bluuebunny/crossref_metadata_2025 huggingface dataset:
The Auto-eFACE: Machine Learning–Enhanced Program Yields Automated Facial Palsy Assessment Tool
Authors: Miller Matthew Q. , Hadlock Tessa A. , Fortier Emily , Guarin Diego L.
Published: November 2020

Background:

Facial palsy assessment is nonstandardized. Clinician-graded scales are limited by subjectivity and observer bias. Computer-aided grading would be desirable to achieve conformity in facial palsy assessment and to compare the effectiveness of treatments. This research compares the clinician-graded eFACE scale to machine learning–derived automated assessments (auto-eFACE).

Methods:

The Massachusetts Eye and Ear Infirmary Standard Facial Palsy Dataset was employed. Clinician-graded eFACE assessment was performed on 160 photographs. A Python script was used to automatically generate auto-eFACE scores on the same photographs. eFACE and auto-eFACE scores were compared for normal, flaccidly paralyzed, and synkinetic faces.

Results:

Auto-eFACE and eFACE scores differentiated normal faces from those with facial palsy. Auto-eFACE produced significantly lower scores than eFACE for normal faces (93.83 ± 4.37 versus 100.00 ± 1.58; p = 0.01). Review of photographs revealed minor facial asymmetries in normal faces that clinicians tend to disregard. Auto-eFACE reported better facial symmetry in patients with flaccid paralysis (59.96 ± 5.80) and severe synkinesis (62.35 ± 9.35) than clinician-graded eFACE (52.20 ± 3.39 and 54.22 ± 5.35, respectively; p = 0.080 and p = 0.080, respectively); this result trended toward significance.

Conclusions:

Auto-eFACE scores can be obtained automatically using a freely available machine learning–based computer software. Automated scores predicted more asymmetry in normal patients, and less asymmetry in patients with flaccid palsy and synkinesis, compared to clinician grading. Auto-eFACE is a quick and easy-to-use assessment tool that holds promise for standardization of facial palsy outcome measures and may eliminate observer bias seen in clinician-graded scales.

CLINICAL QUESTION/LEVEL OF EVIDENCE:

Diagnostic, III.
Organizational Health Literacy: Opportunities for Patient-Centered Care in the Wake of COVID-19
Authors: Sentell Tetine , Foss-Durant Anne , Patil Uday , Taira Deborah , Paasche-Orlow Michael K. , Trinacty Connie Mah
Published: November 2020

Background and Objectives:

The coronavirus disease-2019 (COVID-19) pandemic is transforming the health care sector. As health care organizations move from crisis mobilization to a new landscape of health and social needs, organizational health literacy offers practical building blocks to provide high-quality, efficient, and meaningful care to patients and their families. Organizational health literacy is defined by the Institute of Medicine as “the degree to which an organization implements policies, practices, and systems that make it easier for people to navigate, understand, and use information and services to take care of their health.”

Methods:

This article synthesizes insights from organizational health literacy in the context of current major health care challenges and toward the goal of innovation in patient-centered care. We first provide a brief overview of the origins and outlines of organizational health literacy research and practice. Second, using an established patient-centered innovation framework, we show how the existing work on organizational health literacy can offer a menu of effective, patient-centered innovative options for care delivery systems to improve systems and outcomes. Finally, we consider the high value of management focusing on organizational health literacy efforts, specifically for patients in health care transitions and in the rapid transformation of care into myriad distance modalities.

Results:

This article provides practical guidance for systems and informs decisions around resource allocation and organizational priorities to best meet the needs of patient populations even in the face of financial and workforce disruption.

Conclusions:

Organizational health literacy principles and guidelines provide a road map for promoting patient-centered care even in this time of crisis, change, and transformation. Health system leaders seeking innovative approaches can have access to well-established tool kits, guiding models, and materials toward many organizational health literacy goals across treatment, diagnosis, prevention, education, research, and outreach.
Personality Traits in the International Classification of Diseases 11th Revision (ICD-11)
Authors: Oltmanns Joshua R.
Published: November 2020

Purpose of review

The International Classification of Diseases 11th Revision (ICD-11) officially adopted a dimensional system of personality disorder that was a paradigm shift for the classification of personality disorders. The purpose of this article is to review the growing amount of research on one component of that system – the personality trait domain model. Importantly, several self-report measures have been developed to measure the ICD-11 domains and have been subjected to initial validation through examination of their factor structure, multimethod use, convergent and discriminant validity with other prominent dimensional personality models (such as the Five-Factor Model), and criterion validity for important life outcomes.

Recent findings

Studies indicate the ICD-11 domains align with the Five-Factor Model and prior influential models of dimensional personality traits, as expected, and thus rest on an impressive body of empirical research. They also capture large amounts of variance included in the ICD-10/Diagnostic and Statistical Manual of Mental Disorders, 5th Edition Section II personality disorders.

Together these findings support the construct validity of the ICD-11 trait domains. However, continued validation research is necessary, as well as research on how to implement these domains into clinical practice, and research on the more specific facet-level of the trait domains – although the ICD-11 model is only officially at the domain-level.
Bilateral pedal edema associated with lurasidone: a case report
Authors: Su Chun-Yi , Hsu Wei-Tse , Lin Ching-Hua
Published: November 2020

Lurasidone, an atypical antipsychotic, is currently approved for treatment of schizophrenia and bipolar depression. Little is known about whether lurasidone might also cause pedal edema. A 55-year-old female patient had been diagnosed with bipolar I disorder from the age of 26. She had been prescribed escitalopram and quetiapine 300 mg/day for her persistent depressive mood. Later, she took lurasidone plus escitalopram to treat depressive episode. Consequently, she developed mild bilateral swelling over the lower legs and ankles. After lurasidone was discontinued, the bilateral pedal edema was completely resolved, and no further recurrence of edema occurred. Resolution of the edema after discontinuation of lurasidone indicates that the edema may have been caused by lurasidone. Caution should be needed when prescribing lurasidone for patients, as pedal edema may affect patients’ adherence to the prescription.
Expression levels of the tetratricopeptide repeat protein gene
ttc39b
covary with carotenoid-based skin colour in cichlid fish
Authors: Ahi Ehsan Pashay , Lecaudey Laurène A. , Ziegelbecker Angelika , Steiner Oliver , Goessler Walter , Sefc Kristina M.
Published: November 2020

Carotenoid pigments play a major role in animal body colouration, generating strong interest in the genes involved in the metabolic processes that lead from their dietary uptake to their storage in the integument. Here, we used RNA sequencing (RNA-Seq) to test for differentially expressed genes in a taxonomically replicated design using three pairs of related cichlid fish taxa from the genera
Tropheus
and
Aulonocara
. Within each pair, taxa differed in terms of red and yellow body colouration, and high‐performance liquid chromatography (HPLC) analyses of skin extracts revealed different carotenoid profiles and concentrations across the studied taxa. Five genes were differentially expressed in all three yellow–red skin contrasts (
dhrsx
,
nlrc3
,
tcaf2
,
urah
and
ttc39b
), but only the tetratricopeptide repeat protein-coding gene
ttc39b
, whose gene product is linked to mammalian lipid metabolism, was consistently expressed more highly in the red skin samples. The RNA-Seq results were confirmed by quantitative PCR. We propose
ttc39b
as a compelling candidate gene for variation in animal carotenoid colouration. Since differential expression of
ttc39b
was correlated with the presence/absence of yellow carotenoids in a previous study, we suggest that
ttc39b
is more likely associated with the concentration of total carotenoids than with the metabolic formation of red carotenoids.
Phosphoglycerate kinase: structural aspects and functions, with special emphasis on the enzyme from Kinetoplastea
Authors: Rojas-Pirela Maura , Andrade-Alviárez Diego , Rojas Verónica , Kemmerling Ulrike , Cáceres Ana J. , Michels Paul A. , Concepción Juan Luis , Quiñones Wilfredo
Published: November 2020

Phosphoglycerate kinase (PGK) is a glycolytic enzyme that is well conserved among the three domains of life. PGK is usually a monomeric enzyme of about 45 kDa that catalyses one of the two ATP-producing reactions in the glycolytic pathway, through the conversion of 1,3-bisphosphoglycerate (1,3BPGA) to 3-phosphoglycerate (3PGA). It also participates in gluconeogenesis, catalysing the opposite reaction to produce 1,3BPGA and ADP. Like most other glycolytic enzymes, PGK has also been catalogued as a moonlighting protein, due to its involvement in different functions not associated with energy metabolism, which include pathogenesis, interaction with nucleic acids, tumorigenesis progression, cell death and viral replication. In this review, we have highlighted the overall aspects of this enzyme, such as its structure, reaction kinetics, activity regulation and possible moonlighting functions in different protistan organisms, especially both free-living and parasitic Kinetoplastea. Our analysis of the genomes of different kinetoplastids revealed the presence of open-reading frames (ORFs) for multiple PGK isoforms in several species. Some of these ORFs code for unusually large PGKs. The products appear to contain additional structural domains fused to the PGK domain. A striking aspect is that some of these PGK isoforms are predicted to be catalytically inactive enzymes or ‘dead’ enzymes. The roles of PGKs in kinetoplastid parasites are analysed, and the apparent significance of the PGK gene duplication that gave rise to the different isoforms and their expression inTrypanosoma cruziis discussed.
A review on nonlinear DNA physics
Authors: Chevizovich Dalibor , Michieletto Davide , Mvogo Alain , Zakiryanov Farit , Zdravković Slobodan
Published: November 2020

The study and the investigation of structural and dynamical properties of complex systems have attracted considerable interest among scientists in general and physicists and biologists in particular. The present review paper represents a broad overview of the research performed over the nonlinear dynamics of DNA, devoted to some different aspects of DNA physics and including analytical, quantum and computational tools to understand nonlinear DNA physics. We review in detail the semi-discrete approximation within helicoidal Peyrard–Bishop model and show that localized modulated solitary waves, usually called breathers, can emerge and move along the DNA. Since living processes occur at submolecular level, we then discuss a quantum treatment to address the problem of how charge and energy are transported on DNA and how they may play an important role for the functioning of living cells. While this problem has attracted the attention of researchers for a long time, it is still poorly understood how charge and energy transport can occur at distances comparable to the size of macromolecules. Here, we review a theory based on the mechanism of ‘self-trapping’ of electrons due to their interaction with mechanical (thermal) oscillation of the DNA structure. We also describe recent computational models that have been developed to capture nonlinear mechanics of DNAin vitroandin vivo, possibly under topological constraints. Finally, we provide some conjectures on potential future directions for this field.
Developing and testing an algorithm for automatic segmentation of the fetal face from three-dimensional ultrasound images
Authors: Clark A. E. , Biffi B. , Sivera R. , Dall'Asta A. , Fessey L. , Wong T.-L. , Paramasivam G. , Dunaway D. , Schievano S. , Lees C. C.
Published: November 2020

Fetal craniofacial abnormalities are challenging to detect and diagnose on prenatal ultrasound (US). Image segmentation and computer analysis of three-dimensional US volumes of the fetal face may provide an objective measure to quantify fetal facial features and identify abnormalities. We have developed and tested an atlas-based partially automated facial segmentation algorithm; however, the volumes require additional manual segmentation (MS), which is time and labour intensive and may preclude this method from clinical adoption. These manually refined segmentations can then be used as a reference (atlas) by the partially automated segmentation algorithm to improve algorithmic performance with the aim of eliminating the need for manual refinement and developing a fully automated system. This study assesses the inter- and intra-operator variability of MS and tests an optimized version of our automatic segmentation (AS) algorithm. The manual refinements of 15 fetal faces performed by three operators and repeated by one operator were assessed by Dice score, average symmetrical surface distance and volume difference. The performance of the partially automatic algorithm with difference size atlases was evaluated by Dice score and computational time. Assessment of the manual refinements showed low inter- and intra-operator variability demonstrating its suitability for optimizing the AS algorithm. The algorithm showed improved performance following an increase in the atlas size in turn reducing the need for manual refinement.
Assessing the strength of case growth trends in the coronavirus pandemic
Authors: Kriston Levente
Published: November 2020

The ability to distinguish between erratic and systematic patterns of change in case count data is crucial for assessing and projecting the course of disease outbreaks. Here, it is shown that measuring the strength of trends can provide information that is not readily captured by commonly used descriptive indicators. In combination with the 7-day moving average, Bandt and Pompe's permutation entropy and Wilder's relative strength index were found to support the timely detection of coronavirus epidemic trends and transitions in data from various countries. The results demonstrate that measuring the strength of epidemic growth trends in addition to their magnitude can significantly enhance disease surveillance.
Mixed-precision iterative refinement using tensor cores on GPUs to accelerate solution of linear systems
Authors: Haidar Azzam , Bayraktar Harun , Tomov Stanimire , Dongarra Jack , Higham Nicholas J.
Published: November 2020

Double-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half-precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced-precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations
Ax
 = 
b
without sacrificing numerical stability. The techniques we employ include multiprecision LU factorization, the preconditioned generalized minimal residual algorithm (GMRES), and scaling and auto-adaptive rounding to avoid overflow. We also show how to efficiently handle systems with multiple right-hand sides. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a

4
×
−
5
×

performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability.
Bayesian differential programming for robust systems identification under uncertainty
Authors: Yang Yibo , Aziz Bhouri Mohamed , Perdikaris Paris
Published: November 2020

This paper presents a machine learning framework for Bayesian systems identification from noisy, sparse and irregular observations of nonlinear dynamical systems. The proposed method takes advantage of recent developments in differentiable programming to propagate gradient information through ordinary differential equation solvers and perform Bayesian inference with respect to unknown model parameters using Hamiltonian Monte Carlo sampling. This allows an efficient inference of the posterior distributions over plausible models with quantified uncertainty, while the use of sparsity-promoting priors enables the discovery of interpretable and parsimonious representations for the underlying latent dynamics. A series of numerical studies is presented to demonstrate the effectiveness of the proposed methods, including nonlinear oscillators, predator–prey systems and examples from systems biology. Taken together, our findings put forth a flexible and robust workflow for data-driven model discovery under uncertainty. All codes and data accompanying this article are available athttps://bit.ly/34FOJMj.
On the accuracy and applicability of a new implicit Taylor method and the high-order spectral method on steady nonlinear waves
Authors: Klahn Mathias , Madsen Per A. , Fuhrman David R.
Published: November 2020

This paper presents an investigation and discussion of the accuracy and applicability of an implicit Taylor (IT) method versus the classical higher-order spectral (HOS) method when used to simulate two-dimensional regular waves. This comparison is relevant, because the HOS method is in fact an explicit perturbation solution of the IT formulation. First, we consider the Dirichlet–Neumann problem of determining the vertical velocity at the free surface given the surface elevation and the surface potential. For this problem, we conclude that the IT method is significantly more accurate than the HOS method when using the same truncation order,
M
, and spatial resolution,
N
, and is capable of dealing with steeper waves than the HOS method. Second, we focus on the problem of integrating the two methods in time. In this connection, it turns out that the IT method is less robust than the HOS method for similar truncation orders. We conclude that the IT method should be restricted to
M
 = 4, while the HOS method can be used with
M
 ≤ 8. We systematically compare these two options and finally establish the best achievable accuracy of the two methods as a function of the wave steepness and the water depth.
Analytic and numerical solutions to the seismic wave equation in continuous media
Authors: Walters S. J. , Forbes L. K. , Reading A. M.
Published: November 2020

This paper presents two approaches to mathematical modelling of a synthetic seismic pulse, and a comparison between them. First, a new analytical model is developed in two-dimensional Cartesian coordinates. Combined with an initial condition of sufficient symmetry, this provides a valuable check for the validity of the numerical method that follows. A particular initial condition is found which allows for a new closed-form solution. A numerical scheme is then presented which combines a spectral (Fourier) representation for displacement components and wave-speed parameters, a fourth-order Runge–Kutta integration method, and an absorbing boundary layer. The resulting large system of differential equations is solved in parallel on suitable enhanced performance desktop hardware in a new software implementation. This provides an alternative approach to forward modelling of waves within isotropic media which is efficient, and tailored to rapid and flexible developments in modelling seismic structure, for example, shallow depth environmental applications. Visual comparisons of the analytic solution and the numerical scheme are presented.
Oscillatory dynamics in the dilemma of social distancing
Authors: Glaubitz Alina , Fu Feng
Published: November 2020

Social distancing as one of the main non-pharmaceutical interventions can help slow down the spread of diseases, like in the COVID-19 pandemic. Effective social distancing, unless enforced as drastic lockdowns and mandatory cordon sanitaire, requires consistent strict collective adherence. However, it remains unknown what the determinants for the resultant compliance of social distancing and their impact on disease mitigation are. Here, we incorporate into the epidemiological process with an evolutionary game theory model that governs the evolution of social distancing behaviour. In our model, we assume an individual acts in their best interest and their decisions are driven by adaptive social learning of the real-time risk of infection in comparison with the cost of social distancing. We find interesting oscillatory dynamics of social distancing accompanied with waves of infection. Moreover, the oscillatory dynamics are dampened with a non-trivial dependence on model parameters governing decision-makings and gradually cease when the cumulative infections exceed the herd immunity. Compared to the scenario without social distancing, we quantify the degree to which social distancing mitigates the epidemic and its dependence on individuals’ responsiveness and rationality in their behaviour changes. Our work offers new insights into leveraging human behaviour in support of pandemic response.
Findings and insights from the genetic investigation of age of first reported occurrence for complex disorders in the UK Biobank and FinnGen
Authors: Feng Yen-Chen A. , Ge Tian , Cordioli Mattia ,   FinnGen, Ganna Andrea , Smoller Jordan W. , Neale Benjamin M.
Published: November 2020

Age of onset contains information on the timing of events relevant to disease etiology, but there has not been a systematic investigation of its heritability from GWAS data. Here, we characterize the genetic architecture of age of first occurrence and its genomic relationship with disease susceptibility for a wide range of complex disorders in the UK Biobank. For diseases with a sufficient sample size, we discover that age of first occurrence has non-trivial genetic contributions, some with specific genetic risk factors not associated with susceptibility to the disease. Through genetic correlation analysis, we show that an earlier health-event occurrence is correlated with a higher polygenic risk of disease susceptibility. An independent genetic investigation of the FinnGen cohort replicates the pattern of heritability and genetic correlation estimates. We then demonstrate that incorporating disease onset age with susceptibility may improve genetic risk prediction and stratification.
Timing the SARS-CoV-2 Index Case in Hubei Province
Authors: Pekar Jonathan , Worobey Michael , Moshiri Niema , Scheffler Konrad , Wertheim Joel O.
Published: November 2020

Understanding when SARS-CoV-2 emerged is critical to evaluating our current approach to monitoring novel zoonotic pathogens and understanding the failure of early containment and mitigation efforts for COVID-19. We employed a coalescent framework to combine retrospective molecular clock inference with forward epidemiological simulations to determine how long SARS-CoV-2 could have circulated prior to the time of the most recent common ancestor. Our results define the period between mid-October and mid-November 2019 as the plausible interval when the first case of SARS-CoV-2 emerged in Hubei province. By characterizing the likely dynamics of the virus before it was discovered, we show that over two-thirds of SARS-CoV-2-like zoonotic events would be self-limited, dying out without igniting a pandemic. Our findings highlight the shortcomings of zoonosis surveillance approaches for detecting highly contagious pathogens with moderate mortality rates.
Comparing COVID-19 vaccine allocation strategies in India: a mathematical modelling study
Authors: Foy Brody H , Wahl Brian , Mehta Kayur , Shet Anita , Menon Gautam I , Britto Carl
Published: November 2020

Background

The development and widespread use of an effective SARS-CoV-2 vaccine could help prevent substantial morbidity and mortality associated with COVID-19 infection and mitigate many of the secondary effects associated with non-pharmaceutical interventions. The limited availability of an effective and licensed vaccine will task policymakers around the world, including in India, with decisions regarding optimal vaccine allocation strategies. Using mathematical modelling we aimed to assess the impact of different age-specific COVID-19 vaccine allocation strategies within India on SARS CoV-2-related mortality and infection.

Methods

We used an age-structured, expanded SEIR model with social contact matrices to assess different age-specific vaccine allocation strategies in India. We used state-specific age structures and disease transmission coefficients estimated from confirmed Indian incident cases of COVID-19 between 28 January and 31 August 2020. Simulations were used to investigate the relative reduction in mortality and morbidity of vaccinate allocation strategies based on prioritizing different age groups, and the interactions of these strategies with several concurrent non-pharmacologic interventions (i.e., social distancing, mandated masks, lockdowns). Given the uncertainty associated with current COVID-19 vaccine development, we also varied several vaccine characteristics (i.e., efficacy, type of immunity conferred, and rollout speed) in the modelling simulations.

Results

In nearly all scenarios, prioritizing COVID-19 vaccine allocation for older populations (i.e., >60yrs old) led to the greatest relative reduction in deaths, regardless of vaccine efficacy, control measures, rollout speed, or immunity dynamics. However, preferential vaccination of this target group often produced higher total symptomatic infection counts and more pronounced estimates of peak incidence than strategies which targeted younger adults (i.e., 20-40yrs or 40-60yrs) or the general population irrespective of age. Vaccine efficacy, immunity type, target coverage and rollout speed all significantly influenced overall strategy effectiveness, with the time taken to reach target coverage significantly affecting the relative mortality benefit comparative to no vaccination.

Conclusions

Our findings support global recommendations to prioritize COVID-19 vaccine allocation for older age groups. Including younger adults in the prioritisation group can reduce overall infection rates, although this benefit was countered by the larger mortality rates in older populations. Ultimately an optimal vaccine allocation strategy will depend on vaccine characteristics, strength of concurrent non-pharmaceutical interventions, and region-specific goals such as reducing mortality, morbidity, or peak incidence.
Metabolic correlates of late midlife cognitive function: findings from the 1946 British Birth Cohort
Authors: Green Rebecca , Lord Jodie , Xu Jin , Maddock Jane , Kim Min , Dobson Richard , Legido-Quigley Cristina , Wong Andrew , Richards Marcus , Proitsi Petroula
Published: November 2020

Investigating associations between metabolites and late midlife cognitive function could reveal potential markers and mechanistic insights relevant to early dementia. Here, we aimed to systematically explore the metabolic underpinnings of cognitive outcomes across the 7th decade of life, while untangling influencing life course factors. Using levels of 1019 metabolites detected by liquid chromatography-mass spectrometry and quantified at age 60-64, we evaluated relationships between metabolites and cognitive outcomes in the British 1946 Birth Cohort (N=1740). We conducted pathway and network analyses to allow for greater insight into underlying mechanisms, and sequentially adjusted for life course factors including social factors, childhood cognition and lifestyle influences. After adjusting for multiple tests, 155 metabolites, 10 pathways and 5 network modules demonstrated relationships with cognitive outcomes. Integrating these, we identified thirty-five “hub” metabolites that were influential in their module and associated with our outcomes. Notably, we report relationships between a module comprised of acylcarnitines and processing speed that were independent of life course factors, revealing palmitoylcarnitine as a hub (final model: ß =-0.10, 95%CI =-0.15--0.052, p=5.99×10−5). Two modules additionally demonstrated associations with several cognitive outcomes that were partly explained by life course factors: one enriched in nucleosides and amino acids, and another in vitamin A and C metabolites. Our other findings, including a module enriched in sphingolipid pathways, were entirely explained by life course factors - particularly social factors and childhood cognition. These results highlight potential metabolic mechanisms underlying cognitive function in late midlife, suggesting marker candidates and life course relationships for further study.
The Contrasting Role of Nasopharyngeal Angiotensin Converting Enzyme 2 (ACE2) Expression in SARS-CoV-2 Infection: A Cross-Sectional Study of People Tested for COVID-19 in British Columbia
Authors: Nikiforuk Aidan M. , Kuchinski Kevin S. , Twa David D.W. , Lukac Christine D. , Sbihi Hind , Basham C. Andrew , Steidl Christian , Prystajecky Natalie A. , Jassem Agatha N. , Krajden Mel , Patrick David M , Sekirov Inna
Published: November 2020

Background

Angiotensin converting enzyme 2 (ACE2) serves as the host receptor for SARS-CoV-2, with a critical role in viral infection. We aim to understand population level variation of nasopharyngealACE2expression in people tested for COVID-19 and the relationship betweenACE2expression and SARS-CoV-2 viral RNA load, while adjusting for expression of the complementary protease, Transmembrane serine protease 2 (TMPRSS2), solubleACE2, age, and biological sex.

Methods

A cross-sectional study of n=424 participants aged 1-104 years referred for COVID-19 testing was performed in British Columbia, Canada. Participants who tested negative or positive for COVID-19 were matched by age and biological sex. Viral and host gene expression was measured by quantitative reverse-transcriptase polymerase chain reaction. Bivariate analysis and multiple linear regression were performed to understand the role of nasopharyngealACE2expression in SARS-CoV-2 infection. TheACE2gene was targeted to measure expression of transmembrane and soluble transcripts.

Findings

Analysis shows no association between age and nasopharyngealACE2expression in those who tested negative for COVID-19 (P=0·092). Mean expression of transmembrane (P=1·2e-4), solubleACE2(P<0·0001) andTMPRSS2(P<0·0001) differed between COVID-19-negative and -positive groups. In bivariate analysis of COVID-19-positive participants, expression of transmembraneACE2positively correlated with SARS-CoV-2 RNA viral load (P<0·0001), expression of solubleACE2negatively correlated (P<0·0001), and no correlation was found withTMPRSS2 (P=0·694). Multivariable analysis showed that the greatest viral RNA loads were observed in participants with high transmembraneACE2expression (B=0·886, 95%CI:[0·596 to 1·18]), while expression of solubleACE2may protect against high viral RNA load in the upper respiratory tract (B= −0·0990, 95%CI:[−0·176 to −0·0224]).

Interpretation

NasopharyngealACE2expression plays a dual, contrasting role in SARS-CoV-2 infection of the upper respiratory tract. TransmembraneACE2positively correlates, while solubleACE2negatively correlates with viral RNA load after adjusting for age, biological sex and expression of TMPRSS2.

Funding

This project (COV-55) was funded by Genome British Columbia as part of their COVID-19 rapid response initiative.
Optimal symptom combinations to aid COVID-19 case identification: analysis from a community-based, prospective, observational cohort
Authors: Antonelli M , Capdevila J , Chaudhari A , Granerod J , Canas LS , Graham MS , Klaser K , Modat M , Molteni E , Murray B , Sudre CH , Davies R , May A , Nguyen LH , Drew DA , Joshi A , Chan AT , Cramer JP , Spector T , Wolf J , Ourselin S , Steves CJ , Loeliger AE
Published: November 2020

Objectives

Diagnostic work-up following any COVID-19 associated symptom will lead to extensive testing, potentially overwhelming laboratory capacity whilst primarily yielding negative results. We aimed to identify optimal symptom combinations to capture most cases using fewer tests with implications for COVID-19 vaccine developers across different resource settings and public health.

Methods

UK and US users of the COVID-19 Symptom Study app who reported new-onset symptoms and an RT-PCR test within seven days of symptom onset were included. Sensitivity, specificity, and number of RT-PCR tests needed to identify one case (test per case [TPC]) were calculated for different symptom combinations. A multi-objective evolutionary algorithm was applied to generate combinations with optimal trade-offs between sensitivity and specificity.

Findings

UK and US cohorts included 122,305 (1,202 positives) and 3,162 (79 positive) individuals. Within three days of symptom onset, the COVID-19 specific symptom combination (cough, dyspnoea, fever, anosmia/ageusia) identified 69% of cases requiring 47 TPC. The combination with highest sensitivity (fatigue, anosmia/ageusia, cough, diarrhoea, headache, sore throat) identified 96% cases requiring 96 TPC.

Interpretation

We confirmed the significance of COVID-19 specific symptoms for triggering RT-PCR and identified additional symptom combinations with optimal trade-offs between sensitivity and specificity that maximize case capture given different resource settings.

Highlights

Widely recommended symptoms identified only ∼70% COVID-19 cases

Additional symptoms increased case finding to > 90% but tests needed doubled

Optimal symptom combinations maximise case capture considering available resources

Implications for COVID-19 vaccine efficacy trials and wider public health
Differential homeostatic regulation of glycinergic and GABAergic nanocolumns at mixed inhibitory synapses
Authors: Yang Xiaojuan , Le Corronc Hervé , Legendre Pascal , Triller Antoine , Specht Christian G
Published: November 2020

Super-resolution imaging of synapses has revealed that key synaptic proteins are dynamically organized within sub-synaptic domains (SSDs). At mixed inhibitory synapses in spinal cord neurons, both GlyRs and GABAARs reside at the same post-synaptic density (PSD). To examine how the different inhibitory receptors are organized and regulated, we carried out dual-color direct stochastic optical reconstruction microscopy (dSTORM). We found that endogenous GlyRs and GABAARs as well as their common scaffold protein gephyrin form SSDs that align with pre-synaptic RIM1/2, thus forming trans-synaptic nanocolumns. Strikingly, GlyRs and GABAARs occupy different sub-synaptic spaces, exhibiting only a partial overlap at mixed inhibitory synapses. When network activity was increased by pharmacological treatment using the K+channel blocker 4-aminopyridine (4-AP), the GABAAR copy numbers of as well as the number of GABAAR SSDs were reduced, while GlyRs remained largely unchanged. This differential regulation is likely the result of changes in gephyrin phosphorylation that preferentially occurred outside of the SSDs. The total gephyrin content was not altered by 4-AP application. The activity-dependent regulation of GABAARs versus GlyRs suggests that different signaling pathways control their respective sub-synaptic organization. Whereas gephyrin serves as a scaffold protein that upholds GlyR numbers at SSDs, it may act as a switch regulating GABAARs via its phosphorylation state. Taken together, our data reinforce the notion that the precise sub-synaptic organization of GlyRs, GABAARs and gephyrin has functional consequences for the homeostatic regulation of mixed inhibitory synapses.

Highlights

Alignment of sub-synaptic domains (SSDs) in trans-synaptic nanocolumns at inhibitory synapses Differential spatial organization of SSDs formed by GlyRs and GABAARs at mixed inhibitory synapses Activity-dependent regulation of GABAARs but not GlyRs at mixed inhibitory synapses Gephyrin phosphorylation is compartmentalized in SSDs within the synaptic scaffold
Rapid Detection of VanA/B-Producing Vancomycin-Resistant enterococci using Lateral Flow Immunoassay from colonies and blood culture
Authors: Oueslati Saoussen , Volland Hervé , Cattoir Vincent , Bernabeu Sandrine , Girlich Delphine , Dulac Duncan , Plaisance Marc , Boutigny Laure , Dortet Laurent , Simon Stéphanie , Naas Thierry
Published: November 2020

Vancomycin-resistant enterococci (VRE) have become one of the most important nosocomial pathogens worldwide associated with increased treatment costs, prolonged hospital stay, and high mortality. Rapid detection is crucial to reduce their spread and prevent infections and outbreaks. The lateral flow immunoassay NG-Test VanB (NG Biotech) was evaluated for the rapid detection of VanB-producing vancomycin-resistant enterococci (VanB-VRE) using 104 well-characterized enterococcal isolates. The sensitivity and specificity were both 100%, when bacterial cells were grown in the presence of vancomycin used as VanB inducer. The NG-Test VanB is an efficient, rapid, and easy to implement assay in clinical microbiology laboratories for the confirmation of VanB-VREs either from colonies or from positive blood cultures. Together with the NG-Test VanA, they could complete/replace the already existing panel of tests available for confirmation of acquired vancomycin resistance in enterococci, especially from selective media (rectal screenings) or from antibiograms (infections), with a sensitivity and specificity of both of 100%. The rapid detection in less than 15 minutes will result in more efficient management of carriers and infected patients.
Estimating the effectiveness of routine asymptomatic PCR testing at different frequencies for the detection of SARS-CoV-2 infections
Authors: Hellewell Joel , Russell Timothy W. ,   The SAFER Investigators and Field Study Team,   The Crick COVID-19 Consortium,   CMMID COVID-19 working group, Beale Rupert , Kelly Gavin , Houlihan Catherine , Nastouli Eleni , Kucharski Adam J.
Published: November 2020

Background

Routine asymptomatic testing using RT-PCR of people who interact with vulnerable populations, such as medical staff in hospitals or care workers in care homes, has been employed to help prevent outbreaks among vulnerable populations. Although the peak sensitivity of RT-PCR can be high, the probability of detecting an infection will vary throughout the course of an infection. The effectiveness of routine asymptomatic testing will therefore depend on testing frequency and how PCR detection varies over time.

Methods

We fitted a Bayesian statistical model to a dataset of twice weekly PCR tests of UK healthcare workers performed by self-administered nasopharyngeal swab, regardless of symptoms. We jointly estimated times of infection and the probability of a positive PCR test over time following infection, we then compared asymptomatic testing strategies by calculating the probability that a symptomatic infection is detected before symptom onset and the probability that an asymptomatic infection is detected within 7 days of infection.

Findings

We estimated that the probability that the PCR test detected infection peaked at 77% (54 - 88%) 4 days after infection, decreasing to 50% (38 - 65%) by 10 days after infection. Our results suggest a substantially higher probability of detecting infections 1–3 days after infection than previously published estimates. We estimated that testing every other day would detect 57% (33-76%) of symptomatic cases prior to onset and 94% (75-99%) of asymptomatic cases within 7 days if test results were returned within a day.

Interpretation

Our results suggest that routine asymptomatic testing can enable detection of a high proportion of infected individuals early in their infection, provided that the testing is frequent and the time from testing to notification of results is sufficiently fast.

Funding

Wellcome Trust, National Institute for Health Research (NIHR) Health Protection Research Unit, Medical Research Council (UKRI)
Asymptomatic SARS-CoV-2 testing: predictors of effectiveness; risk of increasing transmission
Authors: Skittrall Jordan P.
Published: November 2020

Testing asymptomatic people for SARS-CoV-2 aims to reduce COVID-19 transmission. Screening programs’ effectiveness depends upon testing strategy, sample handling logistics, test sensitivity, and individual behavior, in addition to dynamics of viral transmission. We investigated the interaction between these factors to determine how to optimize reduction of transmission. We show that under idealistic assumptions 70% of transmission may be averted, but under realistic assumptions only 7% may be averted. We show that programs that overwhelm laboratory capacity or reduce isolation of those with minor symptoms have increased transmission compared with those that do not: programs need to be designed to avoid these issues. Our model allows optimal selection of whom to test, quantifies the balance between accuracy and timeliness, and quantifies potential impacts of behavioral interventions.

One Sentence Summary

Programs that overwhelm laboratory capacity or reduce isolation of those with minor symptoms have impaired effectiveness.
Seroprevalence of SARS-CoV-2 infection in the craft and manual worker population of Qatar
Authors: Al-Thani Mohamed H. , Farag Elmoubasher , Bertollini Roberto , Al Romaihi Hamad Eid , Abdeen Sami , Abdelkarim Ashraf , Daraan Faisal , Ismail Ahmed , Mostafa Nahid , Sahl Mohamed , Suliman Jinan , Tayar Elias , Kasem Hasan Ali , Agsalog Meynard J. A. , Akkarathodiyil Bassam K. , Alkhalaf Ayat A. , Alakshar Mohamed Morhaf M. H. , Al-Qahtani Abdulsalam Ali A. H. , Al-Shedifat Monther H. A. , Ansari Anas , Ataalla Ahmad Ali , Chougule Sandeep , Gopinathan Abhilash K. K. V. , Poolakundan Feroz J. , Ranbhise Sanjay U. , Saefan Saed M. A. , Thaivalappil Mohamed M. , Thoyalil Abubacker S. , Umar Inayath M. , Kanaani Zaina Al , Khal Abdullatif Al , Kuwari Einas Al , Butt Adeel A. , Coyle Peter , Jeremijenko Andrew , Kaleeckal Anvar Hassan , Latif Ali Nizar , Shaik Riyazuddin Mohammad , Rahim Hanan F. Abdul , Yassine Hadi M. , Nasrallah Gheyath K. , Kuwari Mohamed G. Al , Chaghoury Odette , Chemaitelly Hiam , Abu-Raddad Laith J. ,   the Craft and Manual Workers Seroprevalence Study Group
Published: November 2020

Background

Qatar experienced a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual worker (CMW) population who comprise 60% of the total population. This study aimed to assess the proportions of ever and/or current infection in this population.

Methods

A cross-sectional population-based survey was conducted during July 26-September 09, 2020 to assess both anti-SARS-CoV-2 positivity through serological testing and polymerase chain reaction (PCR) positivity through PCR testing. Associations with antibody and PCR positivity were identified through regression analyses.

Results

Study included 2,641 participants, 69.3% of whom were <40 years of age. Anti-SARS-CoV-2 positivity was estimated at 55.3% (95% CI: 53.3-57.3%) and was significantly associated with nationality, geographic location, educational attainment, occupation, presence of symptoms in the two weeks preceding the survey, and previous infection diagnosis. PCR positivity was assessed at 11.3% (95% CI: 9.9-12.8%) and was significantly associated with geographic location, contact with an infected person, and reporting two or more symptoms. Infection positivity (antibody and/or PCR positive) was assessed at 60.6% (95% CI: 9.9-12.8%). The proportion of antibody-positive CMWs that had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI: 7.9-11.0%). Only seven infections were ever severe and one was ever critical—an infection severity rate of 0.5% (95% CI: 0.2-1.0%).

Conclusions

Six in every 10 CMWs have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low with only one in every 200 infections progressing to be severe or critical. Only one in every 10 infections had been previously diagnosed suggestive of mostly asymptomatic or minimally mild infections.
Mapping epigenetic divergence in the massive radiation of Lake Malawi cichlid fishes
Authors: Vernaz Grégoire , Malinsky Milan , Svardal Hannes , Du Mingliu , Tyers Alexandra M. , Santos M. Emília , Durbin Richard , Genner Martin J. , Turner George F. , Miska Eric A.
Published: November 2020

Epigenetic variation modulates gene expression and can be heritable. However, knowledge of the contribution of epigenetic divergence to adaptive diversification in nature remains limited. The massive evolutionary radiation of Lake Malawi cichlid fishes displaying extensive phenotypic diversity despite extremely low sequence divergence is an excellent system to study the epigenomic contribution to adaptation. Here, we present a comparative genome-wide methylome and transcriptome study, focussing on liver and muscle tissues in phenotypically divergent cichlid species. In both tissues we find substantial methylome divergence among species. Differentially methylated regions (DMR), enriched in evolutionary young transposons, are associated with transcription changes of ecologically-relevant genes related to energy expenditure and lipid metabolism, pointing to a link between dietary ecology and methylome divergence. Unexpectedly, half of all species-specific DMRs are shared across tissues and are enriched in developmental genes, likely reflecting distinct epigenetic developmental programmes. Our study reveals substantial methylome divergence in closely-related cichlid fishes and represents a resource to study the role of epigenetics in species diversification.
Double Lock of a Potent Human Monoclonal Antibody against SARS-CoV-2
Authors: Zhu Ling , Deng Yong-Qiang , Zhang Rong-Rong , Cui Zhen , Sun Chun-Yun , Fan Chang-Fa , Xing Xiaorui , Huang Weijin , Chen Qi , Zhang Na-Na , Ye Qing , Cao Tian-Shu , Wang Nan , Wang Lei , Cao Lei , Wang Huiyu , Kong Desheng , Ma Juan , Luo Chunxia , Zhang Yanjing , Nie Jianhui , Sun Yao , Lv Zhe , Shaw Neil , Li Qianqian , Li Xiao-Feng , Hu Junjie , Xie Liangzhi , Rao Zihe , Wang Youchun , Wang Xiangxi , Qin Cheng-Feng
Published: November 2020

Receptor recognition and subsequent membrane fusion are essential for the establishment of successful infection by SARS-CoV-2. Halting these steps can cure COVID-19. Here we have identified and characterized a potent human monoclonal antibody, HB27, that blocks SARS-CoV-2 attachment to its cellular receptor at sub-nM concentrations. Remarkably, HB27 can also prevent SARS-CoV-2 membrane fusion. Consequently, a single dose of HB27 conferred effective protection against SARS-CoV-2 in two established mouse models. Rhesus macaques showed no obvious adverse events when administrated with 10-fold of effective dose of HB27. Cryo-EM studies on complex of SARS-CoV-2 trimeric S with HB27 Fab reveal that three Fab fragments work synergistically to occlude SARS-CoV-2 from binding to ACE2 receptor. Binding of the antibody also restrains any further conformational changes of the RBD, possibly interfering with progression from the prefusion to the postfusion stage. These results suggest that HB27 is a promising candidate for immuno-therapies against COVID-19.

Highlights

SARS-CoV-2 specific antibody, HB27, blocks viral receptor binding and membrane fusion

HB27 confers prophylactic and therapeutic protection against SARS-CoV-2 in mice models

Rhesus macaques showed no adverse side effects when administered with HB27

Cryo-EM studies suggest that HB27 sterically occludes SARS-CoV-2 from its receptor