bluuebunny/crossref_metadata_2025_split huggingface dataset:
WMHs AND HOMOCYSTEINE LEVELS AS CANDIDATE BIOMARKER FOR COGNITIVE IMPAIRMENT
Authors: Misra Vivek , Krishnamoorthy Ennapadam S. , Balaji Shruti , Kuppan Jayandrakumar , Nagarajan K 
Published: May 2020

ABSTRACTThe aim of this pilot study was to test the hypotheses that a) WMHs would be a biological marker in South Indian patients who present with either cognitive impairment, dementia or depression and b) presence of WMHs would be related to other blood biochemical markers. A significant positive correlation was present between temporal WMHs and increased homocysteine levels. A significant inverse correlation was obtained between MMSE scores and frontal caps. Association between temporal WMHs and elevated plasma homocysteine levels implies that this can serve as a biological marker for cognitive impairment and possibly for therapy.
Multivariate Prediction Network Model for epidemic progression to study the effects of lockdown time and coverage on a closed community on theoretical and real scenarios of COVID-19
Authors: Abramov Dimitri Marques , Junior Saint-Clair Gomes 
Published: May 2020

ABSTRACTThe aim of this study was to develop a realistic network model to predict the relationship between lockdown duration and coverage in controlling the progression of the incidence curve of an epidemic with the characteristics of COVID-19 in two scenarios (1) a closed and non-immune population, and (2) a real scenario from State of Rio de Janeiro from May 6th 2020.Effects of lockdown time and rate on the progression of an epidemic incidence curve in a virtual population of 10 thousand subjects. Predictor variables were reproductive values established in the most recent literature (R0 =2.7 and 5.7, and Re = 1.28 from Rio de Janeiro State at May 6th), without lockdown and with coverages of 25%, 50%, and 90% for 21, 35, 70, and 140 days in up to 13 different scenarios for each R0/Re, where individuals remained infected and transmitters for 14 days. We estimated model validity in theoretical and real scenarios respectively by applying an exponential model on the incidence curve with no lockdown with growth rate coefficient observed in realistic scenarios, and (2) fitting real data series from RJ upon simulated data, respectively.For R0=5.7, the flattening of the curve occurs only with long lockdown periods (70 and 140 days) with a 90% coverage. For R0=2.7, coverages of 25 and 50% also result in curve flattening and reduction of total cases, provided they occur for a long period (70 days or more). For realistic scenario in Rio de Janeiro, lockdowns +25% or more from May 6th during 140 days showed expressive flattening and number of COVID cases two to five times lower. If a more intense coverage lockdown (about +25 to +50% as much as the current one) will be implemented until June 6th during at least 70 days, it is still possible reduce nearly 40-50% the impact of pandemy in state of Rio de Janeiro.These data corroborate the importance of lockdown duration regardless of virus transmission and sometimes of intensity of coverage, either in realistic or theoretical scenarios of COVID-10 epidemics. Even later, the improvement of lockdown coverage can be effective to minimize the impact of epidemic.
Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States
Authors: Liang Donghai , Shi Liuhua , Zhao Jingxuan , Liu Pengfei , Schwartz Joel , Gao Song , Sarnat Jeremy , Liu Yang , Ebelt Stefanie , Scovronick Noah , Chang Howard H 
Published: May 2020

AbstractBackgroundThe novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis.MethodsWe conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5 and O3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors.Results1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM2.5 or O3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM2.5 (3.4 ug/m3) was marginally associated with 10.8% (95% CI: −1.1% to 24.1%) increase in COVID-19 mortality rate.Discussions and ConclusionsLong-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of longterm PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.
Training deep learning algorithms with weakly labeled pneumonia chest X-ray data for COVID-19 detection
Authors: Rajaraman Sivaramakrishnan , Antani Sameer 
Published: May 2020

AbstractThe novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused a pandemic resulting in over 2.7 million infected individuals and over 190,000 deaths and growing. Respiratory disorders in COVID-19 caused by the virus commonly present as viral pneumonia-like opacities in chest X-ray images which are used as an adjunct to the reverse transcription-polymerase chain reaction test for confirmation and evaluating disease progression. The surge places high demand on medical services including radiology expertise. However, there is a dearth of sufficient training data for developing image-based automated decision support tools to alleviate radiological burden. We address this insufficiency by expanding training data distribution through use of weakly-labeled images pooled from publicly available CXR collections showing pneumonia-related opacities. We use the images in a stage-wise, strategic approach and train convolutional neural network-based algorithms to detect COVID-19 infections in CXRs. It is observed that weakly-labeled data augmentation improves performance with the baseline test data compared to non-augmented training by expanding the learned feature space to encompass variability in the unseen test distribution to enhance inter-class discrimination, reduce intra-class similarity and generalization error. Augmentation with COVID-19 CXRs from individual collections significantly improves performance compared to baseline non-augmented training and weakly-labeled augmentation toward detecting COVID-19 like viral pneumonia in the publicly available COVID-19 CXR collections. This underscores the fact that COVID-19 CXRs have a distinct pattern and hence distribution, unlike non-COVID-19 viral pneumonia and other infectious agents.
Asthma and COVID-19 in children – a systematic review and call for data
Authors: Castro-Rodriguez Jose A. , Forno Erick 
Published: May 2020

ABSTRACTRationaleWhether asthma constitutes a risk factor for COVID-19 is unclear.MethodsWe performed a systematic literature search in three stages: First, we reviewed PubMed, EMBASE and CINAHL for systematic reviews of SARS-CoC-2 and COVID-19 in pediatric populations, and reviewed their primary articles; next, we searched PubMed for studies on COVID-19 or SARS-CoV-2 and asthma/wheeze, and evaluated whether the resulting studies included pediatric populations; lastly, we repeated the second search in BioRxiv.org and MedRxiv.org to find pre-prints that may have information on pediatric asthma.ResultsIn the first search, eight systematic reviews were found, of which five were done in pediatric population; after reviewing 67 primary studies we found no data on pediatric asthma as a comorbidity for COVID-19. In the second search, we found 25 results in PubMed, of which five reported asthma in adults, but none included data on children. In the third search, 14 pre-prints in MedRxiv were identified with data on asthma, but again none with pediatric data. We found only one report by the U.S. CDC stating that 40/345 (~11.5%) children with data on chronic conditions had “chronic lung diseases including asthma”.ConclusionThere is scarcely any data on whether childhood asthma (or other pediatric respiratory diseases) constitute risk factors for SARS-CoV-2 infection or COVID-19 severity. Studies are needed that go beyond counting the number of cases in the pediatric age range.
The date predicted 200.000 cases of Covid-19 in Spain using SutteARIMA
Authors: Ahmar Ansari Saleh , del Val Eva Boj 
Published: May 2020

AbstractThe aim of this study is predicted 200.000 cases of Covid-19 in Spain. Covid-19 Spanish confirmed data obtained from Worldometer from 01 March 2020 – 17 April 2020. The data from 01 March 2020 – 10 April 2020 using to fitting with data from 11 April – 17 April 2020. For the evaluation of the forecasting accuracy measures, we use mean absolute percentage error (MAPE). Based on the results of SutteARIMA fitting data, the accuracy of SutteARIMA for the period 11 April 2020 - 17 April 2020 is 0.61% and we forecast 20.000 confirmed cases of Spain by the WHO situation report day 90/91 which is 19 April 2020 / 20 April 2020.
Trends in Perception of COVID-19 in Polish Internet
Authors: Jarynowski Andrzej , Wójta-Kempa Monika , Belik Vitaly 
Published: May 2020

ABSTRACTINTRODUCTIONDue to the spread of SARS CoV-2 virus responsible for COVID-19 disease, there is an urgent need to analyse COVID-2019 epidemic perception in Poland. This study aims to investigate social perception of coronavirus in the Internet media during the epidemic. It is a signal report highlighting the main issues in public perception and medical commutation in real time.METHODSWe study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet on platforms: Google, Twitter, YouTube, Wikipedia and electronic media represented by Event Registry, from January 2020 to 29.04.2020 (before and after official introduction to Poland on 04.03.20). We present trend analysis with a support of natural language processing techniques.RESULTSWe identified seven temporal major clusters of interest on the topic COVID-2019: 1) Chinese, 2) Italian, 3) Waiting, 4) Mitigations, 5) Social distancing and Lockdown, 6) Anti-crisis shield, 7) Restrictions releasing. There was an exponential increase of interest when the Polish government “declared war against disease” around 11/12.03.20 with a massive mitigation program. Later on, there was a decay in interest with additional phases related to social distancing and an anti-crisis legislation act with local peaks. We have found that declarations of mitigation strategies by the Polish prime minister or the minister of health gathered the highest attention of Internet users. So enacted or in force events do not affect interest to such extent. Traditional news agencies were ahead of social media (mainly Twitter) in dissemination of information. We have observed very weak or even negative correlations between a colloquial searching term ‘antiviral mask’ in Google, encyclopaedic definition in Wikipedia “SARS-CoV-2” as well official incidence series, implying different mechanisms governing the search for knowledge, panic related behaviour and actual risk of acquiring infection.CONCLUSIONSTraditional and social media do not only reflect reality, but also create it. Risk perception in Poland is unrelated to actual physical risk of acquiring COVID-19. As traditional media are ahead of social media in time, we advise to choose traditional news media for a quick dissemination of information, however for a greater impact, social media should be used. Otherwise public information campaigns might have less impact on society than expected.
A mathematically rigorous assessment of the efficiency of quarantining and contact tracing in curbing the COVID-19 epidemic
Authors: Lambert Amaury 
Published: May 2020

AbstractIn our model of the COVID-19 epidemic, infected individuals can be of four types, according whether they are asymptomatic (A) or symptomatic (I), and use a contact tracing mobile phone app (Y) or not (N). We denote by f the fraction of A’s, by y the fraction of Y’s and by R0 the average number of secondary infections from a random infected individual.We investigate the effect of non-electronic interventions (voluntary isolation upon symptom onset, quarantining private contacts) and of electronic interventions (contact tracing thanks to the app), depending on the willingness to quarantine, parameterized by four cooperating probabilities.For a given ‘effective’ R0 obtained with non-electronic interventions, we use nonnegative matrix theory and stopping line techniques to characterize mathematically the minimal fraction y0 of app users needed to curb the epidemic. We show that under a wide range of scenarios, the threshold y0 as a function of R0 rises steeply from 0 at R0= 1 to prohibitively large values (of the order of 60 – 70% up) whenever R0 is above 1.3. Our results show that moderate rates of adoption of a contact tracing app can reduce R0 but are by no means sufficient to reduce it below 1 unless it is already very close to 1 thanks to non-electronic interventions.
Do maternal intrauterine environmental influences that lower offspring birthweight causally increase offspring cardiometabolic risk factors in later life? A Mendelian randomization study of 45,849 genotyped parent offspring pairs in the HUNT study
Authors: Moen Gunn-Helen , Brumpton Ben , Willer Cristen , Åsvold Bjørn Olav , Birkeland Kåre , Neale Michael C , Freathy Rachel M , Smith George Davey , Lawlor Deborah A , Kirkpatrick Robert M , Warrington Nicole M , Evans David M 
Published: May 2020

AbstractIntroductionThere is a robust and well-documented observational relationship between lower birthweight and higher risk of cardiometabolic disease in later life. The Developmental Origins of Health and Disease (DOHaD) hypothesis posits that adverse environmental factors in utero or in the early years of life result in increased future risk of cardiometabolic disease. Our aim was to investigate whether there was evidence for causal effects of the intrauterine environment, as proxied by maternal single nucleotide polymorphisms (SNPs) that influence offspring birthweight independent of offspring genotype, on offspring cardiometabolic risk factors such as blood pressure, non-fasting glucose, body mass index (BMI), and lipid levels.MethodsWe investigated whether a genetic risk score of maternal SNPs associated with offspring birthweight was also associated with offspring cardiometabolic risk factors, after controlling for offspring genotypes at the same loci, in up to 26,057 mother-offspring pairs from the Nord-Trøndelag Health (HUNT) Study. We also conducted similar analyses in 19,792 father-offspring pairs from the same study to investigate whether there was evidence that any such causal effects operated through the postnatal, rather than the intrauterine environment. To take account of the considerable cryptic relatedness in HUNT, we implemented a computationally efficient genetic linear mixed model using the OpenMx software package to perform our analyses.ResultsWe found little evidence for a maternal genetic effect of birthweight associated variants on offspring cardiometabolic risk factors after adjusting for offspring genotypes at the same loci. Likewise, we found little evidence for paternal genetic effects on offspring cardiometabolic risk factors performing similar analyses in father-offspring pairs. In contrast, offspring genetic risk scores of birthweight associated variants were strongly related to many cardiometabolic risk factors, even after conditioning on maternal genotypes at the same loci.ConclusionOur results suggest that the maternal intrauterine environment, as proxied by maternal SNPs that influence offspring birthweight, is unlikely to be a major determinant of adverse cardiometabolic outcomes in population based samples of individuals. In contrast, genetic pleiotropy appears to explain some of the observational relationship between offspring birthweight and future cardiometabolic risk.
Genetic and environmental determinants of variation in the plasma lipidome of older Australian twins
Authors: Wong Matthew W.K. , Thalamuthu Anbupalam , Braidy Nady , Mather Karen A. , Liu Yue , Ciobanu Liliana , Baune Bernhardt T. , Armstrong Nicola J. , Kwok John , Schofield Peter R. , Wright Margaret J. , Ames David , Pickford Russell , Lee Teresa , Poljak Anne , Sachdev Perminder S. 
Published: May 2020

AbstractThe critical role of blood lipids in a broad range of health and disease states is well recognised, while an understanding of the complex genetic regulation of lipid homeostasis is emerging. Traditional blood lipids (LDL-C, HDL-C and triglycerides) are known to be substantially regulated by genetic variation. Less well explored is the interplay of genetics and environment within the broader blood lipidome. Here we use the twin model to examine heritability of the plasma lipidome among healthy older aged twins and explore gene expression and epigenetic (DNA methylation) associations of these lipids. Heritability of 209 plasma lipids quantified by liquid chromatography coupled mass spectrometry (LC-MS) was assessed in 75 monozygotic and 55 dizygotic twin pairs enrolled in the Older Australian Twins Study (OATS), aged 69-93 years. Only 27/209 lipids (13.3%) were significantly heritable under the classical ACE twin model (h2= 0.28-0.59). Ceramides (Cer) and triglycerides (TG) were most heritable, while sphingomyelins (SM) and most phospholipids, especially lysophospholipids, were not significantly heritable. Lipid levels correlated with 3731 transcripts. Relative to non-significantly heritable TGs, heritable TGs had a greater number of associations with gene transcripts, which were not directly associated with lipid metabolism, but with immune function, signalling and transcriptional regulation. Genome-wide average DNA methylation (GWAM) levels accounted for a proportion of variability in some non-heritable lipids, especially lysophosphatidylcholine (LPC). We found a complex interplay of genetic and environmental influences on the ageing plasma lipidome, with most of the variation controlled by unique environmental influences.
Alternative Lengthening of Telomeres is not synonymous with mutations in ATRX/DAXX
Authors: de Nonneville Alexandre , Reddel Roger R. 
Published: May 2020

AbstractThe PCAWG Consortium has recently released an unprecedented set of tumor whole genome sequence (WGS) data from 2,658 cancer patients across 38 different primary tumor sites1. WGS is able to document the quantity and distribution of telomeric repeats2. In one of the papers analyzing the PCAWG dataset, Sieverlinget al.3confirmed previous data4indicating that tumors with truncating ATRX or DAXX alterations, referred to as ATRX/DAXXtrunc, have an aberrant telomere variant repeat (TVR) distribution. By regarding these mutations,vs.TERT modifications (TERTmod; i.e. promoter mutations +/− amplifications +/− structural variations), as indicators of Alternative Lengthening of Telomeres (ALT)vs.telomerase, they built a random forest classifier for ALT-probability, and then associated genomic characteristics with the putative Telomere Maintenance Mechanism (TMM)3. However, we show here that equating ATRX/DAXXtruncand TERTmodwith ALT and telomerase, respectively, results in TMM predictions which correlate poorly with TMM assay data. ATRX/DAXXtruncmutations are heterogeneously distributed in ALT-positive (ALT+) tumors of different types, as are TERTmodin telomerase-positive tumors4. Although these mutations are strongly associated with TMM, most tumors do not harbor them, making them an inadequate basis for building a classifier in a large-scale pan-cancer study4–7. Here, we provide a new analysis of the PCAWG data, based on C-circle assay (CCA)8that is available for a subset of these tumors4,9,10. We show that the Sieverlinget al.score overestimates the proportion of ALT associated with ATRX/DAXXtruncand misclassifies ALT tumors when these mutations are absent. We also show some TVR correlate with ATRX/DAXXtruncmutations, regardless of TMM. Finally, we propose a new classifier to identify ALT tumors in the PCAWG cohort.
“A Proteogenomic workflow reveals distinct molecular phenotypes related to breast cancer appearance”
Authors: De Marchi Tommaso , Pyl Paul Theodor , Sjöstrom Martin , Klasson Stina , Sartor Hanna , Malmström Johan , Malmström Lars , Niméus Emma 
Published: May 2020

AbstractProteogenomics approaches have enabled the generation of extensive information levels when compared to single omics technology studies, although burdened by massive experimental efforts. Here, we developed four improvements of a data independent acquisition mass spectrometry proteogenomics workflow to reveal distinct molecular phenotypes related to breast cancer appearance. We confirm mutational processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Our analyses also validated previously established enrichments of estrogen receptor-dependent molecular features relating to transcription factor expression, and provided evidence for molecular differences related to the presence of mammographic appearances in spiculated tumors. In addition, several transcript-protein pairs displayed radically different abundance correlations depending on the overall clinical and pathological properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant sample groups, and that these protein networks influence both cancer biology as well as the abundance of potential biomarkers and drug targets.