeffrey L. , Mayeux Richard
Published: September 2020

Introduction

Blood-based Alzheimer’s disease (AD) biomarkers provide opportunities for community studies and across ethnic groups. We investigated blood biomarker concentrations in the Washington Heights, Inwood, Columbia Aging Project (WHICAP), a multi-ethnic community study of aging and dementia.

Methods

We measured plasma Aβ40, Aβ42,T-tau, P-tau181 and P-tau217, and neurofilament light chain (NfL) in 113 autopsied participants, (29% with high AD neuropathological changes) and in 300 clinically evaluated individuals (42% with clinical AD). Receiver operating characteristics were used to evaluate each biomarker. We also investigated biomarkers as predictors of incident clinical AD.

Results

P-tau181, P-tau217 and NfL concentrations were elevated in pathologically and clinically diagnosed AD. Decreased Aβ42/Aβ40 ratio and increased P-tau217 and P-tau181 were associated with subsequent AD diagnosis.

Discussion

Blood-based AD biomarker concentrations are associated with pathological and clinical diagnoses and can predict future development of clinical AD, providing evidence that they can be incorporated into multi-ethnic, community-based studies.
Development, clinical translation, and utility of a COVID-19 antibody test with qualitative and quantitative readouts
Authors: Bortz Robert H. , Florez Catalina , Laudermilch Ethan , Wirchnianski Ariel S. , Lasso Gorka , Malonis Ryan J. , Georgiev George I. , Vergnolle Olivia , Herrera Natalia G. , Morano Nicholas C. , Campbell Sean T. , Orner Erika P. , Mengotto Amanda , Dieterle M. Eugenia , Fels J. Maximilian , Haslwanter Denise , Jangra Rohit K. , Celikgil Alev , Kimmel Duncan , Lee James H. , Mariano Margarette , Nakouzi Antonio , Quiroz Jose , Rivera Johanna , Szymczak Wendy A. , Tong Karen , Barnhill Jason , Forsell Mattias N. E. , Ahlm Clas , Stein Daniel T. , Pirofski Liise-anne , Goldstein D. Yitzchak , Garforth Scott J. , Almo Steven C. , Daily Johanna P. , Prystowsky Michael B. , Faix James D. , Fox Amy S. , Weiss Louis M. , Lai Jonathan R. , Chandran Kartik
Published: September 2020

The COVID-19 global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to place an immense burden on societies and healthcare systems. A key component of COVID-19 control efforts is serologic testing to determine the community prevalence of SARS-CoV-2 exposure and quantify individual immune responses to prior infection or vaccination. Here, we describe a laboratory-developed antibody test that uses readily available research-grade reagents to detect SARS-CoV-2 exposure in patient blood samples with high sensitivity and specificity. We further show that this test affords the estimation of viral spike-specific IgG titers from a single sample measurement, thereby providing a simple and scalable method to measure the strength of an individual’s immune response. The accuracy, adaptability, and cost-effectiveness of this test makes it an excellent option for clinical deployment in the ongoing COVID-19 pandemic.
Mathematical Modeling and a Month Ahead Forecast of the Coronavirus Disease 2019 (COVID-19) Pandemic: An Indian Scenario
Authors: Ganiny Suhail , Nisar Owais
Published: September 2020

India, the second-most populous country in the world, has been lately witnessing a daily surge in the COVID-19 infected cases. India is currently among the worst-hit nations worldwide, due to the COVID-19 pandemic, and ranks just behind Brazil and USA. In order to prevent the further worsening of the situation, predicting the future course of the pandemic is of utmost importance. In this paper, we model the past trajectory (March 01, 2020 - July 25, 2020) and make a month-long (July 26, 2020 - August 24, 2020) forecast of the future evolution of the COVID-19 pandemic in India using an autoregressive integrated moving average (ARIMA) model. According to our forecasting results, India is likely to have 3,800,989 cumulative infected cases, 1,634,142 cumulative active cases, 2,110,697 cumulative recoveries and 56,150 cumulative deaths by August 24, 2020, if the current trend of the pandemic continues to prevail. The implications of these forecasts are that in the upcoming month the infection rate of COVID-19 in India is going to escalate, while as the rate of recovery and the case-fatality rate is likely to reduce. In order to avert these possible scenarios, the administration and health-care personnel need to formulate and implement robust control measures, while the general public needs to be more responsible and strictly adhere to the established and newly formulated guidelines to slow down the spread of the pandemic and prevent it from transforming into a catastrophe.
Relationship between nursing home COVID-19 outbreaks and staff neighborhood characteristics
Authors: Shen Karen
Published: September 2020

The COVID-19 pandemic has taken a significant toll on nursing homes in the US, with upwards of a third of deaths occurring in nursing homes, and more in long-term care facilities. By combining data on facility-level COVID-19 deaths with facility-level data on the neighborhoods where nursing home staff reside for a sample of eighteen states, this paper finds that staff neighborhood characteristics are a large and significant predictor of COVID-19 outbreaks. One standard deviation increases in average staff tract population density, public transportation use, and non-white share were associated with 1.3 (SE .33), 1.4 (SE .35), and 0.9 (SE .24) additional deaths per 100 beds, respectively. These effects are larger than all facility management or quality variables, and larger than the effect of the nursing home’s own neighborhood characteristics. These results suggest that staff communities are likely to be an important source of infection, and that disparities in nursing home outbreaks may be related to differences in the types of neighborhoods nursing home staff live in.
A comparison of ten polygenic score methods for psychiatric disorders applied across multiple cohorts
Authors: Ni Guiyan , Zeng Jian , Revez Joana A , Wang Ying , Zheng Zhili , Ge Tian , Restuadi Restuadi , Kiewa Jacqueline , Nyholt Dale R , Coleman Jonathan R I , Smoller Jordan W ,   Schizophrenia Working Group of the Psychiatric Genomics Consortium,   Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Yang Jian , Visscher Peter M , Wray Naomi R
Published: September 2020

Background

Polygenic scores (PGSs), which assess the genetic risk of individuals for a disease, are calculated as a weighted count of risk alleles identified in genome-wide association studies (GWASs). PGS methods differ in which DNA variants are included and the weights assigned to them; some require an independent tuning sample to help inform these choices. PGSs are evaluated in independent target cohorts with known disease status. Variability between target cohorts is observed in applications to real data sets, which could reflect a number of factors, e.g., phenotype definition or technical factors.

Methods

The Psychiatric Genomics Consortium working groups for schizophrenia (SCZ) and major depressive disorder (MDD) bring together many independently collected case- control cohorts. We used these resources (31K SCZ cases, 41K controls; 248K MDD cases, 563K controls) in repeated application of leave-one-cohort-out meta-analyses, each used to calculate and evaluate PGS in the left-out (target) cohort. Ten PGS methods (the baseline PC+T method and nine methods that model genetic architecture more formally: SBLUP, LDpred2-Inf, LDpred-funct, LDpred2, Lassosum, PRS-CS, PRS-CS-auto, SBayesR, MegaPRS) are compared.

Results

Compared to PC+T, the other nine methods give higher prediction statistics, MegaPRS, LDPred2 and SBayesR significantly so, up to 9.2% variance in liability for SCZ across 30 target cohorts, an increase of 44%. For MDD across 26 target cohorts these statistics were 3.5% and 59%, respectively.

Conclusions

Although the methods that more formally model genetic architecture have similar performance, MegaPRS, LDpred2, and SBayesR rank highest in most comparison and are recommended in applications to psychiatric disorders.
On the reliability of predictions on Covid-19 dynamics: a systematic and critical review of modelling techniques
Authors: Gnanvi Janyce , Salako Valère Kolawolé , Kotanmi Brezesky , Kakaï Romain Glèlè
Published: September 2020

Since the beginning of the new coronavirus 2019-nCoV disease (Covid-19) in December 2019, there has been an exponential number of studies using diverse modelling techniques to assess the dynamics of transmission of the disease, predict its future course and determine the impact of different control measures. In this study, we conducted a global systematic literature review to summarize trends in the modelling techniques used for Covid-19 from January 1st 2020 to June 30th 2020. We further examined the reliability and correctness of predictions by comparing predicted and observed values for cumulative cases and deaths. From an initial 2170 peer-reviewed articles and preprints found with our defined keywords, 148 were fully analyzed. We found that most studies on the modelling of Covid-19 were from Asia (52.70%) and Europe (25%). Most of them used compartmental models (SIR and SEIR) (57%) and statistical models (growth models and time series) (28%) while few used artificial intelligence (5%) and Bayesian approach (3%). For cumulative cases, the ratio predicted/observed values and the ratio of the amplitude of confidence interval (CI) or credibility interval (CrI) of predictions and the central value were on average larger than 1 (4.49 ± 9.98 and 1.10 ± 1.94, respectively) indicating cases of incorrect predictions, large uncertainty on predictions, and large variation across studies. There was no clear difference among models used for these two ratios. However, the ratio predicted/observed values was relatively smaller for SIR models than for SEIR models, indicating that more complex models might not be more accurate for predictions. We further found that values of both ratios decreased with the number of days covered by studies, indicating that the wider the time covered by the data, the higher the correctness and accuracy of predictions. In 21.62% of studies, observed values fall within the CI or CrI of the cumulative cases predicted by studies. Only six of the 148 selected studies (4.05%) predicted the number of deaths. For 33.3% of these predictions, the ratio of predicted to actual number of deaths was close to 1. We also found that the Bayesian model made predictions closer to reality than the compartmental and the statistical models, although these differences are only suggestive due to the small size of the data. Our findings suggest that while predictions made by the different models are useful to understand the pandemic course and guide policy-making, there should be cautious in their usage.
Racial disparities in COVID-19 mortality are driven by unequal infection risks
Authors: Zelner Jon , Trangucci Rob , Naraharisetti Ramya , Cao Alex , Malosh Ryan , Broen Kelly , Masters Nina , Delamater Paul
Published: September 2020

Background

As of August 5, 2020, there were more than 4.8M confirmed and probable cases and 159K deaths attributable to SARS-CoV-2 in the United States, with these numbers undoubtedly reflecting a significant underestimate of the true toll. Geographic, racial-ethnic, age and socioeconomic disparities in exposure and mortality are key features of the first and second wave of the U.S. COVID-19 epidemic.

Methods

We used individual-level COVID-19 incidence and mortality data from the U.S. state of Michigan to estimate age-specific incidence and mortality rates by race/ethnic group. Data were analyzed using hierarchical Bayesian regression models, and model results were validated using posterior predictive checks.

Findings

In crude and age-standardized analyses we found rates of incidence and mortality more than twice as high than Whites for all groups other than Native Americans. Of these, Blacks experienced the greatest burden of confirmed and probable COVID-19 infection (Age-standardized incidence = 1,644/100,000 population) and mortality (age-standardized mortality rate 251/100,000). These rates reflect large disparities, as Blacks experienced age-standardized incidence and mortality rates 5.6 (95% CI = 5.5, 5.7) and 6.9 (6.5, 7.3) times higher than Whites, respectively. We also found that the bulk of the disparity in mortality between Blacks and Whites is driven by dramatically higher rates of COVID-19 infection across all age groups, particularly among older adults, rather than age-specific variation in case-fatality rates.

Interpretation

This work suggests that well-documented racial disparities in COVID-19 mortality in hard-hit settings, such as the U.S. state of Michigan, are driven primarily by variation in household, community and workplace exposure rather than case-fatality rates.

Funding

This work was supported by a COVID-PODS grant from the Michigan Institute for Data Science (MIDAS) at the University of Michigan. The funding source had no role in the preparation of this manuscript.
Exploring the binding of resveratrol to an oncogene promoter DNA sequence d(CCAATTGG)2 through multispectroscopic, nuclear magnetic resonance and molecular dynamics studies
Authors: Kumar Shailendra , Kumar Peeyush , Nair Maya S.
Published: September 2020

We report the interaction of resveratrol with an octamer DNA sequence d(CCAATTGG)2, present in the promoter region of many oncogenes, using a combination of absorption, fluorescence, calorimetric and nuclear magnetic resonance techniques to probe the binding. Resveratrol binds to the duplex sequence with a binding constant 2.20×106 M−1 in absorption studies. A ligandduplex stoichiometry of 2.2:1 was obtained with binding constant varying from 109 to 106M−1 with the concentration of DNA varied in fluorescence titration measurements. Spectral changes indicated external binding of resveratrol to duplex DNA. Circular dichroism data displayed minimal variation suggesting external binding. Melting temperatures of DNA and its 1:1 complex showed a difference of approximately 2.25°C, which supports the external binding. Nuclear magnetic resonance data showed resveratrol binds to the minor groove region near the AT basepair from the nuclear Overhauser effect spectroscopic cross peaks. Distance restrained molecular dynamics was employed in explicit solvent condition to obtain the lowest energy structure. The complex was stable and retained the B-DNA conformation. Findings in this study identify resveratrol as a minor groove binder to the AT region of DNA and pave the way for exploring resveratrol and its analogues as promising anticancer/antibacterial drug.
In vivoandin vitromechanistic characterization of a clinically relevant PolγA mutation
Authors: Silva-Pinheiro Pedro , Pardo-Hernández Carlos , Reyes Aurelio , Tilokani Lisa , Mishra Anup , Cerutti Raffaele , Li Shuaifeng , Ho Dieu Hien , Valenzuela Sebastian , Dogan Anil Sukru , Bradley Peter , Fernandez-Silva Patricio , Trifunovic Aleksandra , Prudent Julien , Minczuk Michal , Bindoff Laurence , Macao Bertil , Zeviani Massimo , Falkenberg Maria , Viscomi Carlo
Published: September 2020

Mutations inPOLG, encoding POLγA, the catalytic subunit of the mitochondrial DNA polymerase, cause a spectrum of disorders characterized by mtDNA instability. However, the molecular pathogenesis ofPOLG-related diseases is poorly understood and efficient treatments are missing. Here, we generated aPOLGA449T/A449Tmouse model, which reproduces the most common human recessive mutation ofPOLG, encoding the A467T change, and dissected the mechanisms underlying pathogenicity. We show that the A449T mutation impairs DNA binding and mtDNA synthesis activities of POLγin vivoandin vitro. Interestingly, the A467T mutation also strongly impairs interactions with POLγB, the homodimeric accessory subunit of holo-POLγ. This allows the free POLγA to become a substrate for LONP1 protease degradation, leading to dramatically reduced levels of POLγA, which in turn exacerbates the molecular phenotypes ofPolgA449T/A449Tmice. Importantly, we validated this mechanism for other mutations affecting the interaction between the two POLγ subunits. We suggest that LONP1 dependent degradation of POLγA can be exploited as a target for the development of future therapies.
The temporal and spectral characteristics of expectations and prediction errors in pain and thermoception
Authors: Strube Andreas , Rose Michael , Fazeli Sepideh , Büchel Christian
Published: September 2020

In the context of a generative model, such as predictive coding, pain and heat perception can be construed as the integration of expectation and input with their difference denoted as a prediction error. In a previous neuroimaging study (Geuter et al., 2017) we observed an important role of the insula in such a model, but could not establish its temporal aspects. Here we employed electroencephalography to investigate neural representations of predictions and prediction errors in heat and pain processing. Our data show that alpha-to-beta activity was associated with stimulus intensity expectation, followed by a negative modulation of gamma band activity by absolute prediction errors. This is in contrast to prediction errors in visual and auditory perception, which are associated with increased gamma band activity, but is in agreement with observations in working memory and word matching, which show gamma band activity for correct, rather than violated predictions.
A COVID-19 antibody curbs SARS-CoV-2 nucleocapsid protein-induced complement hyper-activation
Authors: Kang Sisi , Yang Mei , He Suhua , Wang Yueming , Chen Xiaoxue , Chen Yao-Qing , Hong Zhongsi , Liu Jing , Jiang Guanmin , Chen Qiuyue , Zhou Ziliang , Zhou Zhechong , Huang Zhaoxia , Huang Xi , He Huanhuan , Zheng Weihong , Liao Hua-Xin , Xiao Fei , Shan Hong , Chen Shoudeng
Published: September 2020

Although human antibodies elicited by severe acute respiratory distress syndrome coronavirus-2 (SARS-CoV-2) nucleocapsid (N) protein are profoundly boosted upon infection, little is known about the function of N-directed antibodies. Herein, we isolated and profiled a panel of 32 N protein-specific monoclonal antibodies (mAb) from a quick recovery coronavirus disease-19 (COVID-19) convalescent, who had dominant antibody responses to SARS-CoV-2 N protein rather than to Spike protein. The complex structure of N protein RNA binding domain with the highest binding affinity mAb nCoV396 reveals the epitopes and antigen’s allosteric changes. Functionally, a virus-free complement hyper-activation analysis demonstrates that nCoV396 specifically compromises N protein-induced complement hyper-activation, a risk factor for morbidity and mortality in COVID-19, thus paving the way for functional anti-N mAbs identification.

One Sentence Summary

B cell profiling, structural determination, and protease activity assays identify a functional antibody to N protein.
Induction of AmpC-mediated β-lactam resistance requires a single lytic transglycosylase inAgrobacterium tumefaciens
Authors: Figueroa-Cuilan Wanda M. , Howell Matthew , Richards Christopher , Randich Amelia , Yadav Akhilesh K. , Cava Felipe , Brown Pamela J.B.
Published: September 2020

The remarkable ability ofAgrobacterium tumefaciensto transfer DNA to plant cells has allowed the generation of important transgenic crops. One challenge ofA. tumefaciens-mediated transformation is eliminating the bacteria after plant transformation to prevent detrimental effects to plants and the release of engineered bacteria to the environment. Here we use a reverse genetics approach to identify genes involved in ampicillin resistance with the goal of utilizing these antibiotic-sensitive strains for plant transformations. We show that treatingA. tumefaciensC58 with ampicillin led to increased β-lactamase production, a response dependent on the broad-spectrum β-lactamase AmpC and its transcription factor AmpR. Loss of the putativeampDorthologue,atu2113, led to constitutive production of AmpC-dependent β-lactamase activity and ampicillin resistance. Finally, one cell wall remodeling enzyme, MltB3, was necessary for the AmpC-dependent β-lactamase activity and its loss elicited ampicillin and carbenicillin sensitivity in theA. tumefaciensC58 and GV3101 strains. Furthermore, GV3101ΔmltB3transforms plants with comparable efficiency to wildtype but can be cleared with sub-lethal concentrations of ampicillin. The functional characterization of the genes involved in the inducible ampicillin resistance pathway ofA. tumefaciensconstitutes a major step forward in efforts to reduce the intrinsic antibiotic resistance of this bacterium.

IMPORTANCE

Agrobacterium tumefaciens, a significant biotechnological tool for production of transgenic plant lines, is highly resistant to a wide variety of antibiotics, posing challenges for various applications. One challenge is the efficient elimination ofA. tumefaciensfrom transformed plant tissue without using levels of antibiotics that are toxic to the plants. Here, we present the functional characterization of genes involved in β-lactam resistance inA. tumefaciens.Knowledge about proteins that promote or inhibit β-lactam resistance will enable the development of strains to improve the efficiency ofAgrobacterium-mediated plant genetic transformations. Effective removal ofAgrobacteriumfrom transformed plant tissue has the potential to maximize crop yield and food production, improving the outlook for global food security.
No association between circulating levels of testosterone and sex hormone-binding globulin and risk of COVID-19 mortality in UK biobank
Authors: Fan Xikang , Yang Jing , Wang Jiayu , Yin Cheng , Zhu Meng , Ma Hongxia , Jin Guangfu , Hu Zhibin , Shen Hongbing , Hang Dong
Published: September 2020

Background

Sex-disaggregated data suggest that men with coronavirus disease 2019 (COVID-19) are more likely to die than women. Whether circulating testosterone or sex hormone-binding globulin (SHBG) contributes to such sex differences remains unknown.

Objective

To evaluate the associations of circulating total testosterone (TT), free testosterone (FT), and SHBG with COVID-19 mortality.

Design

Prospective analysis.

Setting

UK Biobank.

Participants

We included 1306 COVID-19 patients (678 men and 628 women) who had serum TT and SHBG measurements and were free of cardiovascular disease or cancer at baseline (2006-2010).

Main outcome measures

The death cases of COVID-19 were identified from National Health Service death records updated at 31 July 2020. Unconditional logistic regression was performed to estimate the odds ratio (OR) and 95% confidence intervals (CI) for mortality.

Results

We documented 315 deaths of COVID-19 (194 men and 121 women). After adjusting for potential confounders, we did not find any statistically significant associations for TT (OR per 1-SD increase = 1.03, 95% CI: 0.85-1.25), FT (OR per 1-SD increase = 0.95, 95% CI: 0.77-1.17), or SHBG (OR per 1-SD increase = 1.09, 95% CI: 0.87-1.37) with COVID-19 mortality in men. Similar null results were observed in women (TT: OR per 1-SD increase = 1.10, 95% CI: 0.85-1.42; FT: OR per 1-SD increase = 1.10, 95% CI: 0.82-1.46; SHBG: OR per 1-SD increase = 1.16, 95% CI: 0.89-1.53).

Conclusions

Our findings do not support a significant role of circulating testosterone or SHBG in COVID-19 prognosis.
Early effect of the Covid-19 epidemic on vaccine coverage of major antigens in Guinea: an analysis of the interrupted time series of national immunization coverage
Authors: Dabo Moustapha , Samah Yombounaud , Kande Mouctar , Sompare Djenou , Camara Aly , Dian Bah Mamadou , Solano Sekou , Baldé Idrissa , Fabrice Latou , Sylla Younoussa , Condé Iya saidou , Kuotu Gerard Cristhian , Touré Almamy Amara , Sidiki Magassouba Aboubacar
Published: September 2020

Introduction

Since the declaration of the first case of Covid-19 on March 12, 2020, in Guinea, the number of COVID-19 cases has been increasing day by day despite the state of health emergency and the barrier measures decreed by the Guinean government. This study aimed to assess the early impact of COVID-19 on immunization activities by comparing current trends to trends over the past year when vaccine coverage of major antigens (BCG, OPV, DTC, MMR, IPV, and Td) had improved considerably.

Methods

The study was carried out at the Expanded Vaccination Program (EPI) of the Republic of Guinea from February 2019 to June 2019. It was a comparative retrospective cohort study on the trends in administrative coverage of the different antigens used in the framework of vaccination.

We performed interrupted time series (STI) analysis using the delayed dependent variable model ANCOVA type II Sum Squares with significance for a p-value less than 0.05 to confirm the link between the occurrence of Covid-19 and the collapse of vaccine coverage. These analyzes were performed on global vaccine-preventable disease surveillance data extracted from the District Immunization Data Management Tool (DVD-MT) designed by WHO. Estimates of the target population were obtained from the National Health Information System (SNIS), and surveillance data for Covid-19 patients were obtained from the National Health Security Agency (ANSS).

Results

Overall, the EPI recorded a median vaccination coverage of less than 80% for all the vaccines introduced and the analysis of the interrupted time series shows that the interruption of the vaccination program was significant for all the vaccines. This finding is factual at both the national and district levels. However, there are disparities at this level, even though some districts have yet to report cases of COVID-19 have experienced drop-in vaccination coverage. The comparison of vaccination coverage for DTP3, for example, shows a sharp drop in the prefectures of Yomou, N’Nzérékoré, Macenta, Kankan, Mandiana, Dinguiraye, Mamou, Koubia, Mali, and Conakry, where it varies between 0 and 80% compared to 2019 where it was above 80%.

Conclusion

Our results express the need for a resilient health system that could adapt quickly and effectively to pandemics and which in turn makes it possible to strengthen EPI activities in Guinea during this period of a health crisis, in particular for children.
Impacts of the COVID-19 epidemic on the department of stomatology in a tertiary hospital: a case study in the General Hospital of the Central Theater Command, Wuhan, China
Authors: Dong Qingshan , Kuria Angelica , Weng Yanming , Liu Yu , Cao Yang
Published: September 2020

Objectives

The aim of this study is to depict the impacts of COVID-19 pandemic on the clinical services and academic activities in the department of stomatology of a tertiary hospitals in Wuhan, China.

Methods

We obtained historical data of the Department of Stomatology from the Health Information System of the General Hospital of Central Theater Command, Wuhan, China between January 2018 and June 2020. Line plots were used to illustrate temporal trend of the variables. Mean ± standard deviation and median with interquartile range were used to summarize the variables. The Kruskal-Wallis equality-of-populations rank test was used to compare the difference between groups.

Results

A significant decrease was noted in the monthly average number of patients seeking the outpatient services for the year 2020. The monthly numbers of patients seeking outpatient services were decreased by two thirds from 2018 to 2020. The number of emergency cases also decreased significantly by 64% in 2020. The monthly number of teaching hours decreased from 3.8 ± 1.5 in 2018 and 4.7 ± 1.4 in 2019 to 1.7 ± 1.9 in 2020. The number of interns also decreased more than 70% in 2020.

Conclusions

The impacts of COVID 19 in the stomatology clinic were significant with notable decreases in clinical services and education offered to the stomatology students. We must find solutions to keep as many as needed dental profession stay on thriving and to remain on the frontline of healthcare.