bluuebunny/crossref_metadata_2025_split huggingface dataset:
Individual Preparedness for Distant Wildfires and the Delta Variant in the United States: A Survey of 2,250 US Residents
Authors: Srikrishna Devabhaktuni 
Published: July 2021

AbstractBackgroundCOVID-19 virus travels in the air and collects indoors through tiny particles from exhaled breath, and remains a growing concern globally especially since case studies of vaccine breakthrough infections are being reported. Last year’s wildfires resulted in the worst air quality on record in the Western US due to toxic wildfire smoke (PM 2.5 pollution) traveling from distant wildfires and this year can potentially be even worse due to extremely dry conditions. Aerosol precautions such as high-filtration (Hi-Fi) masks and HEPA air purifiers are useful to effectively reduce inhalation of most of these toxic aerosols. Whereas the lack of fit or filtration in a mask or use of an air purifier of insufficient size (capacity) for the room can inadvertently render these precautions ineffective. Here we investigate the public’s concerns about wildfires and the COVID-19 variants (e.g. delta), their use of aerosol precautions, and whether these are being done in an effective manner.MethodsWe conducted a national survey of 2,250 US residents in order to understand public concerns about airborne threats and their usage of airborne (aerosol) precautions.ResultsWe find over 66% of US residents surveyed are worried about inhaling COVID-19 and its variants, and 52% are worried about toxic wildfire particles in the air. In the mountain and pacific regions the latter rises to 73%. Only a quarter are using masks with higher filtration and high level of fit (or Hi-Fi masks e.g. N95 or similar such as elastomeric N95 or KF94). Two-thirds are still using loose-fitting cloth or surgical masks. Just over 40% of respondents report using air purifiers at home, and of this group only 40% use it in their bedroom where they sleep. Of those using air purifiers, the majority said they chose the size of their air purifier based on “most popular” models, “recommendations,” or “reviews.” However, of those using air purifiers only 42% reported doing a calculation (or using a calculator) to estimate the right size of air purifier needed for the room they are using it in. Notably, a much higher percentage of people (than average) reported use of Hi-Fi masks and home air purifiers in certain occupations such as doctors, healthcare, first responders, public safety, engineering, military, and construction.ConclusionNational survey data suggests most US residents are worried about wildfire smoke and Covid variants (e.g. delta variant) but a majority are not prepared for it. Preparation with aerosol precautions will also be useful for future pandemics and national biodefense.
Emergence and spread of a B.1.1.28-derived P.6 lineage with Q675H and Q677H Spike mutations in Uruguay
Authors: Rego Natalia , Salazar Cecilia , Paz Mercedes , Costábile Alicia , Fajardo Alvaro , Ferrés Ignacio , Perbolianachis Paula , Fernández-Calero Tamara , Noya Veronica , Machado Matias R. , Arce Rodrigo , Arleo Mailen , Possi Tania , Reyes Natalia , Noel Bentancor María , Lizasoain Andrés , Bortagaray Viviana , Moller Ana , Chappos Odhille , Nin Nicolas , Hurtado Javier , Duquía Melissa , González Belén , Griffero Luciana , Méndez Mauricio , Pía Techera Ma , Zanetti Juan , Rivera Bernardina , Maidana Matías , Alonso Martina , Alonso Cecilia , Medina Julio , Albornoz Henry , Colina Rodney , Bello Gonzalo , Moreno Pilar , Moratorio Gonzalo , Iraola Gregorio , Spangenberg Lucía 
Published: July 2021

AbstractUruguay was able to control the viral dissemination during the first nine months of the SARS-CoV-2 pandemic. Unfortunately, towards the end of 2020, the number of daily new cases exponentially increased. Herein we analyzed the country-wide genetic diversity of SARS-CoV-2 between November, 2020 and April, 2021. Our findings identified that the most prevalent viral variant during late 2020 was a B.1.1.28 sublineage carrying mutations Q675H+Q677H in the viral Spike, now designated as lineage P.6. This new lineage P.6 probably arose around November 2020, in Montevideo, Uruguay’s capital department and rapidly spread to other Uruguayan departments, with evidence of further local transmission clusters, also spread sporadically to the USA and Spain. The Q675H and Q677H mutations are in the proximity of the polybasic cleavage site at the S1/S2 boundary and also arose independently in many SARS-CoV-2 lineages circulating worldwide. Although the lineage P.6 was replaced by the Variant of Concern (VOC) P.1 as the predominant viral strain in Uruguay since April 2021, the monitoring of the concurrent emergence of Q675H+Q677H in VOCs should be of worldwide interest.
COVID-19 outcomes in hospitalized puerperal, pregnant, and neither pregnant nor puerperal women: a population study
Authors: Serra Fabiano Elisei , Francisco Rossana Pulcineli Vieira , de Rossi Patricia , de Lourdes Brizot Maria , Rodrigues Agatha Sacramento 
Published: July 2021

AbstractObjectiveTo compare hospitalized reproductive age women with COVID-19 who were pregnant, puerperal, or neither one nor the other in terms of demographic and clinical characteristics and disease progression using Brazilian epidemiological data.MethodsA retrospective analysis of the records of the Information System of the Epidemiological Surveillance of Influenza of the Health Ministry of Brazil was performed. It included the data of female patients aged 10 to 49 years hospitalized because of severe COVID-19 disease (RT-PCR+ for SARS-CoV-2), from February17, 2020 to January 02, 2021.They were separated into 3 groups: pregnant, puerperal, and neither pregnant nor puerperal. General comparisons and then adjustments for confounding variables (propensity score matching [PSM]) were made, using demographic and clinical characteristics, disease progression (admission to the intensive care unit [ICU] and invasive or noninvasive ventilatory support), and outcome (cure or death). Deaths were analyzed in each group according to comorbidities, invasive or noninvasive ventilatory support, and admission to the ICU.ResultsAs many as 40,640 reproductive age women hospitalized for COVID-19 were identified: 3,372 were pregnant, 794 were puerperal, and 36,474 were neither pregnant nor puerperal. Groups were significantly different in terms of demographic data and comorbidities. Pregnant and puerperal women were less likely to be symptomatic than the women who were neither one nor the other. Pregnant women, however, had a higher frequency of cough, anosmia, and ageusia. Puerperal women had a worse prognosis than pregnant women with respect to admission to the ICU, invasive ventilatory support, and death.ConclusionPuerperal women were at a higher risk for serious outcomes (need for the ICU, need for invasive and noninvasive ventilatory support, and death) than pregnant women.
Can Vaccine Prioritization Reduce Disparities in Covid-19 Burden for Historically Marginalized Populations?
Authors: Rosenstrom Erik , Mele Jessica , Ivy Julie , Mayorga Maria , Patel Mehul , Lich Kristen Hassmiller , Johnson Karl , Delamater Paul , Keskinocak Pinar , Boyce Ross , Smith Raymond , Swann Julie L. 
Published: July 2021

1.ABSTRACTImportanceNationally stated goals for distributing SARS-CoV-2 vaccines included to reduce COVID-19 mortality, morbidity, and inequity using prioritization groups. However, the impact of these prioritization strategies is not well understood, particularly their effect on health inequity in COVID-19 burden for historically marginalized racial and ethnic populations.ObjectiveTo assess the impact of vaccination prioritization and operational strategies on disparities in COVID-19 burden among historically marginalized populations, and on mortality and morbidity by race and ethnicity.DesignWe use an agent-based simulation model of North Carolina to project SARS-CoV-2 infections and COVID-19-associated deaths (mortality), hospitalizations (morbidity), and cases over 18 months (7/1/2020-12/31/2021) with vaccine distribution beginning 12/13/2020 to frontline medical and people 75+, assuming initial uptake similar to influenza vaccine. We study two-stage subsequent prioritization including essential workers (“essential”), adults 65+ (“age”), adults with high-risk health conditions, HMPs, or people in low income tracts, with eligibility for the general population in the third stage. For age-essential and essential-age strategies, we also simulated maximal uptake (100% for HMP or 100% for everyone), and we allowed for distribution to susceptible-only people.ResultsPrioritizing Age then Essential had the largest impact on mortality (2.5% reduction from no prioritization); Essential then Age had the lowest morbidity and reduced infections (4.2% further than Age-Essential) without significantly impacting mortality. Under each prioritization scenario, the age-adjusted mortality burden for HMPs is higher (e.g., 33.3-34.1% higher for the Black population, 13.3%-17.0% for the Hispanic population) compared to the White population, and the gap grew under some prioritizations. In the Age-Essential strategy, the burden on HMPs decreases only when uptake is increased to 100% in HMPs. However, the Black population still had the highest mortality rate even with the Susceptible-Only distribution.Conclusions and RelevanceSimulation results show that prioritization strategies have differential impact on mortality, morbidity, and disparities overall and by race and ethnicity. If prioritization schemes were not paired with increased uptake in HMPs, disparities did not improve and could worsen. Although equity was one of the tenets of vaccine distribution, the vaccination strategies publicly outlined are insufficient to remove and may exacerbate disparities between racial and ethnic groups, thus targeted strategies are needed for the future.
Leveraging video data from a digital smartphone autism therapy to train an emotion detection classifier
Authors: Hou Cathy , Kalantarian Haik , Washington Peter , Dunlap Kaiti , Wall Dennis P. 
Published: July 2021

ABSTRACTAutism spectrum disorder (ASD) is a neurodevelopmental disorder affecting one in 40 children in the United States and is associated with impaired social interactions, restricted interests, and repetitive behaviors. Previous studies have demonstrated the promise of applying mobile systems with real-time emotion recognition to autism therapy, but existing platforms have shown limited performance on videos of children with ASD. We propose the development of a new emotion classifier designed specifically for pediatric populations, trained with images crowdsourced from an educational mobile charades-style game: Guess What?. We crowdsourced the acquisition of videos of children portraying emotions during remote game sessions of Guess What? that yielded 6,344 frames from fifteen subjects. Two raters manually labeled the frames with four of the Ekman universal emotions (happy, scared, angry, sad), a “neutral” class, and “n/a” for frames with an indeterminable label. The data were pre-processed, and a model was trained with a transfer-learning and neural-architecture-search approach using the Google Cloud AutoML Vision API. The resulting classifier was evaluated against existing approaches (Microsoft’s Azure Face API and Amazon Web Service’s Rekognition) using the standard metrics of F1 score. The resulting classifier demonstrated superior performance across all evaluated emotions, supporting our hypothesis that a model trained with a pediatric dataset would outperform existing emotion-recognition approaches for the population of interest. These results suggest a new strategy to develop precision therapy for autism at home by integrating the model trained with a personalized dataset to the mobile game.
Influence of social determinants of health and county vaccination rates on machine learning models to predict COVID-19 case growth in Tennessee
Authors: Wylezinski Lukasz S. , Harris Coleman R. , Heiser Cody N. , Gray Jamieson D. , Spurlock Charles F. 
Published: July 2021

AbstractThe SARS-CoV-2 (COVID-19) pandemic has exposed health disparities throughout the United States, particularly among racial and ethnic minorities. As a result, there is a need for data-driven approaches to pinpoint the unique constellation of clinical and social determinants of health (SDOH) risk factors that give rise to poor patient outcomes following infection in US communities.We combined county-level COVID-19 testing data, COVID-19 vaccination rates, and SDOH information in Tennessee. Between February-May 2021, we trained machine learning models on a semi-monthly basis using these datasets to predict COVID-19 incidence in Tennessee counties. We then analyzed SDOH data features at each time point to rank the impact of each feature on model performance.Our results indicate that COVID-19 vaccination rates play a crucial role in determining future COVID-19 disease risk. Beginning in mid-March 2021, higher vaccination rates significantly correlated with lower COVID-19 case growth predictions. Further, as the relative importance of COVID-19 vaccination data features grew, demographic SDOH features such as age, race, and ethnicity decreased while the impact of socioeconomic and environmental factors, including access to healthcare and transportation, increased.Incorporating a data framework to track the evolving patterns of community-level SDOH risk factors could provide policymakers with additional data resources to improve health equity and resilience to future public health emergencies.
DNA methylation patterns associated with cyanogenic cassava exposure and konzo in Sub-Saharan Africa
Authors: Kocher Kristen , Bhattacharya Surajit , Bramble Matthew S. , Okitundu-Luwa Daniel , Ngoyi Dieudonne Mumba , Tshala-Katumbay Desire , Vilain Eric 
Published: July 2021

AbstractMain TextKonzo, a disease characterized by sudden, irreversible spastic paraparesis, affecting up to 10% of the population in some regions of Sub-Saharan Africa during outbreaks and is strongly associated with dietary exposure to cyanogenic bitter cassava. The molecular mechanisms underlying the development of konzo, remain largely unknown. Here, through an analysis of 16 individuals with konzo and matched healthy controls from the same outbreak zones, we identified 117 differentially methylated loci involved in numerous biological processes that may identify cyanogenic- sensitive regions of the genome, providing the first study of epigenomic alterations associated with sub-lethal cyanide exposure and a clinical phenotype.
Identification of muscle weakness in older adults from normalized lower and upper limbs strength
Authors: Abdalla Pedro Pugliesi , Bohn Lucimere , Lopes da Silva Leonardo Santos , dos Santos André Pereira , Tasinafo Junior Marcio Fernando , Rossini Venturini Ana Claudia , dos Santos Carvalho Anderson , Gomez David Martinez , Mota Jorge , Lopes Machado Dalmo Roberto 
Published: July 2021

ABSTRACTIntroductionWeakness is a natural age-related condition meaning the loss of muscle strength that impairs older adults’ mobility and quality of life. Because the relationship between muscle strength and body-size variables is non-linear, weakness is misclassified in older adults with extreme body size (e.g., light, short, heavy, or tall). This misclassification can be overcome using the allometric approach.ObjectivesTo propose cut-off points for older adults’ weakness for upper and lower limbs muscle strength normalized by body size with the ratio standard and allometric scaling.MethodsNinety-four community-dwelling older adults (69.1% women) were assessed for 49 body-size variables (anthropometry, body composition and body indexes), handgrip strength (HGS), one maximum repetition measurement for knee extensors (1RMknee extensors), isokinetic knee extension peak torque at 60°/s (knee extensionPT60°/s), and six-minute walk test (6MWT). Ratio standard (muscle strength/body size) and allometric scaling (muscle strength/body sizeb; when b is the allometric exponent) were applied for body-size variables that significantly were correlated with HGS, 1RMknee extensors and knee extensionPT60°/s. Cut-off points were computed based on ROC curve and Youden index. When there was mobility limitation (6MWT<400m) cut-off were computed according to sex.ResultsAbsolute HGS, 1RMknee extensors and knee extensionPT60°/s cut-off points were not adequate because they were associated with body size (r>0.30). But it was corrected with muscle strength normalization according to body size-variables: HGS (n=1); 1RMknee extensors (n=24) and knee extensionPT60°/s (n=24). The best cut-off points, with the highest area under the curve (AUC), were found after normalization for men: HGS/forearm circumference (1.33 kg/cm, AUC=0.74), 1RMknee extensors/triceps skinfold (4.22 kg/mm, AUC=0.81), and knee extensionPT60°/s/body mass*height0.43 (13.0 Nm/kg*m0.43, AUC=0.94); and for women: HGS/forearm circumference (1.04 kg/cm, AUC=0.70), 1RMknee extensors/body mass (0.54 kg/kg, AUC=0.76); and knee extensionPT60°/s/body mass0.72 (3.14 Nm/kg0.72; AUC=0.82).ConclusionNormalization removes the effect of extreme body size on muscle strength and improves the accuracy to identify weakness at population level, reducing the risk of false-positive cases.HighlightsThis study proposed a new approach to identify muscle weakness in older adults based on upper and lower limbs muscle strength normalized by body size (ratio standard and allometry).The identification of functional limitation is more precise when procedures of muscle strength normalization is applied.
Monitoring COVID-19 spread in Prague local neighborhoods based on the presence of SARS-CoV-2 RNA in wastewater collected throughout the sewer network
Authors: Zdenkova Kamila , Bartackova Jana , Cermakova Eliska , Demnerova Katerina , Dostalkova Alzbeta , Janda Vaclav , Novakova Zuzana , Rumlova Michaela , Ambrozova Jana Rihova , Skodakova Klara , Swierczkova Iva , Sykora Petr , Vejmelkova Dana , Wanner Jiri , Bartacek Jan 
Published: July 2021

AbstractMany reports have documented that the presence of SARS-CoV-2 RNA in the influents of municipal wastewater treatment plants (WWTP) correlates with the actual epidemic situation in a given city. However, few data have been reported thus far on measurements upstream of WWTPs, i.e. throughout the sewer network. In this study, the monitoring of the presence of SARS-CoV-2 RNA in Prague wastewater was carried out at selected locations of the Prague sewer network from August 2020 through May 2021. Various locations such as residential areas of various sizes, hospitals, city center areas, student dormitories, transportation hubs (airport, bus terminal), and commercial areas were monitored together with four of the main Prague sewers. The presence of SARS-CoV-2 RNA was determined by reverse transcription – multiplex quantitative polymerase chain reaction (RT-mqPCR) after the precipitation of nucleic acids with PEG8000 and RNA isolation with TRIzol™ Reagent. The number of copies of the gene encoding SARS-CoV-2 nucleocapsid (N1) per liter of wastewater was compared with the number of officially registered COVID-19 cases in Prague. Although the data obtained by sampling wastewater from the major Prague sewers were more consistent than those obtained from the small sewers, the correlation between wastewater-based and clinical-testing data was also good for the residential areas with more than 1 000 registered inhabitants. It was shown that monitoring SARS-CoV-2 RNA in wastewater sampled from small sewers could identify isolated occurrences of COVID-19-positive cases in local neighborhoods. This can be very valuable while tracking COVID-19 hotspots within large cities.HighlightsSARS-CoV-2 RNA presence was measured at 24 locations in the Prague sewer networkResidential areas (100–13 000 inhab.), transport hubs, hospitals etc. were includedConsistent wastewater monitoring by RT-mqPCR took place from August 2020 – May 2021The sampling of major Prague sewers correlated well with clinical-based dataGrab samples can identify COVID-19 hotspots in local neighborhoodsGraphical abstract
Features importance in seizure classification using scalp EEG reduced to single timeseries
Authors: Naze Sébastien , Tang Jianbin , Kozloski James R. , Harrer Stefan 
Published: July 2021

AbstractSeizure detection and seizure-type classification are best performed using intra-cranial or full-scalp electroencephalogram (EEG). In embedded wearable systems however, recordings from only a few electrodes are available, reducing the spatial resolution of the signals to a handful of timeseries at most. Taking this constraint into account, we tested the performance of multiple classifiers using a subset of the EEG recordings by selecting a single trace from the montage or performing a dimensionality reduction over each hemispherical space. Our results support that Random Forest (RF) classifiers lead most ef-ficient and stable classification performances over Support Vector Machines (SVM). Interestingly, tracking the feature importances using permutation tests reveals that classical EEG spectrum power bands display different rankings across the classifiers: low frequencies (delta, theta) are most important for SVMs while higher frequencies (alpha, gamma) are more relevant for RF and Decision Trees. We reach up to 94.3% ∓ 5.3% accuracy in classifying absence from tonic-clonic seizures using state-of-art sampling methods for unbalanced datasets and leave-patients-out fold cross-validation policy.
Right Ventricular Dysfunction in Ventilated Patients with COVID-19 (COVID-RV)
Authors: McCall Philip , Willder Jennifer , Stanley Bethany , Messow Claudia-Martina , Allan John , Gemmell Lisa , Puxty Alex , Strachan Dominic , Berry Colin , Shelley Ben 
Published: July 2021

ABSTRACTPurposeCOVID-19 is associated with cardiovascular complications, with right ventricular dysfunction (RVD) commonly reported. The combination of acute respiratory distress syndrome (ARDS), injurious invasive ventilation, micro/macro thrombi and the potential for direct myocardial injury create conditions where RVD is likely to occur. No study has prospectively explored the prevalence of RVD, and its association with mortality, in a cohort requiring mechanical ventilation.MethodsProspective, multi-centre, trans-thoracic echocardiographic, cohort study of ventilated patients with COVID-19 in Scottish intensive care units. RVD was defined as the presence of severe RV dilatation and interventricular septal flattening. To explore role of myocardial injury, high sensitivity troponin and N-terminal pro B-type natriuretic peptide (NT-proBNP) were measured in all patients.ResultsOne hundred and twenty-one patients were recruited to COVID-RV, 118 underwent imaging and it was possible to determine the primary outcome in 112. RVD was present in seven (6.2% [95%CI; 2.5%, 12.5%]) patients. Thirty-day mortality was 85.7% in those with RVD, compared to 44.8% in those without (p=0.051). Patients with RVD were more likely to have; pulmonary thromboembolism (p<0.001), higher plateau pressure (p=0.048), lower dynamic compliance (p=0.031), higher NT-proBNP (p<0.006) and more frequent abnormal troponin (p=0.048). Abnormal NT-proBNP (OR 4.77 [1.22, 21.32], p=0.03) and abnormal Troponin (16.54 [4.98, 67.12], p<0.001) independently predicted 30-day mortality.ConclusionCOVID-RV demonstrates a prevalence of RVD in ventilated patients with COVID-19 of 6.2% and is associated with a mortality of 85.7%. Association is observed between RVD and each of the aetiological domains of; ARDS, ventilation, micro/macro thrombi and myocardial injury.