bluuebunny/crossref_metadata_2025 huggingface dataset:
ACE2 Expression is elevated in Airway Epithelial Cells from aged and male donors but reduced in asthma
Authors: Wark Peter AB , Pathinayake Prabuddha S. , Kaiko Gerard , Nichol Kristy , Ali Ayesha , Chen Ling , Sutanto Erika N , Garratt Luke W , Sohal Sukhwinder S. , Lu Wenying , Eapen Mathew S. , Oldmeadow Christopher , Bartlett Nathan , Reid Andrew , Veerati Punnam , C-Y.Hsu Alan , Looi Kevin , Iosifidis Thomas , Stick Stephen M , Hansbro Philip M. , Kicic Anthony
Published: July 2020

Rationale

COVID-19 is complicated by acute lung injury, and death in some individuals. It is caused by SARS-CoV-2 that requires the ACE2 receptor and serine proteases to enter airway epithelial cells (AECs).

Objective

To determine what factors are associated with ACE2 expression particularly in patients with asthma and chronic obstructive pulmonary disease (COPD).

Methods

We obtained upper and lower AECs from 145 people from two independent cohorts, aged 2-89, Newcastle (n=115), and from Perth (n= 30) Australia. The Newcastle cohort was enriched with people with asthma (n=37) and COPD (n=38). Gene expression for ACE2 and other genes potentially associated with SARS-CoV-2 cell entry were assessed by quantitative PCR, protein expression was confirmed with immunohistochemistry on endobronchial biopsies and cultured AECs.

Results

Increased gene expression of ACE2 was associated with older age (p=0.02) and male sex (p=0.03), but not pack-years smoked. When we compared gene expression between adults with asthma, COPD and healthy controls, mean ACE2 expression was lower in asthma (p=0.01). Gene expression of furin, a protease that facilitates viral endocytosis, was also lower in asthma (p=0.02), while ADAM-17, a disintegrin that cleaves ACE2 from the surface was increased (p=0.02). ACE2 protein levels were lower in endobronchial biopsies from asthma patients.

Conclusions

Increased ACE2 expression occurs in older people and males. Asthma patients have reduced expression. Altered ACE2 expression in the lower airway may be an important factor in virus tropism and may in part explain susceptibility factors and why asthma patients are not over-represented in those with COVID-19 complications.

Impact

ACE2 is the primary receptor for SARS-COV-2. We demonstrate that lower airway expression of ACE2 is increased in older adults and males. We also find that lower ACE2 expression in epithelial cells occurs in people with asthma and is associated with reduced Furin expression and increased ADAM-17 expression. This may explain at least in part the relative sparing of people with asthma from severe COVID-19 disease.
Accounting for external factors and early intervention adoption in the design and analysis of stepped-wedge designs: Application to a proposed study design to reduce opioid-related mortality
Authors: Rennert Lior , Heo Moonseong , Litwin Alain H. , De Gruttola Victor
Published: July 2020

Background

Stepped-wedge designs (SWDs) are currently being used to investigate interventions to reduce opioid overdose deaths in communities located in several states. However, these interventions are competing with external factors such as newly initiated public policies limiting opioid prescriptions, media awareness campaigns, and social distancing orders due to the COVID-19 pandemic. Furthermore, control communities may prematurely adopt components of the proposed intervention as they become widely available. These types of events induce confounding of the intervention effect by time. Such confounding is a well-known limitation of SWDs; a common approach to adjusting for it makes use of a mixed effects modeling framework that includes both fixed and random effects for time. However, these models have several shortcomings when multiple confounding factors are present.

Methods

We discuss the limitations of existing methods based on mixed effects models in the context of proposed SWDs to investigate interventions intended to reduce mortality associated with the opioid epidemic, and propose solutions to accommodate deviations from assumptions that underlie these models. We conduct an extensive simulation study of anticipated data from SWD trials targeting the current opioid epidemic in order to examine the performance of these models under different sources of confounding. We specifically examine the impact of factors external to the study and premature adoption of intervention components.

Results

When only external factors are present, our simulation studies show that commonly used mixed effects models can result in unbiased estimates of the intervention effect, but have inflated Type 1 error and result in under coverage of confidence intervals. These models are severely biased when confounding factors differentially impact intervention and control clusters; premature adoption of intervention components is an example of this scenario. In these scenarios, models that incorporate fixed intervention-by-time interaction terms and an unstructured covariance for the intervention-by-cluster-by-time random effects result in unbiased estimates of the intervention effect, reach nominal confidence interval coverage, and preserve Type 1 error, but may reduce power.

Conclusions

The incorporation of fixed and random time effects in mixed effects models require certain assumptions about the impact of confounding by time in SWD. Violations of these assumptions can result in severe bias of the intervention effect estimate, under coverage of confidence intervals, and inflated Type 1 error. Since model choice has considerable impact on study power as well as validity of results, careful consideration needs to be given to choosing an appropriate model that takes into account potential confounding factors.
Non-COVID-19 deaths in the United States during the imposition of sheltering-in-place
Authors: Catalano Ralph , Casey Joan A. , Gemmill Alison , Bruckner Tim A.
Published: July 2020

Public debate over imposed sheltering-in-place in the United States (US) includes the claim that non-COVID-19 deaths increased above those expected from history and from such deaths in Sweden. We test this claim by applying Box-Jenkins transfer function modeling to weekly deaths between December 29, 2013 and May 16, 2020 in the US and Sweden. In the eight weeks of imposed sheltering-in-place in the US – assumed begun in the week of March 22 – an average of 715 fewer non-COVID-19 deaths (95% CI: −1428, −2) occurred per week implying a total of 5720 less than expected from those in Sweden and from history. Results changed little (i.e., 5472 fewer deaths than expected) when we excluded deaths in New York City. Contrary to speculation, non-COVID-19 mortality appeared to decline in the US after shelter-in-place orders.
Persistent heterogeneity not short-term overdispersion determines herd immunity to COVID-19
Authors: Tkachenko Alexei V. , Maslov Sergei , Elbanna Ahmed , Wong George N. , Weiner Zachary J. , Goldenfeld Nigel
Published: July 2020

It has become increasingly clear that the COVID-19 epidemic is characterized by overdispersion whereby the majority of the transmission is driven by a minority of infected individuals. Such a strong departure from the homogeneity assumptions of the traditional well-mixed compartment model is usually hypothesized to be the result of short-term super-spreader events, such as an individual’s extreme rate of virus shedding at the peak of infectivity while attending a large gathering without appropriate mitigation. However, we demonstrate that the spread of epidemics is primarily sensitive to longterm, orpersistent heterogeneityof individual susceptibility or infectivity. We demonstrate how to incorporate this heterogeneity into a wide class of epidemiological models, and derive a non-linear dependence of the effective reproduction numberReon the susceptible population fractionS. Persistent heterogeneity has three important consequences compared to the effects of short-term overdispersion: (1) It results in a major modification of the early epidemic dynamics; (2) It significantly suppresses the herd immunity threshold; (3) It also significantly reduces the final size of the epidemic. We estimate social and biological contributions to persistent heterogeneity using data on real-life face-to-face contact networks and age variation of the incidence rate during the COVID-19 epidemic. In addition, empirical data from the COVID-19 epidemic in New York City (NYC) and Chicago, as well as 50 US states provide a consistent characterization of the level of heterogeneity. Our estimates suggest that the hardest-hit areas, such as NYC, are close to the heterogeneity-modified herd immunity threshold following the first wave of the epidemic. However, this type of immunity is fragile as it wanes over time if the pattern of social interactions changes substantially.

Significance Statement

This study demonstrates how a wide class of epidemiological models can be adapted for applications to heterogeneous populations in the context of the COVID-19 epidemic. It is shown that a persistent heterogeneity, rather than bursty short-term variations in infection transmission is responsible for self-limiting epidemic dynamics. Compact generalizations of the classical results for the herd immunity threshold and the final size of an epidemic are derived. The degree of persistent heterogeneity is estimated from data on real-life face-to-face contact networks, and on age variation of susceptibility to COVID-19. The estimate is further supported by the analysis of the empirical data from the epidemic in NYC and Chicago, as well as in 50 US states. The results suggest that by the end of the first wave of the epidemic, the hardest-hit areas, such as NYC, have been close to the heterogeneity-modified herd immunity, thereby limiting their vulnerability to a potential second wave of the epidemic.
An Interpretable Risk Prediction Model for Healthcare with Pattern Attention
Authors: Kamal Sundreen Asad , Yin Changchang , Qian Buyue , Zhang Ping
Published: July 2020

Background

The availability of massive amount of data enables the possibility of clinical predictive tasks. Deep learning methods have achieved promising performance on the tasks. However, most existing methods suffer from three limitations: (i) There are lots of missing value for real value events, many methods impute the missing value and then train their models based on the imputed values, which may introduce imputation bias. The models’ performance is highly dependent on the imputation accuracy. (ii) Lots of existing studies just take Boolean value medical events (e.g. diagnosis code) as inputs, but ignore real value medical events (e.g., lab tests and vital signs), which are more important for acute disease (e.g., sepsis) and mortality prediction. (iii) Existing interpretable models can illustrate which medical events are conducive to the output results, but are not able to give contributions of patterns among medical events.

Methods

In this study, we propose a novel interpretable Pattern Attention model with Value Embedding (PAVE) to predict the risks of certain diseases. PAVE takes the embedding of various medical events, their values and the corresponding occurring time as inputs, leverage self-attention mechanism to attend to meaningful patterns among medical events for risk prediction tasks. Because only the observed values are embedded into vectors, we don’t need to impute the missing values and thus avoids the imputations bias. Moreover, the self-attention mechanism is helpful for the model interpretability, which means the proposed model can output which patterns cause high risks.

Results

We conduct sepsis onset prediction and mortality prediction experiments on a publicly available dataset MIMIC-III and our proprietary EHR dataset. The experimental results show that PAVE outperforms existing models. Moreover, by analyzing the self-attention weights, our model outputs meaningful medical event patterns related to mortality.

Conclusions

PAVE learns effective medical event representation by incorporating the values and occurring time, which can improve the risk prediction performance. Moreover, the presented self-attention mechanism can not only capture patients’ health state information, but also output the contributions of various medical event patterns, which pave the way for interpretable clinical risk predictions.

Availability

The code for this paper is available at: https://github.com/yinchangchang/PAVE.
Children with COVID-19 like symptoms in Italian Pediatric Surgeries: the dark side of the coin
Authors: Trapani Gianfranco , Fanos Vassilios , Bertino Enrico , Maiocco Giulia , Jamal Osama Al , Fiore Michele , Bembo Vincenzo , Careddu Domenico , Barberio Lando , Zanino Luisella , Verlato Giuseppe
Published: July 2020

Background

Symptoms of SARS-CoV-2 infection in children are nonspecific and shared with other common acute viral illnesses (fever, respiratory or gastrointestinal symptoms, and cutaneous signs), thus making clinical differential diagnosis tricky. In Italy, first line management of pediatric care is handed over to Primary Care Pediatricians (PCPs), who were not allowed to directly perform diagnostic tests during the recent COVID-19 outbreak. Without a confirmatory diagnosis, PCPs could only collect information on “COVID-19 like symptoms” rather than identify typical COVID-19 symptoms.

Aim

To evaluate the prevalence of COVID-19 like symptoms in outpatient children, during Italian lockdown. To provide PCPs a risk score to be used in clinical practice during the differential diagnosis process.

Methods

A survey was submitted to 50 PCPs (assisting 47,500 children) from 7 different Italian regions between the 4th of March and the 23rd of May 2020 (total and partial lockdown period). COVID-19 like symptoms in the assisted children were recorded, as well as presence of confirmed/suspected cases in children’s families, which was taken as proxy of COVID-19. Multivariable logistic regression was accomplished to estimate the risk of having suspected/confirmed cases in families, considering symptoms as potential determinants.

Results

2,300 children (4.8% of overall survey population) fell ill with COVID-19 like symptoms, 3.1% and 1.7% during total and partial lockdown period respectively. The concurrent presence of fatigue, cough, and diarrhea in children, in absence of sore throat/earache and abnormal skin signs, represents the maximum risk level of having a suspected/confirmed case of COVID-19 at home.

Conclusions

The percentage of children presenting COVID-19 like symptoms at home has been remarkable also during the total lockdown period. The present study identified a pattern of symptoms which could help, in a cost-effective perspective, PCPs in daily clinical practice to define priorities in addressing children to the proper diagnostic procedure.
Are Cloth Masks a Substitute to Medical Masks in reducing transmission and contamination? A Systematic Review
Authors: Santos Milena , Torres Darlyane , Cardoso Paula C. , Pandis Nikolaos , Flores-Mir Carlos , Medeiros Rita , Normando David
Published: July 2020

During the COVID-19 pandemic the use of cloth masks has increased dramatically due to the shortage of medical masks. However, the efficiency of this material is controversial. We aimed to investigate the efficiency of cloth masks in reducing transmission and contamination by droplets and aerosols for the general population and healthcare workers. Electronic databases were searched without year or language restrictions. Clinical and laboratorial studies were included. The risk of bias (RoB) was assessed using an adapted quality checklist for laboratory-based studies. ROBINS-I tool and Cochrane RoB 2.0 were used to evaluate non-randomized (n-RCT) and randomized clinical trials (RCT), respectively. The quality of the evidence was assessed through GRADE tool. From the eleven studies selected, eight were laboratory-based studies, one non-randomized and one RCT supported by laboratory data. Between the evaluated fabrics only three presented a filtration efficiency >90%. Hybrid of cotton/chiffon (95%CI 95.2 to 98.8), hybrid of cotton/silk (95%CI 92.2 to 95.8) and cotton quilt (95%CI 94.2 to 97.8). A meta-analysis was not feasible due to a high methodological heterogeneity. The overall quality of evidence ranged from very low to moderate. Despite the lower efficiency compared to medical masks, laboratorial results may underestimate the efficiency of cloth masks in real life. Cloth mask efficiency is higher when made of hybrid fabrics (cotton/chiffon, cotton/silk) and cotton quilt, mainly with multiple layers. In pandemic situations any measure that can contribute to source control at the population level can have a beneficial effect. However, cloth masks are not recommended for healthcare workers.
Modeling the initial phase of SARS-CoV-2 deposition in the respiratory tract mimicked by the 11C radionuclide
Authors: Evangelista Heitor , Amaral Cesar , Porto Luís Cristóvão , Gonçalves Sergio J. , Sodré Eduardo Delfino , Nogueira Juliana , dos Santos Angela M.G. , Cataldo Marcio
Published: July 2020

The knowledge on the deposition and retention of the viral particle of SARS-CoV-2 in the respiratory tract during the very initial intake from the ambient air is of prime importance to understand the infectious process and COVID-19 initial symptoms. To give some light on that, we propose to use a modified version of a widely tested lung deposition model developed by the ICRP, in the context of the ICRP Publication 66, that provides deposition patterns of microparticles in different lung compartments. In the model, we mimicked the “environmental decay” of the virus, determined by controlled experiments related to normal speeches, by the radionuclide 11C that presents comparable decay rates. Our results confirm clinical observations on the high virus retentions observed in the extrathoracic region and the lesser fraction on the alveolar section (in the order of 5), which relevance is a subject to be investigated.
Evaluation of plasma tau and neurofilament light chain biomarkers in a 12-year clinical cohort of human prion diseases
Authors: Thompson Andrew GB , Anastasiadis Prodromos , Druyeh Ronald , Whitworth Ines , Nayak Annapurna , Nihat Akin , Mok Tze How , Rudge Peter , Wadsworth Jonathan DF , Rohrer Jonathan , Schott Jonathan M , Heslegrave Amanda , Zetterberg Henrik , Collinge John , Jackson Graham S , Mead Simon
Published: July 2020

Prion diseases are fatal neurodegenerative conditions with highly accurate CSF and imaging diagnostic markers, but major unmet needs for blood biomarkers. Using ultrasensitive immuno-assays, we measured tau and neurofilament light chain (NfL) protein concentrations in 709 plasma samples taken from 377 individuals with prion disease during a 12-year prospective clinical study, alongside healthy and neurological control groups. This provides an unprecedented opportunity to evaluate their potential as biomarkers. Plasma tau and NfL were increased across all prion disease types. For distinguishing sCJD from control groups including clinically-relevant “CJD mimics”, both show considerable diagnostic value. In sCJD, NfL was substantially elevated in every sample tested, including during early disease with minimal functional impairment and in all follow-up samples. Plasma tau was independently associated with rate of clinical progression in sCJD, while plasma NfL showed independent association with severity of functional impairment. In asymptomatic PRNP mutation carriers, plasma NfL was higher within 2 years of symptom onset than in samples taken earlier. We present biomarker trajectories for 9 individuals healthy at enrolment who developed symptoms during follow-up, showing potential for plasma NfL as a “proximity marker”. We conclude that plasma tau and NfL have potential to fill key unmet needs for biomarkers in prion disease: as an outcome for clinical trials (NfL and tau); for predicting onset in at-risk individuals (NfL); and as an accessible test for earlier identification of patients that may have CJD and require more definitive tests (NfL). Further studies should evaluate their performance directly in these specific roles.
The diagnostic certainty levels of junior clinicians: A retrospective cohort study
Authors: Chen Yang , Nagendran Myura , Kilic Yakup , Cavlan Dominic , Feather Adam , Westwood Mark , Rowland Edward , Gutteridge Charles , Lambiase Pier D
Published: July 2020

Purpose of the Study

To characterise the documentation of working diagnoses and their associated level of certainty by clinicians assessing patients referred to the medical team from the emergency department.

Design

This was a single centre retrospective cohort study of non-consultant grade clinicians at the Royal London Hospital, Barts Health NHS Trust between 01/03/19 to 31/03/19. De-identified electronic health record data was collected to include the type of diagnosis documented (clinical, laboratory result or symptom/sign defined) and the certainty adjective used for single diagnoses. Presence or absence of diagnostic uncertainty was collected for multiple diagnoses.

Results

865 medical assessments were recorded during the study period. 850 were available for further analysis. 420 presented a single diagnosis while 430 presented multiple diagnoses. Of the 420 single diagnoses, 67 (16%) were documented as either a symptom or physical sign, and 16 (4%) were laboratory-result defined diagnoses. No uncertainty was expressed in 309 (74%) of the diagnoses. Of 430 multiple diagnoses, uncertainty was expressed in 346 (80%) compared to 84 (20%) in which no uncertainty was expressed.

Conclusion

The documentation of working diagnoses is highly variable amongst non-consultant grade clinicians assessing patients admitted via the emergency department. In nearly three quarters of assessments with single diagnoses, no element of uncertainty was implied or quantified. More uncertainty was expressed in multiple diagnoses than single diagnoses however documentation style was heterogenous. These data have implications for prospective studies examining the quantification of diagnostic certainty and its association with important process or outcome measures.

What is already known on this subject

-

The factors which influence medical decision-making is almost exclusively assessed by vignettes, simulations or retrospective questionnaires. The certainty or confidence level of a clinician in making a decision can be a source of bias which can lead to patient harm if their confidence is miscalibrated with their accuracy.

-

A recent review assessing real world studies of decision-making found only nine, all of which used a Likert or visual analogue scale

Main messages

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The documentation of working diagnoses is highly variable amongst non-consultant grade clinicians

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In nearly three quarters of assessments with single diagnoses, no element of uncertainty was implied or quantified

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Existing documentation is too heterogeneous to meaningfully analyse in a quantitative manner – increased standardisation will allow leveraging of electronic health record platforms to become better educational and research tools for clinicians and educators.
Non-communicable disease and the risk of infection death: a UK Biobank prospective cohort study
Authors: Drozd Michael , Lillie Patrick J , Pujades-Rodriguez Mar , Straw Sam , Morgan Ann W , Kearney Mark T , Witte Klaus K , Cubbon Richard M
Published: July 2020

Objectives

Non-communicable diseases (NCDs) have recently been highlighted as important risk factors for COVID-19 fatality. We set out to investigate the association between NCDs and the risk of death from any infection in the pre-COVID-19 era.

Design

Prospective population-based study

Setting

UK Biobank

Participants

493,295 participants

Main outcome measures

Infection death prior to December 31st2019.

Results

During 5,277,344 participant-years of follow-up, 1,385 infection deaths occurred, accounting for 5% of all deaths. Competing risks regression revealed that advancing age, male sex, smoking, socio-economic deprivation and all studied NCDs were independently associated with both the risk of infection death and non-infection death; ethnicity was associated with neither. Only smoking, socio-economic deprivation, hypertension, respiratory disease, chronic kidney disease, psychiatric disease and rheumatological disease were associated with greater hazard ratios for infection than non-infection death. Accrual of multimorbidity was also associated with a greater increases in the risk of infection death (HR 9.03 [95% confidence interval 6.61 to 12.34] for 5+ comorbidities versus none; p<0.001), than non-infection death (HR 5.68 [95% confidence interval 5.22 to 6.17] for 5+ comorbidities versus none; p<0.001).

Conclusions

Diverse NCDs are associated with increased risk of infection death, suggesting that recently reported associations with COVID-19 death may be non-specific. Moreover, only a subset of NCDs, together with the accrual of multimorbidity, smoking and socio-economic deprivation, are associated with greater relative risks of infection death than other causes of death. Further research is needed to define why these risk factors are biased toward infection death so that more effective preventative strategies can be targeted to high-risk groups.

What is already known on this topic

Infection contributes to approximately one in five deaths globally and this often occurs in people with non-communicable diseases (NCDs).

Many NCDs have recently been highlighted as risk factors for fatal COVID-19 infection.

What this study adds

Whilst diverse NCDs are associated with greater risk of infection death, only some pose greater hazards of infection than non-infection death.

The association of many NCDs with fatal COVID-19 infection is unlikely to be specific to this pathogen.
Mathematical Modelling the Impact Evaluation of Lockdown on Infection Dynamics of COVID-19 in Italy
Authors: Kadyrov S. , Orynbassar A. , Saydaliyev H.B , Yergesh D.
Published: July 2020

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the cause of the coronavirus disease-2019 (COVID-19), within months of emergence from Wuhan, China, has rapidly spread, exacting a devastating human toll across around the world reaching the pandemic stage at the the beginning of March 2020. Thus, COVID-19’s daily increasing cases and deaths have led to worldwide lockdown, quarantine and some restrictions. Covid-19 epidemic in Italy started as a small wave of 2 infected cases on January 31. It was followed by a bigger wave mainly from local transmissions reported in 6387 cases on March 8. It caused the government to impose a lockdown on 8 March to the whole country as a way to suppress the pandemic. This study aims to evaluate the impact of the lockdown and awareness dynamics on infection in Italy over the period of January 31 to July 17 and how the impact varies across different lockdown scenarios in both periods before and after implementation of the lockdown policy. The findings SEIR reveal that implementation lockdown has minimised the social distancing flattening the curve. The infections associated with COVID-19 decreases with quarantine initially then easing lockdown will not cause further increasing transmission until a certain period which is explained by public high awareness. Completely removing lockdown may lead to sharp transmission second wave. Policy implementation and limitation of the study were evaluated at the end of the paper.
Prevalence of hypertension and controlled hypertension among United States adults: Evidence from NHANES 2017-18 survey
Authors: Rana Juwel , Oldroyd John , Islam Md. Momin , Tarazona-Meza Carla E , Islam Rakibul M.
Published: July 2020

Background

This study aims to compare the prevalence of hypertension (HTN) and controlled hypertension (CHTN) in US adults and determine the absolute difference in the prevalence of HTN and CHTN between the JNC7 and ACC/AHA 2017 guidelines.

Methods

Data for this study were derived from the most recent cycle of the National Health and Nutrition Examination Survey (NHANES) 2017-2018. After excluding participants with missing systolic blood pressure (BP) or diastolic BP and aged <18 years, 4730 participants were included in the final analyses. BP was defined as the average of the first three measurements. The prevalence of HTN and CHTN, including absolute differences of these prevalences, were estimated using both JNC7 and ACC/AHA 2017 guidelines.

Results

The overall weighted prevalence of HTN was 31.7% (95% CI: 28.7, 34.8) based on JNC7, while the corresponding prevalence was 45.6% (95% CI: 43.0, 48.3) when new guideline of ACC/AHA was used. Of the people who had HTN according to the JNC7 and ACC/AHA 2017 guidelines, 48.2% (95% CI: 44.4-52.0) and 21.0% (95% CI: 18.1-24.2) had a controlled blood pressure level, respectively. When blood pressure was assessed using both guidelines, the greatest absolute increase in rates of HTN and CHTN was 17.4% and 30.0% in people aged 40-59 years, respectively.

Conclusion

Given the high burden of disease due to complications arising from untreated HTN, as well as the higher costs of untreated disease, new guidelines have important public health implications to early detection of patients at risk and prevent complications across different populations.
The German Corona Consensus Dataset (GECCO): A standardized dataset for COVID-19 research
Authors: Sass Julian , Bartschke Alexander , Lehne Moritz , Essenwanger Andrea , Rinaldi Eugenia , Rudolph Stefanie , Heitmann Kai U. , Vehreschild Jörg J. , von Kalle Christof , Thun Sylvia
Published: July 2020

Background

The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the “German Corona Consensus Dataset” (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data.

Methods

Based on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats.

Results

A core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined.

Conclusion

GECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.
How much reserve capacity is justifiable for hospital pandemic preparedness? A cost-effectiveness analysis for COVID-19 in Germany
Authors: Gandjour Afschin
Published: July 2020

Introduction

In preparation for a possible second COVID-19 pandemic wave, expanding intensive care unit (ICU) bed capacity is an important consideration. The purpose of this study was to determine the costs and benefits of this strategy in Germany.

Methods

This study compared the provision of additional capacity to no intervention from a societal perspective. A decision model was developed using, e.g., information on age-specific fatality rates, ICU costs and outcomes, and the herd protection threshold. The net monetary benefit (NMB) was calculated based upon the willingness to pay for new medicines for the treatment of cancer, a condition with a similar disease burden in the near term.

Results

The marginal cost-effectiveness ratio (MCER) of supplying one additional ICU bed is €24,815 per life year gained and increases with the number of additional beds. The NMB remains positive for utilization rates as low as 1.5% and, assuming full capacity utilization, for multiples of the currently available bed capacity. Expanding the ICU bed capacity by 10,000 beds is projected to result in societal costs of €41 billion and to reduce mortality of ICU candidates by 20% compared with no intervention (assuming full capacity utilization). In a sensitivity analysis, the variables with the highest impact on the MCER were the mortality rates in the ICU and after discharge.

Conclusions

In Germany, the provision of additional ICU bed capacity appears to be cost-effective over a large increase in the number of beds. Nevertheless, bed utilization is constrained by labor supply and possibly other input factors.
The optimal level of serum vitamin D in apparently healthy Bangladeshi adult volunteer
Authors: Yadav Anil , Selim Shahjada , Haq Tahniyah , Shah Anil Kumar , Morshed Md. Shahed , Ghani Md. Habibul , Faisal Ibrahim , khan Murshed Ahamed , Mustari Marufa , Rajiv Mostafa Hasan , Hasanat M A , Uddin Farid
Published: July 2020

Introduction

Vitamin D level has profound clinical implications but there is dilemma of optimal vitamin D cut off level among Bangladeshi population as well in many parts of the world. This study aimed to determine the optimal level of vitamin D in relation to intact parathyroid hormone (iPTH) and serum calcium in apparently healthy adult volunteer.

Methods

This observational cross-sectional study was carried out in 130 apparently healthy adult participants of BSMMU. All the subjects were taken their demographic profile and investigated for vitamin D level, iPTH, corrected calcium and phosphate. Serum 25(OH)D was measured by high performance liquid chromatography (HPLC) whereas iPTH, corrected serum calcium and serum phosphate were measured by chemiluminescent method.

Results

The mean 25(OH)D level was found to be 16.78(SD8.47) ng/ml and extensively distinct by age distribution and adequacy of sun exposure. There was substantially inverse correlation between serum iPTH and serum 25(OH)D (r = - 0.22, p = 0.01). Serum 25(OH)D levels < 27.5ng/ml were associated with a steep increase in serum iPTH levels. Serum iPTH was stabilized at level 54.5pg/ml by using the quadratic fit with plateau model.

Conclusions

From this study the optimal level of 25(OH)D for apparently healthy adult in Bangladesh is 27.5 ng/ml.
Genotype and defects in microtubule-based motility correlate with clinical severity in KIF1A Associated Neurological Disorder
Authors: Boyle Lia , Rao Lu , Kaur Simranpreet , Fan Xiao , Mebane Caroline , Hamm Laura , Thornton Andrew , Ahrendsen Jared T , Anderson Matthew P , Christodoulou John , Gennerich Arne , Shen Yufeng , Chung Wendy K
Published: July 2020

KIF1A Associated Neurological Disorder (KAND) encompasses a recently identified group of rare neurodegenerative conditions caused by variants in KIF1A, a member of the kinesin-3 family of microtubule (MT) motor proteins. Here we characterize the natural history of KAND in 117 individuals using a combination of caregiver or self-reported medical history, a standardized measure of adaptive behavior, clinical records, and neuropathology. We developed a heuristic severity score using a weighted sum of common symptoms to assess disease severity. Focusing on 100 individuals, we compared the average clinical severity score for each variant with in silico predictions of deleteriousness and location in the protein. We found increased severity is strongly associated with variants occurring in regions involved with ATP and MT-binding: the P-loop, switch I, and switch II. For a subset of identified variants, we generated recombinant mutant proteins which we used to assess transport in vivo by assessing neurite tip accumulation, and to assess MT binding, motor velocity, and processivity using total internal reflection fluorescence microscopy. We find all patient variants result in defects in transport, and describe three classes of protein dysfunction: reduced MT binding, reduced velocity and processivity, and increased non-motile rigor MT binding. The molecular rigor phenotype is consistently associated with the most severe clinical phenotype, while reduced binding is associated with milder clinical phenotypes. Our findings suggest the clinical phenotypic heterogeneity in KAND likely reflects and parallels diverse molecular phenotypes. We propose a new way to describe KAND subtypes to better capture the breadth of disease severity.
Impact Assessment of Full and Partial Stay-at-Home Orders, Face Mask Usage, and Contact Tracing: An Agent-Based Simulation Study of COVID-19 for an Urban Region
Authors: Tatapudi Hanisha , Das Rachita , Das Tapas K.
Published: July 2020

Purpose

Various social intervention strategies to mitigate COVID-19 are examined using a comprehensive agent-based simulation model. A case study is conducted using a large urban region, Miami-Dade County, Florida, USA. Results are intended to serve as a planning guide for public health decision makers.

Methods

The simulation model mimics daily social mixing behavior of the susceptible and infected generating the spread. Data representing demographics of the region, virus epidemiology, and social interventions shapes model behavior. Results include daily values of infected, reported, hospitalized, and dead.

Results

Study results show that stay-at-home order is quite effective in flattening and then reversing the case growth curve subsiding the pandemic with only 5.8% of the population infected. Whereas, following Florida’s current Phase II reopening plan could end the pandemic via herd immunity with 75% people infected. Use of surgical variety face masks reduced infected by 20%. A further reduction of 66% was achieved through contact tracing.

Conclusions

For Miami-Dade County, a strategy comprising mandatory use of face masks and aggressive contact tracing to identify 50% of the asymptomatic and pre-symptomatic, if adopted now, can potentially steer the COVID-19 pandemic to subside within next 3 months with approximately one fifth of the population infected.
High-throughput SARS-CoV-2 and host genome sequencing from single nasopharyngeal swabs
Authors: Gorzynski J. E. , De Jong H. N. , Amar D. , Hughes C. , Ioannidis A. , Bierman R. , Liu D. , Tanigawa Y. , Kistler A. L. , Kamm J. , Kim J. , Cappello L. , Neff N. F. , Rubinacci S. , Delaneau O. , Shoura M. J. , Seo K. , Kirillova A. , Raja A. , Sutton S. , Huang C. , Sahoo M. K. , Mallempati K. C. , Montero-Martin G. , Osoegawa K. , Watson N. , Hammond N. , Joshi R. , Fernández-Viña M. A. , Christle J. W. , Wheeler M.T. , Febbo P. , Farh K. , Schroth G. P. , DeSouza F. , Palacios J. , Salzman J. , Pinsky B. A. , Rivas M. A. , Bustamante C.D. , Ashley E. A. , Parikh V. N.
Published: July 2020

During COVID19 and other viral pandemics, rapid generation of host and pathogen genomic data is critical to tracking infection and informing therapies. There is an urgent need for efficient approaches to this data generation at scale. We have developed a scalable, high throughput approach to generate high fidelity low pass whole genome and HLA sequencing, viral genomes, and representation of human transcriptome from single nasopharyngeal swabs of COVID19 patients.
Combining structured and unstructured data in eMRs to create clinically-defined eMR-derived cohorts
Authors: Tam Charmaine S , Gullick Janice , Saavedra Aldo , Vernon Stephen T , Figtree Gemma A , Chow Clara K , Cretikos Michelle , Morris Richard W , William Maged , Morris Jonathan , Brieger David
Published: July 2020

Background

There have been few studies describing how eMR systems can be systematically queried to identify clinically-defined populations and limited studies utilising free-text in this process. The aim of this study is to provide a generalisable methodology for constructing clinically-defined eMR-derived patient cohorts using structured and unstructured data in eMRs.

Methods

Patients with possible acute coronary syndrome (ACS) were used as an exemplar. Cardiologists defined clinical criteria for patients presenting with possible ACS. These were mapped to data tables within the eMR system creating seven inclusion criteria comprised of structured data fields (orders and investigations, procedures, scanned electrocardiogram (ECG) images, and diagnostic codes) and unstructured clinical documentation. Data were extracted from two local health districts (LHD) in Sydney, Australia. Outcome measures included examination of the relative contribution of individual inclusion criteria to the identification of eligible encounters, comparisons between inclusion criterion and evaluation of consistency of data extracts across years and LHDs.

Results

Among 802,742 encounters in a 5 year dataset (1/1/13 to 30/12/17), the presence of an ECG image (54.8% of encounters) and symptoms and keywords in clinical documentation (41.4-64.0%) were used most often to identify presentations of possible ACS. Orders and investigations (27.3%) and procedures (1.4%), were less often present for identified presentations. Relevant ICD-10/SNOMED codes were present for 3.7% of identified encounters. Similar trends were seen when the two LHDs were examined separately, and across years.

Conclusions

Clinically-defined eMR-derived cohorts combining structured and unstructured data during cohort identification is prerequisite for critical validation work required for secondary use of eMR data.
Haloargentinum marplatensisgen. nov., sp. nov., a novel extremely halophilic bacterium isolated from salted-ripened anchovy (Engraulis anchoita)
Authors: Perez Silvina , Gomila Margarita , Murialdo Silvia Elena , Ameztoy Irene Mabel , Gonzalez-Escalona Narjol , Ramírez Elida Elvia , Yeannes María Isabel
Published: July 2020

A facultative aerobic, Gram-negative, motile, non-endospore forming and extremely halophilic bacterium, strain 11aii⊺, isolated from salted-ripened anchovy, was examined using a polyphasic approach to characterize and clarify its phylogenetic and taxonomic position. Sequences of the 16S rRNA gene revealed close relationships to species of the generaLentibacillusandVirgibacillus(94.2% similarity). The organism grew optimally in the presence of 20-35 % NaCl. The major fatty acids of strain 11aii⊺were C16:0(42.1%) and anteiso-C15:0(31.2%) and also presented iso-C16:0(11.0%), anteiso-C17:0(10.4%) and C18:0(5.2%). Based on data presented here, strain 11aii⊺is considered to represent a novel genus and species, for which the nameHaloargentinum marplatensis gen. nov. sp. nov. is proposed with the strain 11aii⊺as type strain.
Impairing flow-mediated endothelial remodeling reduces extravasation of tumor cells
Authors: Follain Gautier , Osmani Naël , Mercier Luc , Garcia-Leon Maria Jesus , Busnelli Ignacio , Pichot Angélique , Paul Nicodème , Carapito Raphaël , Bahram Siamak , Lefebvre Olivier , Goetz Jacky G.
Published: July 2020

Tumor progression and metastatic dissemination are driven by cell-intrinsic and biomechanical cues that favor the growth of life-threatening secondary tumors. We recently identified prometastatic vascular regions with blood flow profiles that are permissive for the arrest of circulating tumor cells. We have further established that such flow profiles also control endothelial remodeling, which favors extravasation of arrested CTCs. Yet, how shear forces control endothelial remodeling is unknown. In the present work, we aimed at dissecting the cellular and molecular mechanisms driving blood flow-dependent endothelial remodeling. Transcriptomic analysis revealed that blood flow modulated several signaling pathways in endothelial cells. More specifically, we observed that VEGFR signaling was significantly enhanced. Using a combination of in vitro microfluidics and intravital imaging in zebrafish embryos, we now demonstrate that the early flow-driven endothelial response can be prevented with sunitinib, a pan-inhibitor of VEGFR signaling. Embryos treated with sunitinib displayed reduced endothelial remodeling and subsequent metastatic extravasation. These results confirm the importance of endothelial remodeling as a driving force of CTC extravasation and metastatic dissemination. Furthermore, the present work suggests that therapies targeting endothelial remodeling might be a relevant clinical strategy in order to impede metastatic progression.

Highlights

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Flow profiles that are permissive for metastasis stimulate the VEGFR pathway

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Flow-dependent VEGFR signaling favors extravasation of CTCs through endothelial remodeling

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Inhibition of VEGFR signaling suppresses early flow-driven endothelial response
Identifying signaling genes in spatial single cell expression data
Authors: Li Dongshunyi , Ding Jun , Bar-Joseph Ziv
Published: July 2020

Motivation

Recent technological advances enable the profiling of spatial single cell expression data. Such data presents a unique opportunity to study cell-cell interactions and the signaling genes that mediate them. However, most current methods for the analysis of this data focus on unsupervised descriptive modeling, making it hard to identify key signaling genes and quantitatively assess their impact.

Results

We developed aMixture ofExperts forSpatialSignaling genesIdentification (MESSI) method to identify active signaling genes within and between cells. The mixture of experts strategy enables MESSI to subdivide cells into subtypes. MESSI relies on multi-task learning using information from neighboring cells to improve the prediction of response genes within a cell. Applying the methods to three spatial single cell expression datasets, we show that MESSI accurately predicts the levels of response genes, improving upon prior methods and provides useful biological insights about key signaling genes and subtypes of excitatory neuron cells.

Availability

MESSI is available at:https://github.com/doraadong/MESSI

Contact

zivbj@cs.cmu.edu
Essentially leading antibody production: An investigation of amino acids, myeloma and natural V-region signal peptides in producing Pertuzumab and Trastuzumab variants
Authors: Ling Wei-Li , Su Chinh Tran-To , Lua Wai-Heng , Poh Jun-Jie , Ng Yuen-Ling , Wipat Anil , Gan Samuel Ken-En
Published: July 2020

Boosting the production of recombinant therapeutic antibodies is crucial in both academic and industry settings. In this work, we investigated the usage of varying signal peptides by antibody genes and their roles in recombinant transient production. Comparing myeloma and the native signal peptides of both heavy and light chains in 168 antibody permutation variants, we performed a systematic analysis, finding amino acids counts to be involved in antibody production to construct a model for predicting co-transfection transient recombinant antibody production rates using the HEK293 system. The findings also provide insights into the usage of the large repertoire of antibody signal peptides.