bluuebunny/crossref_metadata_2025 huggingface dataset:
Differential effects of socio-demographic factors on maternal haemoglobin concentration in three sub-Saharan African Countries
Authors: Amugsi Dickson A. , Dimbuene Zacharie T. , Kyobutungi Catherine
Published: May 2020

Objective

To investigate the effects of socio-demographic factors on maternal haemoglobin (Hb) at different points of the conditional distribution of Hb concentration.

Methods

We analysed the Demographic and Health Surveys data from Ghana, Democratic Republic of the Congo (DRC) and Mozambique, using Hb concentration of mothers aged 15-49 years as an outcome of interest. We utilise quantile regression to estimate the effects of the socio-demographic factors across specific points of the maternal Hb concentration.

Results

The results showed crucial differences in the effects of socio-demographic factors along the conditional distribution of Hb concentration. In Ghana, maternal education had a positive effect on Hb concentration in the 5thand 10thquantiles. The positive effect of education on maternal Hb concentration occurred across all quantiles in Mozambique, with the largest effect at the lowest quantile (5th) and the smallest effect at the highest quantile (90th). In contrast, maternal education had a negative effect on the Hb concentration of mothers in the 50th, 75thand 90thquantiles in DRC. Maternal body mass index (BMI) had a positive effect on Hb concentration of mothers in the 5th, 10th, 50thand 90th, and 5thto 50thquantiles in Ghana and Mozambique, respectively. Breastfeeding had a significant positive effect on Hb concentration across all countries, with the largest effect on Hb concentration of mothers in the lower quantiles. All the household wealth indices had positive effects on maternal Hb concentration across quantiles in Mozambique, with the largest effect among mothers in the upper quantiles. However, in Ghana, living in a poor wealth index was inversely related with Hb concentration of mothers in the 5thand 10thquantiles.

Conclusions

Our results showed that the effects of socio-demographic factors on maternal Hb concentration vary along its distribution. Interventions to address maternal anaemia should take these variations into account to identify the most vulnerable groups.

What this study adds

Quantile regression can be used effectively to analyse anaemia data

Socio-demographic factors have differential effects on Hb at different points of its distribution

Interpreting results based on the mean effect (as in OLS) only provides a partial picture

Breastfeeding has positive effect on maternal Hb concentration

The use of multicountry data revealed differences and commonalities between countries
A Droplet Digital PCR Assay to Detect SARS-CoV-2 RNA
Authors: Romeo Martin J. , DiPaola Christian P. , Mentus Cassidy , Timmers Cynthia D.
Published: May 2020

We describe a quantitative droplet digital PCR (ddPCR) assay for detection of SARS-CoV-2 viral ribonucleic acid (RNA) in total RNA extracted from human sputum. This method was validated using the guidance of the United States Food and Drug Administration’s Accelerated Emergency Use Authorization (EUA) Template for SARS-CoV-2 that Causes Coronavirus Disease (COVID-19) Molecular Testing of Respiratory Speciment in CLIA Certified High-Complexity Laboratories. Though our laboratory is not CLIA certified, this method met all criteria specified by the guidance document with a Limit of Detection (LOD) of 0.25 copies/μL in the final ddPCR (at least 19/20 replicates reactive), which we consider to be a Lower Limit of Quantification (LLOQ); inclusivity of all known annotated SARS-CoV-2 genomes; no cross-reactivity with other respiratory pathogens; and reactivity of all contrived positives at or above the LOD.
Understanding the nature of face processing in early autism: A prospective study
Authors: Tye Charlotte , Bussu Giorgia , Gliga Teodora , Elsabbagh Mayada , Pasco Greg , Johnsen Kristinn , Charman Tony , Jones Emily J.H. , Buitelaar Jan , Johnson Mark H. ,   the BASIS team
Published: May 2020

Dimensional approaches to psychopathology interrogate the core neurocognitive domains interacting at the individual level to shape diagnostic symptoms. Embedding this approach in prospective longitudinal studies could transform our understanding of the mechanisms underlying neurodevelopmental disorders. Such designs require us to move beyond traditional group comparisons and determine which domain-specific atypicalities apply at the level of the individual, and whether they vary across distinct phenotypic subgroups. As a proof of principle, this study examines how the domain of face processing contributes to a clinical diagnosis of Autism Spectrum Disorder (ASD). We used an event-related potentials (ERPs) task in a cohort of 8-month-old infants with (n=148) and without (n=68) an older sibling with ASD, and combined traditional case-control comparisons with machine-learning techniques like supervised classification for prediction of clinical outcome at 36 months and Bayesian hierarchical clustering for stratification into subgroups. Our findings converge to indicate that a broad profile of alterations in the time-course of neural processing of faces is an early predictor of later ASD diagnosis. Furthermore, we identified two brain response-defined subgroups in ASD that showed distinct alterations in different aspects of face processing compared to siblings without ASD diagnosis, suggesting that individual differences between infants contribute to the diffuse pattern of alterations predictive of ASD in the first year of life. This study shows that moving from group-level comparisons to pattern recognition and stratification can help to understand and reduce heterogeneity in clinical cohorts, and improve our understanding of the mechanisms that lead to later neurodevelopmental outcomes.

General Scientific Summary

This study suggests that neural processing of faces is diffusely atypical in Autism Spectrum Disorder, and that it represents a strong candidate predictor of outcome at an individual level in the first year of life.
Efficacy and safety of turmeric extracts in knee osteoarthritis: protocol for a systematic review and meta-analysis of randomised controlled trials
Authors: Wang Zhiqiang , Singh Ambrish , Antony Benny
Published: May 2020

Turmeric extracts have been used as a remedy for treating arthritis in traditional medicine. Recent years have witnessed the rise of different extracts from turmeric and randomised clinical trials (RCTs) evaluating the efficacy and safety of these extracts for the treatment of knee osteoarthritis (OA). This planned systematic review and meta-analysis aims to assess the efficacy and safety of turmeric extracts for the treatment of knee OA. Biomedical databases such as PubMed, Scopus, and Embase will be searched for RCTs reporting safety and efficacy of turmeric extracts for the treatment of knee OA. Cochrane risk of bias tool will be used to assess the methodological quality of the included studies, and a meta-analysis will be performed to pool the effect estimates.
Associations with covid-19 hospitalisation amongst 406,793 adults: the UK Biobank prospective cohort study
Authors: Khawaja Anthony P , Warwick Alasdair N , Hysi Pirro G , Kastner Alan , Dick Andrew , Khaw Peng T , Tufail Adnan , Foster Paul J , Khaw Kay-Tee
Published: May 2020

OBJECTIVES

To identify the sociodemographic, lifestyle, comorbidity and antihypertensive medication associations with the development of hospitalisation with covid-19 in an English population.

DESIGN

Prospective cohort study

SETTING

The population-based UK Biobank study was linked to English covid-19 test results.

PARTICIPANTS

Individuals resident in England and alive in 2020.

MAIN OUTCOME MEASURES

Cases (n=605) were defined by a positive covid-19 test result conducted between 16th March and 16th April 2020, during a restricted testing policy for hospitalised individuals with severe disease.

RESULTS

A total of 406,793 participants were included. Mean age on 1st January 2020 was 68 years (range 48 to 85 years). 55% were women. In multivariable models, major independent risk factors for hospitalisation with covid-19 were male sex (odds ratio 1.52; 95% confidence interval 1.28 to 1.81; P<0.001), South Asian ethnicity (2.02; 1.28 to 3.17; P=0.002) or black ethnicity (3.09; 2.18 to 4.38; P<0.001) compared to white ethnicity, greater residential deprivation (1.92 for most deprived quartile compared to least deprived quartile; 1.50 to 2.47; P<0.001), higher BMI (2.04 for BMI >35 compared to <25 Kg/m2; 1.50 to 2.77; P<0.001), former smoking (1.39 compared to never smoked; 1.16 to 1.66; P<0.001), and comorbidities hypertension (1.28; 1.06 to 1.53; P=0.009) and chronic obstructive pulmonary disease (1.81; 1.34 to 2.44; P<0.001). Increased risk was observed with increasing number of antihypertensive medications used rather than any individual class.

CONCLUSION

Understanding why these factors confer increased risk of severe covid-19 in the population may help elucidate the underlying mechanisms as well as inform strategy and policy to prevent this disease and its consequences. We found no evidence of increased risk with specific classes of antihypertensive medication.
A study on the relationship between BCG vaccination and Covid-19 prevalence: Do other confounders warrant investigation?
Authors: Mariita Richard M. , Musila Jonathan M.
Published: May 2020

The Covid-19 pandemic, which originated from Wuhan, Hubei province, China, and quickly spread to the rest of the globe is caused by SARS-CoV-2, a single-stranded RNA virus. Preliminary data suggest a relationship between the BCG vaccine and the prevalence of Covid-19. The BCG vaccine is used in the prevention of tuberculosis, a disease that is most prevalent in developing countries. To determine the potential protective role of BCG vaccination, this study investigated the occurrence of Covid-19 and the relationship between the spread of Covid-19 in countries that offer BCG vaccination and those that do not. The study also performed a phylogenetic analysis of the strains involved in the Covid-19 outbreak from the representative countries. To achieve the objectives, the study utilized publicly available data on population size, vaccination coverage, and Covid-19 cases. Phylogenetic analysis was used to determine if some SARS-CoV-2 strains were more prevalent than others. The study revealed a significant negative trend between countries that offer the BCG vaccine to the general population and the reported cases of Covid-19. The study proposes future molecular and immunological analyses to determine the potential role of BCG vaccination in protection against Covid-19. This will determine if BCG has antiviral properties, with the possibility of recommending it for widespread use if supported by scientific data.
The first 6 weeks – setting up a UK urgent dental care centre during the COVID-19 pandemic
Authors: Carter Emily , Currie Charlotte C , Asuni Abisola , Goldsmith Rachel , Toon Grace , Horridge Catherine , Simpson Sarah , Donnell Christopher , Greenwood Mark , Walton Graham , Cole Ben , Durham Justin , Holliday Richard
Published: May 2020

Introduction

The COVID-19 pandemic has posed many challenges, including provision of urgent dental care. This paper presents a prospective service evaluation during establishment of urgent dental care in the North-East of England over a six-week period.

Aim

To monitor patient volumes, demographics and outcomes at the North-East urgent dental care service and confirm appropriate care pathways.

Main Outcome Methods

Data were collected on key characteristics of patients accessing urgent care from 23rd March to 3rd May 2020. Analysis was with descriptive statistics.

Results

There were 1746 patient triages, (1595 telephone and 151 face-to-face) resulting in 1322 clinical consultations. The most common diagnoses were: symptomatic irreversible pulpitis or apical periodontitis. 65% of clinical consultations resulted in extractions, 0.5% an aerosol generating procedure. Patients travelled 25km on average to access care, however this reduced as more urgent care centres were established. The majority of patients were asymptomatic of COVID-19 and to our knowledge no staff acquired infection due to occupational exposure.

Conclusion

The urgent dental care centre effectively managed urgent and emergency dental care, with appropriate patient pathways established over the 6-week period. Dental preparedness for future pandemic crisis could be improved and informed by this data.

Three In Brief Points

A summary is given of how urgent dental care was established in the North East of England during the COVID-19 pandemic which may help with future preparedness for pandemics.

Aerosol generating procedures were almost always avoided in the delivery of urgent dental care

A telephone triage system was effectively used to determine who needed clinical care, and to separate symptomatic, asymptomatic and shielding patients, with very few failures in triage noted.
How robust are the results of one of the first positive trials exploring hydroxychloroquine for treatment of COVID-19?
Authors: Chow Ronald , Elsayed Sameer , Lock Michael
Published: May 2020

An outbreak of a novel human coronavirus infection emerged in Wuhan, China in December 2019. Two months later, the World Health Organization (WHO) announced SARS-CoV-2 as the name for the new virus and COVID-19 for the associated illness. On March 12, 2020, the WHO officially declared COVID-19 as a pandemic. The scientific community has raced to find effective therapeutic agents against the virus. Gautret et al 2020 is among one of the first purportedly positive trials of hydroxychloroquine for the treatment of COVID-19. However, it is imperative that a thorough analysis and understanding of trial data be undertaken prior to making claims about safety and efficacy. Our group assessed the statistical robustness of the trial using the Fragility Index (FI). The FI provides a numerical quantification of a clinical trial’s conclusions. The index is based on iterative statistical calculations to determine the minimum number of events within a trial that would theoretically need to change from positive to negative in order for the trial’s endpoint to convert from significant to non-significant; the higher the index, the more statistically robust the study results. For the Gautret et al trial, one endpoint had an FI of 1, two had indices of 2, and another had an index of 4. The primary endpoint of viral clearance on day 6 had an FI of 4. This indicates that if 4 events were to change from positive to negative, the conclusion of the trial would become mathematically non-significant. This index is comparable to many other published trials of established agents; the median FI across the reported literature appears to be 2. In conclusion, the trial results reported by Gautret et al are statistically robust, assuming that data quality is not compromised; however, the study was an open-label trial with non-homogenous groups, with analysis conducted per-protocol. Additionally, SARS-CoV-2 Reverse Transcriptase-PCR (RT-PCR) testing was not conducted in a systematic way amongst the two groups. Further analyses of this trial and future trials of antiviral agents with potential activity against SARS-CoV-2 should be performed with complementary epidemiologic and statistical techniques to determine whether the trial’s results are clinically important and/or should be explored in depth. Given the statistically robust results reported by Gautret et al, despite the study’s inherent methodological and analytical flaws, hydroxychloroquine should be studied as a potential agent against COVID-19 in larger clinical trials.
Quantitative analysis of the iris surface smoothness by spectral domain optical coherence tomography in Fuchs uveitis
Authors: Zarei Mohammad , Pour Elias Khalili , Ebrahimiadib Nazanin , Riazi-Esfahani Hamid
Published: May 2020

Purpose

To demonstrate the value of “smoothness index” as a novel tool for quantitative analysis of iris surface findings in unilateral Fuchs’ uveitis (FU).

Methods

In this observational study, both phakic eyes from patients with the diagnosis of unilateral FU were enrolled. All eyes underwent a complete ophthalmic examination and anterior segment optical coherence tomography(AS-OCT). The images were extracted and exported to the ImageJ software for calculating the “smoothness index (SI)”. The SI was defined as ratio of length of the straight line connecting the most peripheral and the most central points of anterior iris surface to actual length of this boundary.

Results

Forty eyes from 20 patients with unilateral FU were enrolled. Mean age of patients was 40±10 years. Mean overall SI was 0.876± 0.030 in eyes with FU that was significantly more than fellow control eyes (0.841± 0.041). (p=0.005) The mean temporal and nasal SI were 0.878± 0.035 and 0.874± 0.033 in eyes with FU, compared to 0.843± 0.041 and 0.838± 0.047 in control fellow eyes, respectively. (p = 0.008 and p = 0.009, respectively)

Conclusion

Iris “smoothness index” is a novel index to quantitatively document diffuse smoothness of iris anterior surface in eyes with FU. This index may facilitate diagnosis of subtle iris atrophic changes in these eyes, especially when heterochromia is absent.
Born to be young: prenatal thyroid hormones increase early-life telomere length
Authors: Stier Antoine , Hsu Bin-Yan , Marciau Coline , Doligez Blandine , Gustafsson Lars , Bize Pierre , Ruuskanen Suvi
Published: May 2020

Prenatal environmental conditions can have lifelong consequences on health and aging. The underlying mechanisms remain nonetheless little understood. Thyroid hormones (THs) are important regulators of embryogenesis transferred from the mother to the embryo. In an avian model, we manipulated embryo exposure to maternal THs through egg injection and investigated the consequences on postnatal growth and aging. We first report that mitochondrial DNA (mtDNA) copy number and telomere length significantly decrease from early-life to late adulthood, thus confirming that these two molecular markers are hallmarks of aging in our wild bird model. The experimental elevation of prenatal THs levels had a transient positive effect on postnatal growth. Elevated prenatal THs had no effect on mtDNA copy number but significantly increased telomere length both soon after birth and at the end of the growth period (equivalent to offsettingca.4 years of post-growth telomere shortening). These findings suggest that prenatal THs have a key role in setting the ‘biological’ age at birth, and thus might influence longevity.
Treatments administered to the first 9,152 reported cases of COVID19: a systematic review
Authors: Fajgenbaum David C. , Khor Johnson S. , Gorzewski Alek , Tamakloe Mark-Avery , Powers Victoria , Kakkis Joseph J. , Repasky Mileva , Taylor Anne , Beschloss Alexander , Hernandez-Miyares Laura , Go Beatrice , Nimgaonkar Vivek , McCarthy Madison S. , Kim Casey J. , Wing Anna , Mayer Michael A. , Pai Ruth-Anne Langan , Frankl Sarah , Fisher Megan , Germi James , Keyser Cornelia A. , Angelides Philip , Amurthur Ashwin , Jiang Joanna , Rasheed Rozena , Rodriguez-Lopez Eric , Napier Erin , Martins Bruna , Bambury Stephen , Gunderson Karen , Goodyear Nick , Mackay Duncan , Pierson Sheila K.
Published: May 2020

The emergence of SARS-CoV-2/2019 novel coronavirus (COVID19) has created a global pandemic with no approved treatments or vaccines. Many treatments have already been administered to COVID19 patients but have not been systematically evaluated. We performed a systematic literature review to identify all treatments reported to be administered to COVID19 patients and assess time to clinically meaningful response for treatments with sufficient data. We searched PubMed, BioRxiv, MedRxiv, and ChinaXiv for articles reporting treatments for COVID19 patients published between 12/1/2019–3/27/2020. Data were analyzed descriptively. Of the 2,706 articles identified, 155 studies met inclusion criteria, comprising 9,152 patients from 14 different countries. The cohort was 45.4% female and 98.3% hospitalized and mean (SD) age was 44.4 years (SD 21.0). The most frequently administered drug classes were antivirals, antibiotics, and corticosteroids, and of the 115 reported drugs, the most frequently administered was combination lopinavir/ritonavir, which was associated with a time to clinically-meaningful response (complete symptom resolution or hospital discharge) of 11.7 (1.09) days. There was insufficient data to compare across treatments. A large number of treatments have been administered to the first 9,152 reported cases of COVID19. These data serve as the basis for an open-source registry of all reported treatments given to COVID19 patients. Further work is needed to prioritize drugs for investigation in well-controlled clinical trials and treatment protocols.
What factors increase the risk of complications in SARS-CoV-2 positive patients? A cohort study in a nationwide Israeli health organization
Authors: Yanover Chen , Mizrahi Barak , Kalkstein Nir , Marcus Karni , Akiva Pinchas , Barer Yael , Shalev Varda , Chodick Gabriel
Published: May 2020

Reliably identifying patients at increased risk for COVID-19 complications could guide clinical decisions, public health policies, and preparedness efforts. To date, the most globally accepted definitions of at-risk patients rely, primarily, on epidemiological characterization of hospitalized COVID-19 patients. However, such characterization overlooks, and fails to correct for, the prevalence of existing conditions in the wider SARS-CoV-2 positive population. Here, we analyze the complete medical records of all SARS-CoV-2 infected individuals (N=4,353) in a large Israeli health organization (representing a population of 2.3 million people), of whom 173 experienced moderate or severe symptoms of COVID-19, to identify the conditions that increase the risk of disease complications, in various age and sex strata. Our analysis suggests that cardiovascular and kidney diseases, obesity, and hypertension are significant risk factors for COVID-19 complications, as previously reported. Interestingly, it also indicates that depression (e.g., odds ratio, OR, for males 65 years or older: 2.94, 95% confidence intervals [1.55, 5.58]; P-value = 0.014) as well cognitive and neurological disorder (e.g., OR for individuals ≥ 65 year old: 2.65 [1.69, 4.17]; P-value < 0.001) are significant risk factors; and that smoking and background of respiratory diseases do not significantly increase the risk of complications. Adjusting existing risk definitions following these observations may improve their accuracy and impact the global pandemic containment efforts.
The contribution of asymptomatic SARS-CoV-2 infections to transmission - a model-based analysis of the Diamond Princess outbreak
Authors: Emery Jon C , Russell Timothy W , Liu Yang , Hellewell Joel , Pearson Carl AB ,   CMMID 2019-nCoV working group, Knight Gwenan M , Eggo Rosalind M , Kucharski Adam J , Funk Sebastian , Flasche Stefan , Houben Rein M G J
Published: May 2020

Background

Some key gaps in the understanding of SARS-CoV-2 infection remain. One of them is the contribution to transmission from individuals experiencing asymptomatic infections. We aimed to characterise the proportion and infectiousness of asymptomatic infections using data from the outbreak on the Diamond Princess cruise ship.

Methods

We used a transmission model of COVID-19 with asymptomatic and presymptomatic states calibrated to outbreak data from the Diamond Princess, to quantify the contribution of asymptomatic infections to transmission. Data available included the date of symptom onset for symptomatic disease for passengers and crew, the number of symptom agnostic tests done each day, and date of positive test for asymptomatic and presymptomatic individuals.

Findings

On the Diamond Princess 74% (70-78%) of infections proceeded asymptomatically, i.e. a 1:3.8 case-to-infection ratio. Despite the intense testing 53%, (51-56%) of infections remained undetected, most of them asymptomatic. Asymptomatic individuals were the source for 69% (20-85%) of all infections. While the data did not allow identification of the infectiousness of asymptomatic infections, assuming no or low infectiousness resulted in posterior estimates for the net reproduction number of an individual progressing through presymptomatic and symptomatic stages in excess of 15.

Interpretation

Asymptomatic SARS-CoV-2 infections may contribute substantially to transmission. This is essential to consider for countries when assessing the potential effectiveness of ongoing control measures to contain COVID-19.

Funding

ERC Starting Grant (#757699), Wellcome trust (208812/Z/17/Z), HDR UK (MR/S003975/1)
Original research: How accurate are digital symptom assessment apps for suggesting conditions and urgency advice?: a clinical vignettes comparison to GPs
Authors: Gilbert Stephen , Mehl Alicia , Baluch Adel , Cawley Caoimhe , Challiner Jean , Fraser Hamish , Millen Elizabeth , Multmeier Jan , Pick Fiona , Richter Claudia , Türk Ewelina , Upadhyay Shubhanan , Virani Vishaal , Vona Nicola , Wicks Paul , Novorol Claire
Published: May 2020

Objectives

To compare breadth of condition coverage, accuracy of suggested conditions and appropriateness of urgency advice of 8 popular symptom assessment apps with each other and with 7 General Practitioners.

Design

Clinical vignettes study.

Setting

200 clinical vignettes representing real-world scenarios in primary care.

Intervention/comparator

Condition coverage, suggested condition accuracy, and urgency advice performance was measured against the vignettes’ gold-standard diagnoses and triage level.

Primary outcome measures

Outcomes included (i) proportion of conditions “covered” by an app, i.e. not excluded because the patient was too young/old, pregnant, or comorbid, (ii) proportion of vignettes in which the correct primary diagnosis was amongst the top 3 conditions suggested, and, (iii) proportion of “safe” urgency level advice (i.e. at gold standard level, more conservative, or no more than one level less conservative).

Results

Condition-suggestion coverage was highly variable, with some apps not offering a suggestion for many users: in alphabetical order, Ada: 99.0%; Babylon: 51.5%; Buoy: 88.5%; K Health: 74.5%; Mediktor: 80.5%; Symptomate: 61.5%; Your.MD: 64.5%. The top-3 suggestion accuracy (M3) of GPs was on average 82.i±5.2%. For the apps it was - Ada: 70.5%; Babylon: 32.0%; Buoy: 43.0%; K Health: 36.0%; Mediktor: 36.0%; Symptomate: 27.5%; WebMD: 35.5%; Your.MD: 23.5%. Some apps exclude certain user groups (e.g. younger users) or certain conditions - for these apps condition-suggestion performance is generally greater with exclusion of these vignettes. For safe urgency advice, tested GPs had an average of 97.0±2.5%. For the vignettes with advice provided, only three apps had safety performance within 1 S.D. of the GPs (mean) - Ada: 97.0%; Babylon: 95.i%; Symptomate: 97.8%. One app had a safety performance within 2 S.D.s of GPs - Your.MD: 92.6%. Three apps had a safety performance outside 2 S.D.s of GPs - Buoy: 80.0% (p<0.001); K Health: 81.3% (p <0.001); Mediktor: 87.3% (p =1.3×10-3).

Conclusions

The utility of digital symptom assessment apps relies upon coverage, accuracy, and safety. While no digital tool outperformed GPs, some came close, and the nature of iterative improvements to software offers scalable improvements to care.
Nonlinear Classification of EEG recordings from patients with Alzheimer’s Disease using Gaussian Process Latent Variable Model
Authors: Gunawardena S. Rajintha. A. S. , He Fei , Sarrigiannis Ptolemaios , Blackburn Daniel J.
Published: May 2020

In this work, nonlinear temporal features from multi-channel EEGs are used for the classification of Alzheimer’s disease patients from healthy individuals. This was achieved by temporal manifold learning using Gaussian Process Latent Variable Models (GPLVM) as a nonlinear dimensionality reduction technique. Classification of the extracted features was undertaken using a nonlinear Support Vector Machine. Comparisons were made against the linear counterpart, Principle Component Analysis while exploring the effect of the time window or EEG epoch length used. It was demonstrated that temporal manifold learning using GPLVM is better in extracting features that attain high separability and prediction accuracy. This work aims to set the significance of using GPLVM temporal manifold learning for EEG feature extraction in the classification of Alzheimer’s disease.
COVID-19 diagnosis prediction by symptoms of tested individuals: a machine learning approach
Authors: Zoabi Yazeed , Shomron Noam
Published: May 2020

Motivation

Effective screening of SARS-CoV-2 enables quick and efficient diagnosis of COVID-19 and can mitigate the burden on healthcare systems. Prediction models that combine several features to estimate the risk of infection have been developed in hopes of assisting medical staff worldwide in triaging patients when allocating limited healthcare resources.

Results

We established a machine learning approach that trained on records from 51,831 tested individuals (of whom 4,769 were confirmed COVID-19 cases) while the test set contained data from the following week (47,401 tested individuals of whom 3,624 were confirmed COVID-19 cases). Our model predicts COVID-19 test results with high accuracy using only eight features: gender, whether age is above 60, known contact with an infected individual, and five initial clinical symptoms.

Overall, based on the nationwide data publicly reported by the Israeli Ministry of Health, we developed a model that detects COVID-19 cases by simple features accessed by asking basic questions. Our framework can be used, among other considerations, to prioritize testing for COVID-19 when allocating limited testing resources.

Availability

All data used in this study was retrieved from the Israeli Ministry of Health website.

Contact

yazeed@tauex.tau.ac.il, nshomron@tauex.tau.ac.il
Utility and limitations of Google searches on sensory loss as markers for new COVID-19 cases
Authors: Asseo Kim , Fierro Fabrizio , Slavutsky Yuli , Frasnelli Johannes , Niv Masha Y
Published: May 2020

Evidence of smell loss in COVID-19 is growing. Researchers and analysts have suggested to use Google searches on smell loss as indicators of COVID-19 cases. However, such searches may be due to interest elicited by media coverage of the COVID-19-related smell loss, rather than attempts to understand self-symptoms. We analyzed searches related to 4 senses: smell and taste (both recently shown to be impaired in some COVID-19 patients), vision and sight (senses not currently known to be impaired in COVID-19 patients), and an additional general control (“COVID-19 symptoms”). Focusing on two countries with a large number of cases, Italy and the United States, we have compared Google Trends results per region or state to the number of new cases prevalence in that region. The analysis was performed for each of the 8 weeks ranging from March 4th till April 28th.

No correlation with vision loss or sight loss searches was identified, while taste and smell loss searches were correlated with new COVID-19 cases during a limited time window, that starts when the number of weekly new cases reached for the first time 21357 cases in Italy (11-17 March) and 47553 in the US (18-24 March).

Media effect on the specific symptoms searches was also analyzed, establishing a different impact according to the country.

Our results suggest that Google Trends for taste loss and smell loss searches captured a genuine connection between these symptoms and new COVID-19 cases prevalence in the population. However, due to variability in correlation from week to week, and overall decrease in correlation as taste and smell loss are becoming known COVID-19 symptoms, recognized now by CDC and World Health Organization, Google Trends is no longer a reliable marker for monitoring the disease spread. The “surprise rise” followed by decrease, probably attributable to knowledge saturation, should be kept in mind for future digital media analyses of potential new symptoms of COVID-19 or future pandemics.
Transmission in Latent Period Causes A Large Number of Infected People in the United States
Authors: Liu Qinghe , Zhu Junkai , Liu Zhicheng , Zhu Yuhao , Zhou Liuling , Gao Zefei , Li Deqiang , Tang Yuanbo , Zhang Xiang , Yang Junyan , Wang Qiao
Published: May 2020

The cumulative number of confirmed cases in the United States exceeded one million on 29 April 2020, becoming the country of the most serious pandemic in the world. We proposed a model to analyze the real situation and follow-up trend of the epidemic in the US.

The proposed model divides the epidemic period into two phases, and includes three different categories of transmitters: the latent population, the documented infectious population, and the undocumented infectious population. We use metapopulation network to simulate the spread of the COVID-19 in the US, and apply the Bayesian inference to estimate the key parameters of the model. We also perform component analysis and sensitivity analysis, researching the compositions of the people with COVID-19.

The results show that the basic reproduction number in the early period of propagation is 4.06. As of April 13, 2020, only 45% (95% CI: 35% - 73%) of symptom onset cases in the United States were documented. The incubation period of COVID-19 is 10.69 days (95% CI: 10.02 – 11.74). If the current level of interventions is continued, the cumulative number of confirmed cases is expected to reach more than 1.7 million in July and continue to grow.
Epidemiology of CoVID-19 and predictors of recovery in the Republic of Korea
Authors: Das Ashis Kumar , Gopalan Saji Saraswathy
Published: May 2020

Background

The recent CoVID-19 pandemic has emerged as a threat to global health. Though current evidence on the epidemiology of the disease is emerging, very little is known about the predictors of recovery.

Objectives

To describe the epidemiology of confirmed CoVID-19 patients in Republic of Korea and identify predictors of recovery.

Materials and methods

Using publicly available data for confirmed CoVID-19 cases from the Korea Centers for Disease Control and Prevention from January 20, 2020 to April 30, 2020, we undertook descriptive analyses of cases stratified by sex, age group, place of exposure, date of confirmation and province. Correlation was tested among all predictors (sex, age group, place of exposure and province) with the Pearson’s correlation coefficient. Associations between recovery from CoVID-19 and predictors were estimated using a multivariable logistic regression model.

Results

Majority of the confirmed cases were females (56%), from 20-29 age group (24.3%), and primarily from three provinces –– Gyeongsangbuk-do (36.9%), Gyeonggi-do (20.5%) and Seoul (17.1%). Case fatality ratio was 2.1% and 41.6% cases recovered. Older patients, patients from provinces such as Daegu, Gyeonggi-do, Gyeongsangbuk-do, Jeju-do, Jeollabuk-do and Jeollanam-do, and those contracting the disease from healthcare settings had lower recovery.

Conclusions

Our study adds to the very limited evidence base on potential predictors of survival among confirmed CoVID-19 cases. We call additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups.
E-cigarette use frequency by smoking status among youth in the United States, 2014-2019
Authors: Tam Jamie
Published: May 2020

Aims

To report annual 2014-2019 youth estimates of past 30-day e-cigarette use frequency by smoking status in the United States (US).

Design

Weighted prevalence estimates of student’s e-cigarette use using the 2014-2019 National Youth Tobacco Surveys (NYTS). For each year, t-tests for significance were used to compare estimates with those from the preceding year; t-tests were not performed on data for 2019 due to the change in survey format from paper to electronic.

Setting

The NYTS is an annual school-based cross-sectional survey of US middle school (MS) and high school (HS) students.

Participants

117,472 students.

Measurements

Self-report of past 30 day e-cigarette use based on students’ smoking status. Smoking status is assessed by asking if students have ever tried smoking, “even one or two puffs”, with never smokers responding “no”. Former smokers respond “yes” but have not smoked at all in the past 30 days. Current smokers used cigarettes at least once in the past 30 days. Frequent e-cigarette use is defined as use on ≥20 days in the past month.

Findings

Past 30-day and frequent e-cigarette use increased among never, former, and current smoker youth from 2014-2019. In 2019, a greater proportion of current smokers used e-cigarettes frequently (HS = 46.1%, 95% CI: 39.1, 53.2; MS = 27.4%, 95% CI: 21.1, 33.6) compared to former smokers (HS = 23.2%, 95% CI: 18.1, 28.2; MS = 10.9%, 95% CI: 6.1, 15.7) and never smokers (HS = 3.7%, 95% CI: 3.0, 4.3; MS = 0.7%, 95% CI: 0.4, 0.9). From 2018 to 2019, the total number of youth using e-cigarettes frequently who were never smokers (2018: 180,000; 2019: 490,000) or former smokers (2018: 260,000; 2019: 640,000) surpassed that of current smokers (2018: 420,000; 2019: 460,000).

Conclusions

The proportion and number of never smoker youth using e-cigarettes frequently increased greatly since 2014.
Relationship between odor intensity estimates and COVID-19 population prediction in a Swedish sample
Authors: Iravani Behzad , Arshamian Artin , Ravia Aharon , Mishor Eva , Snitz Kobi , Shushan Sagit , Roth Yehudah , Perl Ofer , Honigstein Danielle , Weissgross Reut , Karagach Shiri , Ernst Gernot , Okamoto Masako , Mainen Zachary , Monteleone Erminio , Dinnella Caterina , Spinelli Sara , Mariño-Sánchez Franklin , Ferdenzi Camille , Smeets Monique , Touhara Kazushige , Bensafi Moustafa , Hummel Thomas , Sobel Noam , Lundström Johan N.
Published: May 2020

In response to the COVID-19 pandemic, countries have implemented various strategies to reduce and slow the spread of the disease in the general population. For countries that have implemented restrictions on its population in a step-wise manner, monitoring of COVID-19 prevalence is of importance to guide decision on when to impose new, or when to abolish old, restrictions. We are here determining whether measures of odor intensity in a large sample can serve as one such measure. Online measures of how intense common household odors are perceived and symptoms of COVID-19 were collected from 2440 Swedes. Average odor intensity ratings were then compared to predicted COVID-19 population prevalence over time in the Swedish population and were found to closely track each other (r=-0.83). Moreover, we found that there was a large difference in rated intensity between individuals with and without COVID-19 symptoms and number of symptoms was related to odor intensity ratings. Finally, we found that individuals progressing from reporting no symptoms to subsequently reporting COVID-19 symptoms demonstrated a large drop in olfactory performance. These data suggest that measures of odor intensity, if obtained in a large and representative sample, can be used as an indicator of COVID-19 disease in the general population. Importantly, this simple measure could easily be implemented in countries without wide-spread access to COVID-19 testing or implemented as a fast early response before widespread testing can be facilitated.
Early Mandated Social Distancing is a Strong Predictor of Reduction in Highest Number of New COVID-19 cases per Day within Various Geographic Regions
Authors: Qureshi Adnan I. , Suri M. Fareed K. , Chu Haitao , Suri Habibullah Khan , Suri Ayehsa Khan
Published: May 2020

Mandated social distancing has been globally applied to limit the spread of corona virus disease 2019 (COVID-19) from highly pathogenic severe acute respiratory syndrome (SARS)-associated coronavirus 2 (SARS-CoV-2). The benefit of this community-based intervention in limiting COVID-19 has not been proven nor quantified. We examined the effect of timing of mandated social distancing on the rate of COVID-19 in 119 geographic regions derived from 41 states within United States and 78 countries. We found that highest number of new COVID-19 cases per day per million persons was significantly associated with total number of COVID-19 cases per million persons on the day before mandated social distancing (β=0.66, p<0.0001). Our findings suggest that the initiation of mandated social distancing for each doubling in number of existing COVID-19 cases would result in eventual peak with 58% higher number of COVID-19 infections per day. Subgroup analysis on those regions where the highest number of new COVID-19 cases per day have peaked increased β to .85 (p<0.0001). We demonstrate that initiating mandated social distancing at a 10 times smaller number of COVID-19 cases will reduce the number of daily new COVID-19 cases at peak by 80% highlighting the importance of this community-based intervention.
Connectome and microcircuit models implicate atypical subcortico-cortical interactions in autism pathophysiology
Authors: Park Bo-yong , Hong Seok-Jun , Valk Sofie , Paquola Casey , Benkarim Oualid , Bethlehem Richard A. I. , Di Martino Adriana , Milham Michael P. , Gozzi Alessandro , Yeo B. T. Thomas , Smallwood Jonathan , Bernhardt Boris C.
Published: May 2020

Abstract

Both macroscale connectome miswiring and microcircuit anomalies have been suggested to play a role in the pathophysiology of autism. However, an overarching framework that consolidates these macro and microscale perspectives of the condition is lacking. Here, we combined connectome-wide manifold learning and biophysical simulation models to understand associations between global network perturbations and microcircuit dysfunctions in autism. Our analysis established that autism showed significant differences in structural connectome organization relative to neurotypical controls, with strong effects in low-level somatosensory regions and moderate effects in high-level association cortices. Computational models revealed that the degree of macroscale anomalies was related to atypical increases of subcortical inputs into cortical microcircuits, especially in sensory and motor areas. Transcriptomic decoding and developmental gene enrichment analyses provided biological context and pointed to genes expressed in cortical and thalamic areas during childhood and adolescence. Supervised machine learning showed the macroscale perturbations predicted socio-cognitive symptoms and repetitive behaviors. Our analyses provide convergent support that atypical subcortico-cortical interactions may contribute to both microcircuit and macroscale connectome anomalies in autism.
Primate-specific response of astrocytes to stroke limits peripheral macrophage infiltration
Authors: Boghdadi Anthony G. , Spurrier Joshua , Teo Leon , Li Mingfeng , Skarica Mario , Cao Benjamin , Kwan William , Merson Tobias D. , Nilsson Susie K. , Sestan Nenad , Strittmatter Stephen M. , Bourne James A.
Published: May 2020

Reactive astrocytes play critical roles after brain injuries but their precise function in stroke is not well defined. Here, we utilized single nuclei transcriptomics to characterize astrocytes after ischemic stroke in nonhuman primate (NHP) marmoset monkey primary visual cortex. We identified 19 putative subtypes of astrocytes from injured and uninjured brain hemispheres and observed nearly complete segregation between stroke and control astrocyte clusters. We then screened for genes that might be limiting stroke recovery and discovered that one neurite-outgrowth inhibitory protein, NogoA, previously associated with oligodendrocytes but not astrocytes, was expressed in numerous reactive astrocyte subtypes. NogoA upregulation on reactive astrocytes was confirmedin vivofor NHP and human, but not observed to the same extent in rodent. Furtherin vivoandin vitrostudies determined that NogoA mediated an anti-inflammatory response which limits deeper infiltration of peripheral macrophages from the lesion during the subacute post-stroke period. Specifically, these findings are relevant to the development of NogoA-targeting therapies shortly after ischemic stroke. Our findings have uncovered the complexity and species specificity of astrocyte responses, which need to be considered more when investigating novel therapeutics for brain injury.
Differential neural circuitry behind autism subtypes with imbalanced social-communicative and restricted repetitive behavior symptoms
Authors: Bertelsen Natasha , Landi Isotta , Bethlehem Richard A. I. , Seidlitz Jakob , Busuoli Elena Maria , Mandelli Veronica , Satta Eleonora , Trakoshis Stavros , Auyeung Bonnie , Kundu Prantik , Loth Eva , Dumas Guillaume , Baumeister Sarah , Beckmann Christian F. , Bölte Sven , Bourgeron Thomas , Charman Tony , Durston Sarah , Ecker Christine , Holt Rosemary J. , Johnson Mark H. , Jones Emily J. H. , Mason Luke , Meyer-Lindenberg Andreas , Moessnang Carolin , Oldehinkel Marianne , Persico Antonio , Tillmann Julian , Williams Steven C. R. , Spooren Will , Murphy Declan G. M. , Buitelaar Jan K. ,   the EU-AIMS LEAP group, Baron-Cohen Simon , Lai Meng-Chuan , Lombardo Michael V.
Published: May 2020

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC=RRB, SC>RRB, and RRB>SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n=509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC>RRB and visual association circuitry in SC=RRB. The SC=RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.
Fast scanned widefield scheme provides tunable and uniform illumination for optimized SMLM on large fields of view
Authors: Mau Adrien , Friedl Karoline , Leterrier Christophe , Bourg Nicolas , Lévêque-Fort Sandrine
Published: May 2020

Quantitative analyses in classical fluorescence microscopy and Single Molecule Localization Microscopy (SMLM) require uniform illumination over the field of view; ideally coupled with optical sectioning techniques such as Total Internal Reflection Fluorescence (TIRF) to remove out of focus background. In SMLM, high irradiances (several kW/cm²) are crucial to drive the densely labeled sample into the single molecule regime, and conventional gaussian-shaped lasers will typically restrain the usable field of view to around 40 µm x 40 µm. Here we present Adaptable Scanning for Tunable Excitation Regions (ASTER), a novel and versatile illumination technique that generates uniform illumination over adaptable fields of view and is compatible with illumination schemes from epifluorescence to speckle-free TIRF. For SMLM, ASTER delivers homogeneous blinking kinetics at reasonable laser power, providing constant precision and higher throughput over fields of view 25 times larger than typical. This allows improved clustering analysis and uniform size measurements on sub-100 nm objects, as we demonstrate by imaging nanorulers, microtubules and clathrin-coated pits in COS cells, as well as periodic β2-spectrin along the axons of neurons. ASTER’s sharp, quantitative TIRF and SMLM images up to 200 µm x 200 µm in size pave the way for high-throughput quantification of cellular structures and processes.