bluuebunny/crossref_metadata_2025_split huggingface dataset:
Platelets can contain SARS-CoV-2 RNA and are hyperactivated in COVID-19
Authors: Zaid Younes , Puhm Florian , Allaeys Isabelle , Naya Abdallah , Oudghiri Mounia , Khalki Loubna , Limami Youness , Zaid Nabil , Sadki Khalid , El Haj Rafiqua Ben , Maher Wissal , Lamiae Belayachi , Belefquih Bouchra , Benouda Amina , Cheikh Amine , Cherrah Yahia , Flamand Louis , Guessous Fadila , Boilard Eric 
Published: June 2020

ABSTRACTRationaleIn addition to the overwhelming lung inflammation that prevails in COVID-19, hypercoagulation and thrombosis contribute to the lethality of subjects infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Platelets are chiefly implicated in thrombosis. Moreover, they can interact with viruses and are an important source of inflammatory mediators. While a lower platelet count is associated with severity and mortality, little is known about platelet function during COVID-19.ObjectiveTo evaluate the contribution of platelets to inflammation and thrombosis in COVID-19 patients.Methods and ResultsWe document the presence of SARS-CoV-2 RNA in platelets of COVID-19 patients. Exhaustive assessment of cytokines in plasma and in platelets revealed the modulation of platelet-associated cytokine levels in COVID-19, pointing to a direct contribution of platelets to the plasmatic cytokine load. Moreover, we demonstrate that platelets release their alpha- and dense-granule contents and phosphatidylserine-exposing extracellular vesicles. Functionally, platelets were hyperactivated in COVID-19 subjects, with aggregation occurring at suboptimal thrombin concentrations. Furthermore, platelets adhered more efficiently onto collagen-coated surfaces under flow conditions.ConclusionsThese data suggest that platelets could participate in the dissemination of SARS-CoV-2 and in the overwhelming thrombo-inflammation observed in COVID-19. Thus, blockade of platelet activation pathways may improve outcomes in this disease.KEY POINTSPlatelets are a source of inflammatory cytokines and degranulate in COVID-19 Platelets contain SARS-CoV-2 RNA molecules and are prone to activation in COVID-19Subject termsInfectious diseases/Emerging infectious diseases, SARS-CoV-2, COVID-19, Hematology, Platelets
The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals
Authors: Strawbridge Rona J. , Johnston Keira J. A. , Bailey Mark E. S. , Baldasarre Damiano , Cullen Breda , Eriksson Per , DeFaire Ulf , Ferguson Amy , Gigante Bruna , Giral Philippe , Graham Nicholas , Hamsten Anders , Humphries Steve E. , Kurl Sudhir , Lyall Donald M. , Lyall Laura M. , Pirro Matteo , Pell Jill P. , Savonen Kai , Sennblad Bengt , Smit Andries J. , Tremoli Elena , Tomainen Tomi-Pekka , Veglia Fabrizio , Ward Joey , Smith Daniel J. 
Published: June 2020

AbstractUnderstanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researcher. We explored whether genetic variation could identify individuals with different metabolic profiles. Loci previously associated with schizophrenia, bipolar disorder and major depressive disorder were identified from literature and those overlapping loci genotyped on the Illumina CardioMetabo and Immuno chips (representing cardiometabolic processes and diseases) were selected. In the IMPROVE study (high cardiovascular risk) and UK Biobank (general population) multidimensional scaling was applied to genetic variants implicated in both mental and cardiometabolic illness. Visual inspection of the resulting plots used to identify distinct clusters. Differences between clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both cardiometabolic disease and schizophrenia (but not bipolar or major depressive disorders) identified three groups of individuals with distinct metabolic profiles. The grouping was replicated in UK Biobank, albeit with less distinction between metabolic profiles. This study provides proof of concept that common biology underlying mental and physical illness can identify subsets of individuals with different cardiometabolic profiles.
Longitudinal immunological analyses reveal inflammatory misfiring in severe COVID-19 patients
Authors: Lucas Carolina , Wong Patrick , Klein Jon , Castro Tiago B.R. , Silva Julio , Sundaram Maria , Ellingson Mallory K. , Mao Tianyang , Oh Ji Eun , Israelow Benjamin , Tokuyama Maria , Lu Peiwen , Venkataraman Arvind , Park Annsea , Mohanty Subhasis , Wang Haowei , Wyllie Anne L. , Vogels Chantal B.F. , Earnest Rebecca , Lapidus Sarah , Ott Isabel M. , Moore Adam J. , Muenker M. Catherine , Fournier John B. , Campbell Melissa , Odio Camila D. , Casanovas-Massana Arnau ,   Yale IMPACT Team, Herbst Roy , Shaw Albert C. , Medzhitov Ruslan , Schulz Wade L. , Grubaugh Nathan D. , Cruz Charles Dela , Farhadian Shelli , Ko Albert I. , Omer Saad B. , Iwasaki Akiko 
Published: June 2020

AbstractRecent studies have provided insights into the pathogenesis of coronavirus disease 2019 (COVID-19)1-4. Yet, longitudinal immunological correlates of disease outcome remain unclear. Here, we serially analysed immune responses in 113 COVID-19 patients with moderate (non-ICU) and severe (ICU) disease. Immune profiling revealed an overall increase in innate cell lineages with a concomitant reduction in T cell number. We identify an association between early, elevated cytokines and worse disease outcomes. Following an early increase in cytokines, COVID-19 patients with moderate disease displayed a progressive reduction in type-1 (antiviral) and type-3 (antifungal) responses. In contrast, patients with severe disease maintained these elevated responses throughout the course of disease. Moreover, severe disease was accompanied by an increase in multiple type 2 (anti-helminths) effectors including, IL-5, IL-13, IgE and eosinophils. Unsupervised clustering analysis of plasma and peripheral blood leukocyte data identified 4 immune signatures, representing (A) growth factors, (B) type-2/3 cytokines, (C) mixed type-1/2/3 cytokines, and (D) chemokines that correlated with three distinct disease trajectories of patients. The immune profile of patients who recovered with moderate disease was enriched in tissue reparative growth factor signature (A), while the profile for those with worsened disease trajectory had elevated levels of all four signatures. Thus, we identified development of a maladapted immune response profile associated with severe COVID-19 outcome and early immune signatures that correlate with divergent disease trajectories.
Point prevalence of SARS-CoV-2 and infection fatality rate in Orleans and Jefferson Parish, Louisiana, May 9-15, 2020
Authors: Feehan Amy K , Fort Daniel , Garcia-Diaz Julia , Price-Haywood Eboni , Velasco Cruz , Sapp Eric , Pevey Dawn , Seoane Leonardo 
Published: June 2020

AbstractUsing a novel recruitment method to reduce selection bias with paired molecular and antibody testing for SARS-CoV-2 infection, we determined point prevalence in a racially diverse municipality. Infections were highly variable by ZIP and differed by race. Overall census-weighted prevalence was 7.8% and the calculated infection fatality rate was 1.63%.
Detection of Major Depressive Disorder Using Vocal Acoustic Analysis and Machine Learning
Authors: Espinola Caroline Wanderley , Gomes Juliana Carneiro , Pereira Jessiane Mônica Silva , dos Santos Wellington Pinheiro 
Published: June 2020

AbstractPurposeDiagnosis and treatment in psychiatry are still highly dependent on reports from patients and on clinician judgement. This fact makes them prone to memory and subjectivity biases. As for other medical fields, where objective biomarkers are available, there has been an increasing interest in the development of such tools in psychiatry. To this end, vocal acoustic parameters have been recently studied as possible objective biomarkers, instead of otherwise invasive and costly methods. Patients suffering from different mental disorders, such as major depressive disorder (MDD), may present with alterations of speech. These can be described as uninteresting, monotonous and spiritless speech, low voice.MethodsThirty-three individuals (11 males) over 18 years old were selected, 22 of which being previously diagnosed with MDD, and 11 healthy controls. Their speech was recorded in naturalistic settings, during a routine medical evaluation for psychiatric patients, and in different environments for healthy controls. Voices from third parties were removed. The recordings were submitted to to a vocal feature extraction algorithm, and to different machine learning classification techniques.ResultsThe results showed that support vector machines (SVM) models provided the greatest classification performances for different kernels, with PUK kernel providing accuracy of 89.14% for the detection of MDD.ConclusionThe use of machine learning classifiers with vocal acoustics features has shown to be very promising for the detection of major depressive disorder, but further tests with a larger sample will be necessary to validate our findings.
A model of COVID-19 transmission and control on university campuses
Authors: Lopman Ben , Liu Carol Y. , Guillou Adrien Le , Handel Andreas , Lash Timothy L. , Isakov Alexander P. , Jenness Samuel M. 
Published: June 2020

AbstractIn response to the COVID-19 pandemic, institutions of higher education in almost every nation closed in the first half of 2020. University administrators are now facing decisions about if and how to safely return students, staff and faculty to campus. To provide a framework to evaluate various strategies, we developed a susceptible-exposed-infectious-recovered (SEIR) type deterministic compartmental transmission model of SARS-CoV-2 among students, staff and faculty. Our goals were to support the immediate pandemic planning at our own university, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. We parameterized the model for our institution, Emory University, a medium-size private university in Atlanta, Georgia. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explore a range of screening and testing frequencies and perform a probabilistic sensitivity analysis of input parameters. We find that monthly and weekly screening can reduce cumulative incidence by 30% and 81% in students, respectively, while testing with a 2-, 4- and 7-day delay results in an 92%, 85% and 73% reduction in cumulative incidence in students over the semester, respectively. Smaller reductions are observed among staff and faculty. A testing strategy requires far fewer diagnostic assays to be implemented than a screening assay. Our intervention model is conservative in that we assume a fairly high reproductive number. We find that community-introduction of SARS-CoV-2 infection onto campus may be controlled with effective testing, isolation, contract tracing and quarantine, but that cases, hospitalization, and (in some scenarios) deaths may still occur. In addition to estimating health impacts, this model can help to predict the resource requirements in terms of diagnostic capacity and isolation/quarantine facilities associated with different strategies.
HAS COUNTRYWIDE LOCKDOWN WORKED AS A FEASIBLE MEASURE IN BENDING THE COVID-19 CURVE IN DEVELOPING COUNTRIES?
Authors: Nabi Khondoker Nazmoon , Islam Md. Robiul 
Published: June 2020

AbstractIn the absence of any effective vaccine and clinically proven treatment, experts thought that strict lockdown measures could be an effective way to slow down the spread of novel coronavirus. Despite the strict lockdown measures in several developing countries, the number of newly infected cases is getting unbridled as time progresses. This anomaly ignites questions about the effectiveness of the prolonged strict confinement measures. In light of the above view, with an aim to find the answer to this question, trends of four epidemiological parameters: growth factor of daily reported COVID-19 cases, daily incidence proportion, daily cumulative index and effective reproduction number in five developing countries named Bangladesh, Brazil, Chile, Pakistan and South Africa have been analysed meticulously considering the different phases of their national lockdowns. Any compelling evidence has not been found in favor of countrywide lockdown effectiveness in the above-mentioned countries. Numerical results illustrate that stringent nationwide lockdown measures have failed bringing the epidemic threshold (Re) of COVID-19 under unity. In addition, citizens of the aforementioned countries have been struggling with catastrophic socio-economic consequences due to prolonged confinement measures. Our study suggests that a new policy should be proposed for developing countries to battle against future disease outbreaks ensuring a perfect balance between saving lives and confirming livelihoods.
Analysis and Prediction of COVID-19 Characteristics Using a Birth-and-Death Model
Authors: Viswanath Narayanan C. 
Published: June 2020

AbstractIts spreading speed together with the risk of fatality might be the main characteristic that separates COVID-19 from other infectious diseases in our recent history. In this scenario, mathematical modeling for predicting the spread of the disease could have great value in containing the disease. Several very recent papers have contributed to this purpose. In this study we propose a birth-and-death model for predicting the number of COVID-19 active cases. It relation to the Susceptible-Infected-Recovered (SIR) model has been discussed. An explicit expression for the expected number of active cases helps us to identify a stationary point on the infection curve, where the infection ceases increasing. Parameters of the model are estimated by fitting the expressions for active and total reported cases simultaneously. We analyzed the movement of the stationary point and the basic reproduction number during the infection period up to the 20th of April 2020. These provide information about the disease progression path and therefore could be really useful in designing containment strategies.
A novel demographic-based model shows that intensive testing and social distancing are concurrently required to extinguish COVID-19 progression in densely populated urban areas
Authors: Alvarez Mario Moisés , Santiago Grissel Trujillo-de 
Published: June 2020

AbstractWe present a simple epidemiological model that includes demographic density, social distancing, and efficacy of massive testing and quarantine as the main parameters to model the progression of COVID-19 pandemics in densely populated urban areas (i.e., above 5,000 inhabitants km2). Our model demonstrates that effective containment of pandemic progression in densely populated cities is achieved only by combining social distancing and widespread testing for quarantining of infected subjects. Our results suggest that extreme social distancing without intensive testing is ineffective in extinguishing COVID-19. This finding has profound epidemiological significance and sheds light on the controversy regarding the relative effectiveness of widespread testing and social distancing. Our simple epidemiological simulator is also useful for assessing the efficacy of governmental/societal responses to an outbreak.This study also has relevant implications for the concept of smart cities, as densely populated areas are hotspots that are highly vulnerable to epidemic crises.
Online respondent-driven detection for enhanced contact tracing of close-contact infectious diseases: benefits and barriers for public health practice
Authors: Helms Yannick B. , Hamdiui Nora , Eilers Renske , Hoebe Christian , Dukers-Muijrers Nicole , van den Kerkhof Hans , Timen Aura , Stein Mart L. 
Published: June 2020

AbstractBackgroundOnline respondent-driven detection (online-RDD) is a novel method of case-finding that can enhance contact tracing. However, the advantages and challenges of online-RDD for contact tracing (CT) have not yet been investigated from the perspective of public health professionals (PHPs). Therefore, it remains unclear if, and under what circumstances, PHPs are willing to apply online-RDD for contact tracing.MethodsFirst, between March and April 2019, we conducted semi-structured interviews with Dutch PHPs responsible for CT in practice. Questions were derived from the ‘diffusion of innovations’ theory. Second, between May and June 2019 we distributed an online questionnaire to 260 Dutch PHPs to quantify the main qualitative findings. Using hypothetical scenarios that involved close-contact pathogens (scabies, shigella, and mumps), we assessed anticipated advantages and challenges of online-RDD and PHPs’ intention to apply online-RDD for contact tracing.ResultsTwelve interviews were held and 70 PHPs filled in the online questionnaire. A majority of questionnaire respondents (71%) had a positive intention towards using online-RDD for contact tracing. Anticipated advantages of online-RDD were related to accommodating easy and autonomous participation in contact tracing of patients and contact persons, and reaching contact persons more efficiently. Anticipated challenges with online-RDD were related to limited opportunities for PHPs to support, motivate, and coordinate the execution of contact tracing, adequately conveying measures to patients and contact persons, and anticipated unrest among patients and contact persons. Online-RDD was considered more applicable when patients and their contact persons are reluctant to share sensitive information directly with PHPs, digitally skilled and literate persons are involved, and the scope of contact tracing is large. Online-RDD was considered less applicable when consequences of missing information or individuals are severe for individuals - or public health, when measures that patients and contact persons need to undertake are complex or impactful, and when a disease is perceived as particularly severe or sensitive by patients and their contact persons.ConclusionsPHPs generally perceived online-RDD as beneficial to public health practice. The method can help overcome challenges present in regular CT and could be used during outbreaks of infectious diseases that spread via close-contact, such as the SARS-CoV-2 virus. We propose a staggered implementation study to further investigate the application of online-RDD for enhanced CT during the ongoing COVID-19 pandemic.
Using Machine Learning of Clinical Data to Diagnose COVID-19
Authors: Li Wei Tse , Ma Jiayan , Shende Neil , Castaneda Grant , Chakladar Jaideep , Tsai Joseph C. , Apostol Lauren , Honda Christine O. , Xu Jingyue , Wong Lindsay M. , Zhang Tianyi , Lee Abby , Gnanasekar Aditi , Honda Thomas K. , Kuo Selena Z. , Yu Michael Andrew , Chang Eric Y. , Rajasekaran Mahadevan “Raj” , Ongkeko Weg M. 
Published: June 2020

AbstractThe recent pandemic of Coronavirus Disease 2019 (COVID-19) has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests. In this study, we propose to generate a more accurate diagnosis model of COVID-19 based on patient symptoms and routine test results by applying machine learning to reanalyzing COVID-19 data from 151 published studies. We aimed to investigate correlations between clinical variables, cluster COVID-19 patients into subtypes, and generate a computational classification model for discriminating between COVID −19 patients and influenza patients based on clinical variables alone. We discovered several novel associations between clinical variables, including correlations between being male and having higher levels of serum lymphocytes and neutrophils. We found that COVID-19 patients could be clustered into subtypes based on serum levels of immune cells, gender, and reported symptoms. Finally, we trained an XGBoost model to achieve a sensitivity of 92.5% and a specificity of 97.9% in discriminating COVID-19 patients from influenza patients. We demonstrated that computational methods trained on large clinical datasets could yield ever more accurate COVID-19 diagnostic models to mitigate the impact of lack of testing. We also presented previously unknown COVID-19 clinical variable correlations and clinical subgroups.
Exploration on the Malaysian adolescents’ understanding towards concepts of physical activity, perceived facilitators and barriers in practising an active lifestyle
Authors: Sharif Ishak Sharifah Intan Zainun , Chin Yit Siew , Mohd Taib Mohd Nasir , Mohd Shariff Zalilah 
Published: June 2020

PurposeThis study aimed to explore the understanding of Malaysian adolescents towards concept of physical activity (PA) and their perceived facilitators and barriers in practising an active lifestyle.Design/methodology/approachUsing a quota sampling method, a total of 12 focus group discussions (FGDs) were performed at two secondary schools, which were randomly selected in Selangor. This study involved 72 adolescents (males = 51.4%, females = 48.6%) aged 13–14 years. Based on ethnicity, there was an equal number of Malay, Chinese and Indian participants (n = 24, 33.3%). For analysing the outcome from the FGDs, thematic analysis was applied.FindingsThe adolescents perceived exercise and PA as structured games. They perceived that exercise could have positive effects on the body, appearance and health, and PA as a daily routine. Common differences between exercise and PA were based on frequency, intensity, energy and venue. Perceived facilitators in practising an active lifestyle include concern about body or health, have companions, familial or peer influence, availability of facilities in the neighbourhood and have scheduled time for exercise. Time constraint, no motivation, physically unwell or tired, no companion, security issue at playground or exercise facilities or venue, and weather were mentioned as barriers in practising an active lifestyle.Originality/valueThis study contributed to an improved understanding of the adolescents’ concept of PA, as well as their perceived facilitators and barriers in practising an active lifestyle. The study suggested that health intervention should embrace a way of promoting the immediate advantages of practicing an active lifestyle in order to reinforce the importance of an active lifestyle among adolescents. Furthermore, future intervention should emphasise on educating the adolescents on ways to cope with environmental barriers when practicing an active lifestyle.