bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting Olfactory Loss In Chronic Rhinosinusitis Using Machine Learning
Authors: Ramakrishnan Vijay R. , Arbet Jaron , Mace Jess C. , Suresh Krithika , Smith Stephanie Shintani , Soler Zachary M. , Smith Timothy L. 
Published: October 2020

ABSTRACTObjectiveCompare machine learning (ML) based predictive analytics methods to traditional logistic regression in classification of olfactory dysfunction in chronic rhinosinusitis (CRS-OD), and identify predictors within a large multi-institutional cohort of refractory CRS patients.MethodsAdult CRS patients enrolled in a prospective, multi-institutional, observational cohort study were assessed for baseline CRS-OD using a smell identification test (SIT) or brief SIT (bSIT). Four different ML methods were compared to traditional logistic regression for classification of CRS normosmics versus CRS-OD.ResultsData were collected for 611 study participants who met inclusion criteria between April 2011 and July 2015. 34% of enrolled patients demonstrated olfactory loss on psychophysical testing. Differences between CRS normosmics and those with smell loss included objective disease measures (CT and endoscopy scores), age, sex, prior surgeries, socioeconomic status, steroid use, polyp presence, asthma, and aspirin sensitivity. Most ML methods performed favorably in terms of predictive ability. Top predictors include factors previously reported in the literature, as well as several socioeconomic factors.ConclusionOlfactory dysfunction is a variable phenomenon in CRS patients. ML methods perform well compared to traditional logistic regression in classification of normosmia versus smell loss in CRS, and are able to include numerous risk factors into prediction models. Several actionable features were identified as risk factors for CRS-OD. These results suggest that ML methods may be useful for current understanding and future study of hyposmia secondary to sinonasal disease, the most common cause of persistent olfactory loss in the general population.
Predictors of mortality in hospitalized COVID-19 patients in Athens, Greece
Authors: Giannoglou Dimitrios , Meimeti Evangelia , Provatopoulou Xenia , Stathopoulos Konstantinos , Roukas Ioannis –Kriton , Galanis Petros 
Published: October 2020

ABSTRACTBackgroundThe epidemic of COVID-19 has rapidly spread worldwide, with millions of confirmed cases and related deaths. Numerous efforts are being made to clarify how the infection progresses and potential factors associated with disease severity and mortality. We investigated the mortality in Greek hospitalized COVID-19 patients and also the predictors of this mortality.MethodsStudy population included 512 COVID-19 patients admitted to the hospitals of the Attica region of Greece. Patients’ demographic characteristics, comorbidities, allergies, previous vaccination for seasonal influenza virus, admission to ICU, intubation, and death were recorded. Potential predictors of in-hospital mortality were identified by regression analysis.ResultsThe mean age of hospitalized patients was 60.4 years, and was higher in patients who deceased. The most common comorbidities were respiratory diseases, hypertension, gastrointestinal disorders, dyslipidemia, mental health diseases, asthma, diabetes mellitus and cardiovascular diseases. The need for ICU care and intubation was significantly higher among patients who died. The mortality rate was 15.8% (81 out of 512). Age ≥65 years, cancer, chronic kidney disease, endocrine diseases, central nervous system disorders, anemia, and intubation were independently associated with increased in-hospital mortality, while allergies and previous influenza vaccination were associated with decreased in-hospital mortality.ConclusionOur finding of a beneficial effect of allergies and influenza vaccination against COVID-19 infection merits further investigation, as it may shed light in the mechanisms underlying disease progression and severity. Most importantly, it may assist in the implementation of efficient protective measures and public healthcare policies.
School education during the SARS-CoV-2 pandemic - Which concept is safe, feasible and environmentally sound?
Authors: Kähler Christian J. , Fuchs Thomas , Mutsch Benedikt , Hain Rainer 
Published: October 2020

OverviewThe future belongs to children and they need education to shape the future with foresight and intention. Children therefore have the right to education, according to Article 29 of the UN Convention on the Rights of the Child [1]. However, professional education is not everything, because children must also experience their strengths and weaknesses together and educate each other to be responsible and considerate people, so that they become socially valuable personalities. Only in this way can they shape the future in a peaceful and humane way. Therefore, attending school is essential. However, children also have the right to protection and care by their parents and the state, because the welfare of the child must also be given priority in accordance with Article 3 of the UN Convention on the Rights of the Child. The question is therefore how schooling in community schools can be realized during the SARS-CoV-2 pandemic without exposing children to an unnecessary risk of infection. It is not only about the children, because if the children are at risk, then so are their parents and grandparents and ultimately society as a whole. There are numerous concepts that promise safety in schools during the pandemic. When selecting concepts, the costs must of course be weighed against the benefits. People rightly expect an efficient use of resources. This means that either the set goal is achieved with the least possible resources or that the available resources are used to achieve the greatest possible approximation to the goal. In addition to the financial resources, however, the long-term consequences for the state, the economy, the population and the environment under the pressure of the pandemic must also be taken into account. Social cohesion and democracy must not be jeopardized either. Various protection concepts are currently under discussion. Often the advantages are overstated and the disadvantages concealed. Furthermore, some arguments are based on assumptions that are not true. The aim of this study is to provide a comparative assessment of the main protection concepts and to demonstrate, with the help of experimental analyses, the extent to which the protection concepts are effective. We will show that a comparatively high level of safety against infection in classrooms can be technically ensured without exposing children to masks. At the same time, the protection concept makes economic sense and the burden on the environment is comparatively low, so that infection prevention and climate protection do not have to be weighed against each other, because infection prevention and climate protection are political and social goals that have to be achieved together.
Preventing COVID-19 spread in closed facilities by regular testing of employees – an efficient intervention in long-term care facilities and prisons?
Authors: Tsoungui Obama H. Christian , Adil M. Y. Nessma , Alawam N. Looli , Ngougoue N. Pierre M. , Ngwa Gideon A. , Teboh-Ewungkem Miranda , Schneider Kristan A. 
Published: October 2020

AbstractBackgroundDifferent levels of control measures were introduced to contain the global COVID-19 pandemic, many of which have been controversial, particularly the comprehensive use of diagnostic tests. Regular testing of high-risk individuals (pre-existing conditions, older than 60 years of age) has been suggested by public health authorities. The WHO suggested the use of routine screening of residents, employees, and visitors of long-term care facilities (LTCF) to protect the resident risk group. Similar suggestions have been made by the WHO for other closed facilities including incarceration facilities (e.g., prisons or jails), wherein parts of the U.S., accelerated release of approved inmates is taken as a measure to mitigate COVID-19.Methods and findingsHere, the simulation model underlying the pandemic preparedness tool CovidSim 1.1 (http://covidsim.eu/) is extended to investigate the effect of regularly testing of employees to protect immobile resident risk groups in closed facilities. The reduction in the number of infections and deaths within the risk group is investigated. Our simulations are adjusted to reflect the situation of LTCFs in Germany, and incarceration facilities in the U.S.COVID-19 spreads in closed facilities due to contact with infected employees even under strict confinement of visitors in a pandemic scenario without targeted protective measures. Testing is only effective in conjunction with targeted contact reduction between the closed facility and the outside world – and will be most inefficient under strategies aiming for herd immunity. The frequency of testing, the quality of tests, and the waiting time for obtaining test results have noticeable effects. The exact reduction in the number of cases depends on disease prevalence in the population and the levels of contact reductions. Testing every 5 days with a good quality test and a processing time of 24 hours can lead up to a 40% reduction in the number of infections. However, the effects of testing vary substantially among types of closed facilities and can even be counterproductive in U.S. IFs.ConclusionsThe introduction of COVID-19 in closed facilities is unavoidable without a thorough screening of persons that can introduce the disease into the facility. Regular testing of employees in closed facilities can contribute to reducing the number of infections there, but is only meaningful as an accompanying measure, whose economic benefit needs to be assessed carefully.
Tracking the Progression & Influence of Beta-Amyloid Plaques Using Percolation Centrality and Collective Influence Algorithm: A Study using PET Images
Authors: Baboo Gautam Kumar , Prasad Raghav , Mahajan Pranav , Baths Veeky 
Published: October 2020

Abstract(1) Background: Network analysis allows investigators to explore the many facets of brain networks, particularly the proliferation of disease. One of the hypotheses behind the disruption in brain networks in Alzheimer’s disease is the abnormal accumulation of beta-amyloid plaques and tau protein tangles. In this study, the potential use of percolation centrality to study beta-amyloid movement was studied as a feature of given PET image-based networks; (2) Methods: The PET image-based network construction is possible using a public access database - Alzheimer’s Disease Neuroimaging Initiative, which provided 551 scans. For each image, the Julich atlas provides 121 regions of interest, which are the network nodes. Besides, using the collective influence algorithm, the influential nodes for each scan are calculated; (3) Analysis of variance (p<0.05) yields the region of interest Gray Matter Broca’s Area for PiB tracer type for five nodal metrics. In comparison, AV45: the Gray Matter Hippocampus region is significant for three of the nodal metrics. Pairwise variance analysis between the clinical groups yields five and twelve statistically significant ROIs for AV45 and PiB, capable of distinguishing between pairs of clinical conditions. Multivariate linear regression between the percolation centrality values for nodes and psychometric assessment scores reveals Mini-Mental State Examination is reliable(4) Conclusion: percolation centrality effectively (41% of ROIs) indicates that the regions of interest that are part of the memory, visual-spatial skills, and language are crucial to the percolation of beta-amyloids within the brain network to the other widely used nodal metrics. Ranking the regions of interest based on the collective influence algorithm indicates the anatomical areas strongly influencing the beta-amyloid network.
Prone positioning of non-intubated patients with COVID-19 - A Systematic Review and Meta-analysis
Authors: Reddy Mallikarjuna Ponnapa , Subramaniam Ashwin , Lim Zheng Jie , Zubarev Alexandr , Afroz Afsana , Billah Baki , Blecher Gabriel , Tiruvoipati Ravindranath , Ramanathan Kollengode , Wong Suei Nee , Brodie Daniel , Fan Eddy , Shekar Kiran 
Published: October 2020

ABSTRACTPurposeSeveral studies have reported adopting prone positioning (PP) in non-intubated patients with COVID-19-related hypoxaemic respiratory failure. This systematic review and meta-analysis evaluated the impact of PP on oxygenation and clinical outcomes.MethodsWe searched PubMed, Embase and COVID-19 living systematic review from December1st 2019 to July23rd 2020. We included studies that reported using PP in hypoxaemic, non-intubated adult COVID-19 patients. Primary outcome measure was the weighted mean difference (MD) in oxygenation parameters (PaO2/FiO2, PaO2 or SpO2) pre and post-PP.ResultsFifteen single arm observational studies reporting PP in 449 patients were included. Substantial heterogeneity was noted in terms of, location within hospital where PP was instituted, respiratory supports, frequency and duration of PP. Significant improvement in oxygenation was reported post-PP: PaO2/FiO2, (MD 37.6, 95%CI 18.8, 56.5); PaO2, (MD 30.4 mmHg, 95%CI 10.9, 49.9); and SpO2, (MD 5.8%, 95%CI 3.7, 7.9). Patients with a pre-PP PaO2/FiO2 ≤150 experienced greater oxygenation improvements compared with those with a pre-PP PaO2/FiO2 >150 (MD 40.5, 95%CI −3.5, 84.6) vs. 37, 95%CI 17.1, 56.9). Respiratory rate decreased post-PP (MD −2.9, 95%CI −5.4, −0.4). Overall intubation and mortality rates were 21% (90/426) and 26% (101/390) respectively. No major adverse events were reported.ConclusionsDespite significant variability in frequency and duration of PP and respiratory supports, PP was associated with improvements in oxygenation parameters without any reported serious adverse events. Major limitation being lack of control arm and adjustment for confounders. Clinical trials are required to determine the effect of awake PP on patient-centred outcomes.Systematic review registrationRegistration/protocol in PROSPERO (CRD42020194080).What is the key question?Is the novel approach of prone positioning in non-intubated patients associated with improvement in oxygenation?What is the bottom line?Prone position in non-intubated severe COIVD 19 suffers is associated with improvement of oxygenation while the short- and long-term patient centred out comes in this awake prone patient need more investigation.Why read on?Our study is first of its kind (Systematic review and Meta-analysis) summarising the evidence surrounding the less invasive innovate technique of prone position in non-intubated COVID-19 patients.
Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study
Authors: Levy Joshua J. , Lebeaux Rebecca M. , Hoen Anne G. , Christensen Brock C. , Vaickus Louis J. , MacKenzie Todd A. 
Published: October 2020

AbstractWhat is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?BackgroundFollowing a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.ObjectiveWe sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.MethodsSatellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing approximately 68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.ResultsPredicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r=0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g. sidewalks, driveways and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race and age.ConclusionsThe application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.
Molecular characterization of SARS-CoV-2 from Bangladesh: Implications in genetic diversity, possible origin of the virus, and functional significance of the mutations
Authors: Rahman Md. Marufur , Kader Shirmin Bintay , Rizvi S M Shahriar 
Published: October 2020

AbstractIn a try to understand the pathogenesis, evolution and epidemiology of the SARS-CoV-2 virus, scientists from all over the world are tracking its genomic changes in real-time. Genomic studies can be helpful in understanding the disease dynamics. We have downloaded 324 complete and near complete SARS-CoV-2 genomes submitted in GISAID database from Bangladesh which were isolated between 30 March to 7 September, 2020. We then compared these genomes with Wuhan reference sequence and found 4160 mutation events including 2253 missense single nucleotide variations, 38 deletions and 10 insertions. The C>T nucleotide change was most prevalent (41% of all muations) possibly due to selective mutation pressure to reduce CpG sites to evade CpG targeted host immune response. The most frequent mutation that occurred in 98% isolates was 3037C>T which is a synonymous change that almost always accompanied 3 other mutations that include 241C>T, 14408C>T (P323L in RdRp) and 23403A>G (D614G in spike protein). The P323L was reported to increase mutation rate and D614G is associated with increased viral replication and currently most prevalent variant circulating all over the world. We identified multiple missense mutations in B-cell and T-cell predicted epitope regions and/or PCR target regions (including R203K and G204R that occurred in 86% of the isolates) that may impact immunogenicity and/or RT-PCR based diagnosis. Our analysis revealed 5 large deletion events in ORF7a and ORF8 gene products that may be associated with less severity of the disease and increased viral clearance. Our phylogeny analysis identified most of the isolates belonged to the Nextstrain clade 20B (86%) and GISAID clade GR (88%). Most of our isolates shared common ancestors either directly with European countries or jointly with middle eastern countries as well as Australia and India. Interestingly, the 19B clade (GISAID S clade) was unique to Chittagong which was originally prevalent in China. This reveals possible multiple introduction of the virus in Bangladesh via different routes. Hence more genome sequencing and analysis with related clinical data is needed to interpret functional significance and better predict the disease dynamics that may be helpful for policy makers to control the COVID-19 pandemic in Bangladesh.
Postnatal fluoxetine treatment alters perineuronal net formation and maintenance in the hippocampus
Authors: Mukhopadhyay Sourish , Chatterjee Ashmita , Tiwari Praachi , Ghai Utkarsha , Vaidya Vidita A. 
Published: October 2020

AbstractElevation of serotonin via postnatal fluoxetine (PNFlx) treatment during critical temporal windows is hypothesized to perturb the development of limbic circuits thus establishing a substratum for persistent disruption of mood-related behavior. We examined the impact of PNFlx treatment on the formation and maintenance of perineuronal nets (PNNs), extracellular matrix (ECM) structures that deposit primarily around inhibitory interneurons, and mark the closure of critical period plasticity. PNFlx treatment evoked a significant decline in PNN number, with a robust reduction in PNNs deposited around parvalbumin (PV) interneurons, within the CA1 and CA3 hippocampal subfields at postnatal day 21 in Sprague-Dawley rat pups. While the reduction in CA1 subfield PNN number was still observed in adulthood, we observed no change in colocalization of PV-positive interneurons with PNNs in the hippocampi of adult PNFlx animals. PNFlx treatment did not alter hippocampal parvalbumin, calretinin, or reelin-positive neuron numbers in PNFlx animals at P21 or in adulthood. We did observe a small, but significant increase in somatostatin (SST)-positive interneurons in the DG subfield of PNFlx-treated animals in adulthood. This was accompanied by altered GABA-A receptor subunit composition, increased dendritic complexity of apical dendrites of CA1 pyramidal neurons, and enhanced neuronal activation revealed by increased c-Fos-positive cell numbers within hippocampi of PNFlx-treated animals in adulthood. These results indicate that PNFlx treatment alters the developmental trajectory of PNNs within the hippocampus, raising the possibility of a disruption of critical period plasticity and the establishment of an altered excitation-inhibition balance within this key limbic brain region.Significance StatementClinical and preclinical studies indicate that developmental exposure to fluoxetine programs persistent dysregulation of mood-related behaviors. This is hypothesized to involve the disruption of the normal development of key brain regions, such as the hippocampus that regulate mood behaviors. We show that postnatal exposure to fluoxetine alters hippocampal perineuronal nets (PNNs), extracellular matrix structures that regulate plasticity and mark the closure of critical periods. The decline in PNNs is noted in early postnatal life, and persists into adulthood in specific hippocampal subfields. Adult animals with a history of postnatal fluoxetine exposure exhibit altered numbers of somatostatin interneurons, GABA receptor subunit expression and neuronal activation within the hippocampus. This indicates that postnatal fluoxetine disrupts the normal developmental trajectory of the hippocampus.
From more testing to smart testing: data-guided SARS-CoV-2 testing choices
Authors: van Beek Janko , Igloi Zsofia , Boelsums Timo , Fanoy Ewout , Gotz Hannelore , Molenkamp Richard , van Kampen Jeroen , GeurtsvanKessel Corine , van der Eijk Annemiek , van de Vijver David , Koopmans Marion 
Published: October 2020

AbstractWe present an in-depth analysis of data from drive through testing stations using rapid antigen detection tests (RDT’s), RT-PCR and virus culture, to assess the ability of RDT’s to detect infectious cases. We show that the detection limits of five commercially available RDT’s differ considerably, impacting the translation into the detection of infectious cases. We recommend careful fit-for-purpose testing before implementation of antigen RDT’s in routine testing algorithms as part of the COVID-19 response.