bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sunlight exposure exerts immunomodulatory effects to reduce multiple sclerosis severity
Authors: Ostkamp Patrick , Salmen Anke , Pignolet Béatrice , Görlich Dennis , Andlauer Till F. M. , Schulte-Mecklenbeck Andreas , Gonzalez-Escamilla Gabriel , Bucciarelli Florence , Gennero Isabelle , Breuer Johanna , Antony Gisela , Schneider-Hohendorf Tilman , Mykicki Nadine , Bayas Antonios , Bergh Florian Then , Bittner Stefan , Hartung Hans-Peter , Friese Manuel A. , Linker Ralf A. , Luessi Felix , Lehmann-Horn Klaus , Mühlau Mark , Paul Friedemann , Stangel Martin , Tackenberg Björn , Tumani Hayrettin , Warnke Clemens , Weber Frank , Wildemann Brigitte , Zettl Uwe K. , Ziemann Ulf , Müller-Myhsok Bertram , Kümpfel Tania , Klotz Luisa , Meuth Sven G. , Zipp Frauke , Hemmer Bernhard , Hohlfeld Reinhard , Brassat David , Gold Ralf , Gross Catharina C. , Lukas Carsten , Groppa Sergiu , Loser Karin , Wiendl Heinz , Schwab Nicholas 
Published: July 2020

AbstractBackgroundMultiple sclerosis (MS) disease risk is associated with reduced sun exposure. This study assessed the relationship between measures of sun-exposure (vitamin D (vitD), latitude) and MS disease severity, the mechanisms of action, and effect-modification by medication and sun-sensitivity associated MC1R variants.MethodsTwo multi-center cohort studies (nNationMS=946, nBIONAT=991). Outcomes were the multiple sclerosis severity score (MSSS) and the number of Gd-enhancing lesion (GELs). RNAseq of four immune cell populations before and after UV-phototherapy of five MS patients.ResultsHigh serum vitD was associated with reduced MSSS (PNationMS=0.021; PBIONAT=0.007) and reduced risk for disease aggravation (PNationMS=0.032). Low latitude was associated with higher vitD, lower MSSS (PNationMS=0.018), fewer GELs (PNationMS=0.030) and reduced risk for aggravation (PNationMS=0.044). The influence of latitude on disability seemed to be lacking in the subgroup of interferon-β treated patients (interaction-PBIONAT=0.042, interaction-PNationMS=0.053). In genetic analyses, for carriers of MC1R:rs1805008(T), who reported increased sensitivity towards sunlight (PNationMS=0.038), the relationship between latitude und the number of GELs was inversed (PNationMS=0.001). Phototherapy induced a vitD and type I interferon signature that was most apparent in the transcriptome of monocytes (P=1×10−6).ConclusionVitD is associated with reduced MS severity and disease aggravation. This is likely driven by sun-exposure, as latitude also correlated with disability and serum vitD. However, sun-exposure might be detrimental for sun-sensitive patients. A direct induction of type I interferons through sun-exposure could explain a reduced effect of latitude in interferon-β treated patients. This could also explain opposite effects of sun-exposure in MS and the type I interferon and sun-sensitivity-associated disease Lupus.
Optimal Testing Strategy for the Identification of COVID-19 Infections
Authors: Chatzimanolakis Michail , Weber Pascal , Arampatzis George , Wälchli Daniel , Kičić Ivica , Karnakov Petr , Papadimitriou Costas , Koumoutsakos Petros 
Published: July 2020

The systematic identification of infectious, yet unreported, individuals is critical for the containment of the COVID-19 pandemic. We present a strategy for identifying the location, timing and extent of testing that maximizes information gain for such infections. The optimal testing strategy relies on Bayesian experimental design and forecasting epidemic models that account for time dependent interventions. It is applicable at the onset and spreading of the epidemic and can forewarn for a possible recurrence of the disease after relaxation of interventions. We examine its application in Switzerland and show that it can provide timely and systematic guidance for the effective identification of infectious individuals with finite testing resources. The methodology and the open source code are readily adaptable to countries around the world.We present a strategy for the optimal allocation of testing resources in order to detect COVID-19 infections in a country’s population.
Screening Diabetic Retinopathy Using an Automated Retinal Image Analysis System in Mexico: Independent and Assistive use Cases
Authors: Noriega Alejandro , Meizner Daniela , Camacho Dalia , Enciso Jennifer , Quiroz-Mercado Hugo , Morales-Canton Virgilio , Almaatouq Abdullah , Pentland Alex 
Published: July 2020

AbstractBackgroundThe automated screening of patients at risk of developing diabetic retinopathy (DR) represents an opportunity to improve their mid-term outcome, and lower the public expenditure associated with direct and indirect costs of common sight-threatening complications of diabetes.ObjectiveIn the present study, we aim at developing and evaluating the performance of an automated deep learning–based system to classify retinal fundus images from international and Mexican patients, as referable and non-referable DR cases. In particular, we study the performance of the automated retina image analysis (ARIA) system under an independent scheme (i.e. only ARIA screening) and twoassistiveschemes (i.e., hybrid ARIA + ophthalmologist screening), using a web-based platform for remote image analysis.MethodsWe ran a randomized controlled experiment where 17 ophthalmologists were asked to classify a series of retinal fundus images under three different conditions: 1) screening the fundus image by themselves (solo), 2) screening the fundus image after being exposed to the opinion of the ARIA system (ARIA answer), and 3) screening the fundus image after being exposed to the opinion of the ARIA system, as well as its level of confidence and an attention map highlighting the most important areas of interest in the image according to the ARIA system (ARIA explanation). The ophthalmologists’ opinion in each condition and the opinion of the ARIA system were compared against agold standardgenerated by consulting and aggregating the opinion of three retina specialists for each fundus image.ResultsThe ARIA system was able to classify referable vs. non-referable cases with an area under the Receiver Operating Characteristic curve (AUROC), sensitivity, and specificity of 98%, 95.1% and 91.5% respectively, for international patient-cases; and an AUROC, sensitivity, and specificity of 98.3%, 95.2%, and 90% respectively for Mexican patient-cases. The results achieved on Mexican patient-cases outperformed the average performance of the 17 ophthalmologist participants of the study. We also find that the ARIA system can be useful as an assistive tool, as significant sensitivity improvements were observed in the experimental condition where participants were exposed to the answer of theARIA systemas a second opinion (93.3%), compared to the sensitivity of the condition where participants assessed the images independently (87.3%).ConclusionsThese results demonstrate that both use cases of ARIA systems,independentandassistive, present a substantial opportunity for Latin American countries like Mexico towards an efficient expansion of monitoring capacity for the early detection of diabetes-related blindness.
Application and Reliability of Arm Use Intensities in the Free-Living Environment for Manual Wheelchair Users
Authors: Goodwin Brianna M. , Jahanian Omid , Van Straaten Meegan G. , Fortune Emma , Madansingh Stefan I. , Cloud-Biebl Beth A. , Zhao Kristin D. , Morrow Melissa M. 
Published: July 2020

AbstractArm use in individuals with spinal cord injury who use manual wheelchairs (MWC) is complex, characterized by a combination of overuse and a sedentary lifestyle. This study aimed to calculate arm use intensity levels for MWC users, describe the percentage of daily wear time MWC users and able-bodied individuals spend in each arm use intensity level, and test the reliabilities of the measurements for both MWC users and able-bodied individuals.MWC users wore two inertial measurement units (IMUs) on their bilateral upper arms while performing six MWC-based activities in-lab. Video data were recorded and each second was coded as active or stationary. Acceleration-based signal magnitude area (SMA) ranges were defined for stationary, low, mid, and high arm use intensity levels. IMU data were also collected in the free-living environments for MWC users and able-bodied individuals for four days (3 weekdays and 1 weekend day). The SMA levels were applied to the free-living data from the dominant arm and the percentage of time spent in each level was calculated. The required number of days to achieve moderate, good, and excellent reliabilities was calculated.Eight adult MWC users with SCI participated in the in-lab data collection and SMA arm use intensity levels were defined as, stationary: ⩽ 0.67g, low: 0.671 – 3.27g, mid: 3.271 – 5.87, and high: > 5.871. Six MWC users and 15 able-bodied individuals completed the free-living data collection. The dominant arm of both MWC users and able-bodied individuals was stationary for the majority of the day. The reliability analysis indicated that at least five and eight days of data are needed from MWC users and able-bodied individuals, respectively, to achieve reliable representation of their overall daily arm use intensities throughout a week.Future research is needed to understand the recovery time associated with stationary arm use and if it differs between MWC users and matched able-bodied individuals. At least five days of data should be collected when utilizing these methods for MWC users. The methods presented here will contribute to understanding the mechanisms which cause increased shoulder pain and pathology for MWC users.
Factors Associated with COVID-19 Mitigation Behavior among US Adults
Authors: Lemke Debra C. , Lemke Klaus W. 
Published: July 2020

AbstractIn early 2020, the CDC issued guidelines for personal COVID-19 mitigation behavior, such as mask-wearing, hand-washing, and social-distancing. We examine individual socio-behavioral factors that potentially predict mitigation compliance using public data. Our analysis finds that pandemic prompted strong mitigation behavior by adults, especially among females, non-whites, urban dwellers, and the psychological unwell. Other positive predictors were post-secondary education and higher income. Health symptoms and clinical risk factors did not predict increased mitigation practices, nor did age 65+ and proximity to infected persons. Our study findings are congruent with a report that pointed to a lack of increased pandemic mitigation practices in households with confirmed infections and health risks. We also point to lower levels of psychological resilience, lower socio-economic status, and non-urban location as potential explanatory factors for lack of mitigation behavior. Understanding what factors are associated with mitigation behavior will be important for policy makers in their efforts to curb the COVID-19 pandemic.
A data-driven metapopulation model for the Belgian COVID-19 epidemic: assessing the impact of lockdown and exit strategies
Authors: Coletti Pietro , Libin Pieter , Petrof Oana , Willem Lander , Abrams Steven , Herzog Sereina A. , Faes Christel , Wambua James , Kuylen Elise ,   COVID-19 team the SIMID, Beutels Philippe , Hens Niel 
Published: July 2020

AbstractBackgroundIn response to the ongoing COVID-19 pandemic, several countries adopted measures of social distancing to a different degree. For many countries, after successfully curbing the initial wave, lockdown measures were gradually lifted. In Belgium, such relief started on May 4th with phase 1, followed by several subsequent phases over the next few weeks.MethodsWe analysed the expected impact of relaxing stringent lockdown measures taken according to the phased Belgian exit strategy. We developed a stochastic, data-informed, meta-population model that accounts for mixing and mobility of the age-structured population of Belgium. The model is calibrated to daily hospitalization data and serological data and is able to reproduce the outbreak at the national level. We consider different scenarios for relieving the lockdown, quantified in terms of relative reductions in pre-pandemic social mixing and mobility. We validate our assumptions by making comparisons with social contact data collected during and after the lockdown.ResultsOur model is able to successfully describe the initial wave of COVID-19 in Belgium and identifies interactions during leisure/other activities as pivotal in the exit strategy. Indeed, we find a smaller impact of school re-openings as compared to restarting leisure activities and re-openings of work places. We also assess the impact of case isolation of new (suspected) infections, and find that it allows re-establishing relatively more social interactions while still ensuring epidemic control. Scenarios predicting a second wave of hospitalizations were not observed, suggesting that the per-contact probability of infection has changed with respect to the pre-lockdown period.ConclusionsCommunity contacts are found to be most influential, followed by professional contacts and school contacts, respectively, for an impending second wave of COVID-19. Regular re-assessment is crucial to adjust to evolving behavioral changes that can affect epidemic diffusion. In addition to social distancing, sufficient capacity for extensive testing and contact tracing is essential for successful mitigation.
Hospital-Based Donor Recruitment and Pre-Donation Serologic Testing for COVID-19 Convalescent Plasma
Authors: Balcerek Joanna , Trejo Evelin , Levine Kendall , Couey Paul , Kornberg Zoe V. , Rogine Camille , Young Charlotte , Li Jonathan , Shy Brian R. , Taylor Jordan E. , Bakhtary Sara , Friedlander Terence , Lynch Kara L. , Bern Caryn , Esensten Jonathan H. 
Published: July 2020

AbstractBackgroundMajor blood centers perform serologic testing on potential COVID-19 convalescent plasma donors retrospectively after blood donation. A hospital-based recruitment program for COVID-19 convalescent plasma (CCP) donors may be an efficient way to prospectively identify potential donors.Study Design and MethodsPatients who recovered from known or suspected COVID-19 were identified and recruited through medical record searches and public appeals. Participants were screened with a modified donor history questionnaire (DHQ), and if eligible, were consented and tested for SARS-CoV-2 antibodies (IgG and IgM). Participants who were positive for SARS-CoV-2 IgG were referred to a local blood center for convalescent plasma collection.ResultsOf 179 individuals screened, 128 completed serologic testing and 89 were referred for convalescent plasma donation to a local blood center (49.7% of those screened). IgG antibodies to SARS-CoV-2 were detected in 23/51 (45.1%) of participants with suspected COVID-19 and in 66/77 (85.7%) of participants with self-reported PCR-confirmed COVID-19. Testing was performed at a median of 38 days since last symptoms. Participant age positively correlated with anti-SARS-CoV-2 IgG and IgM levels. Time since last symptoms did not correlate with IgG or IgM levels. A wide range of SARS-CoV-2 IgG levels were observed.ConclusionA hospital based CCP donor recruitment program can prospectively identify potential CCP donors. Variability in SARS-CoV-2 IgG levels has implications for selection of CCP units for transfusion.
Confirmed and Unreported COVID-19-Like Illness Death Counts: An Assessment of Reporting Discrepancy
Authors: Ahamad Mazbahul G. , Tanin Fahian , Talukder Byomkesh 
Published: July 2020

AbstractObjectiveTo assess the reporting discrepancy between officially confirmed COVID-19 death counts and unreported COVID-19-like illness (CLI) death counts.Study DesignThe study is based on secondary time-series data.MethodsWe used publicly available data to explore the differences between confirmed COVID-19 death counts and deaths with probable COVID-19 symptoms in Bangladesh between March 8, 2020, and July 18, 2020. Both tabular analysis and statistical tests were performed.ResultsDuring the week ending May 9, 2020, the unreported CLI death count was higher than the confirmed COVID-19 death count; however, it was lower in the following weeks. On average, unreported CLI death counts were almost equal to the confirmed COVID-19 death counts during the study period. However, the reporting authority neither considers CLI deaths nor adjusts for potential seasonal influenza-like illness or other related deaths, which might produce incomplete and unreliable COVID-19 data and respective mortality rates.ConclusionsDeaths with probable COVID-19 symptoms needs to be included in provisional death counts in order to estimate an accurate COVID-19 mortality rate and to offer data-driven pandemic response strategies. An urgent initiative is needed to prepare a comprehensive guideline for reporting COVID-19 deaths.
Acute Shortage Ventilator
Authors: Akerib D. S. , Ames A. , Breidenbach M. , Bressack M. , Breur P. A. , Charles E. , Gaba D. , Herbst R. , Ignarra C. M. , Luitz S. , Miller E. H. , Mong B. , Shutt T. A. , Wittgen M. 
Published: July 2020

AbstractWe have implemented an “Acute Shortage Ventilator” (ASV) motivated by the COVID-19 pandemic and the possibility of severe ventilator shortages in the near future. The unit cost per ventilator is less than $400 US excluding the patient circuit parts. The ASV mechanically compresses a self-inflating bag resuscitator, uses a modified patient circuit, and is commanded by a microcontroller and an optional laptop. It operates in both Volume-Controlled Assist-Control mode and a Pressure-Controlled Assist-Control mode. It has been tested using an artificial lung against the EURS guidelines. The key design goals were to develop a simple device with high performance for short-term use, made primarily from common hospital parts and generally-available non-medical components, and at low cost and ease in manufacturing.
Linking Outdoor Air Temperature and SARS-CoV-2 Transmission in the US Using a Two Parameter Transmission Model
Authors: Newell Ty 
Published: July 2020

AbstractOutdoor temperature lower than 50F and greater than 70F is shown to nearly double the transmission efficiency of the SARS-CoV-2 virus. Outdoor temperature is an important factor behind the current surge in US Covid-19 cases. Correlation of northern state infection data and outdoor temperatures is used to identify the change in disease transmission efficiency as northern states passed through the lower temperature bound (50F) in spring, and more recently transitioned to temperatures above the higher bound (70F). At current disease transmission efficiency levels, social distancing must be increased above a UMD Social Distance Index (SDI) level of 36 to stop the accelerated increase of daily infection cases. At current disease transmission efficiency (G=0.19) and SDI of 33, the US will approach 150,000 infections per day in September before declining as average US temperature falls below 70F.A primary reason for enhanced disease transmission below 50F and above 70F is attributed to inadequate indoor ventilation. Swing season occurs when outdoor temperatures are between 50F and 70F, and is the time of year when homes and buildings are opened to the outdoors. Increased fresh air ventilation (greater than 40cfm per person), improved air filtration (MERV11 and greater filters), and UVGI (Ultraviolet Germicidal Irradiation, 0.02WUV per cfm airflow) coupled with wearing face masks, 6ft distancing and surface sanitation are estimated to reduce indoor disease transmission probability to a third of the transmission probability resulting from standard building ventilation practice.
Computer vision-based assessment of motor functioning in schizophrenia: Use of smartphones for remote measurement of schizophrenia symptomatology
Authors: Abbas Anzar , Yadav Vijay , Smith Emma , Ramjas Elizabeth , Rutter Sarah B. , Benavides Caridad , Koesmahargyo Vidya , Zhang Li , Guan Lei , Rosenfield Paul , Perez-Rodriguez Mercedes , Galatzer-Levy Isaac R. 
Published: July 2020

AbstractIntroductionMotor abnormalities have been shown to be a distinct component of schizophrenia symptomatology. However, objective and scalable methods for assessment of motor functioning in schizophrenia are lacking. Advancements in machine learning-based digital tools have allowed for automated and remote ‘digital phenotyping’ of disease symptomatology. Here, we assess the performance of a computer vision-based assessment of motor functioning as a characteristic of schizophrenia using video data collected remotely through smartphones.Methods18 patients with schizophrenia and 9 healthy controls were asked to remotely participate in smartphone-based assessments daily for 14 days. Video recorded from the smartphone front-facing camera during these assessments was used to quantify head movement through a pre-trained computer vision model. The ability of head movement measurements to distinguish between patients and healthy controls as well as their relationship to schizophrenia symptom severity as measured through traditional clinical scores was assessed.ResultsA logistic regression demonstrated that head movement was a significant predictor of schizophrenia diagnosis (p < 0.05). Linear regression between head movement and clinical scores of schizophrenia symptom severity showed that head movement has a negative relationship with schizophrenia symptom severity (p < 0.05), primarily with negative symptoms of schizophrenia.ConclusionsRemote, smartphone-based assessments were able to capture meaningful visual behavior for computer vision-based objective measurement of head movement. The measurements of head movement acquired were able to accurately classify schizophrenia diagnosis and quantify symptom severity in patients with schizophrenia.
SARS-CoV-2 antibody prevalence in health care workers: Preliminary report of a single center study
Authors: Brant-Zawadzki Michael , Fridman Deborah , Robinson Philip A. , Zahn Matthew , German Randy , Breit Marcus , Hara Junko 
Published: July 2020

AbstractSARS-CoV-2 has driven a pandemic crisis. Serological surveys have been conducted to establish prevalence for covid-19 antibody in various cohorts and communities. However, the prevalence among healthcare workers is still being analyzed. The present study reports on initial sero-surveillance conducted on healthcare workers at a regional hospital system in Orange County, California, during May and June, 2020.Study participants were recruited from the entire hospital employee workforce and the independent medical staff. Data were collected for job title, location, covid-19 symptoms, a PCR test history, travel record since January 2020, and existence of household contacts with covid-19. A blood sample was collected from each subject for serum analysis for IgG antibodies to SARS- CoV-2.Of 3,013 tested individuals, a total 2,932 were included in the analysis due to some missing data. Observed prevalence of 1.06% (31 antibody positive cases), adjusted prevalence of 1.13% for test sensitivity and specificity were identified. Significant group differences between positive vs. negative were observed for age (z = 2.65, p = .008), race (p = .037), presence of fever (p < .001) and loss of smell (p < .001).Possible explanation for this low prevalence includes a relatively low local geographic community prevalence (∼4.4%) at the time of testing, the hospital’s timely procurement of personal protective equipment, rigorous employee education, patient triage and treatment protocol development and implementation. In addition, possible greater presence of cross- reactive adaptive T cell mediated immunity in healthcare workers vs. the general population may have contributed. Determining antibody prevalence in front-line workers, and duration of antibody presence may help stratify the workforce for risk, establish better health place policies and procedures, and potentially better mitigate transmission.