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SARS-CoV-2 proteins

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SARS-CoV-2 Proteins
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    Increased serum thromboxane A2 and prostacyclin but lower complement C3 HGNC and C4 levels in COVID-19 MESHD: associations with chest CT-scan anomalies MESHD and lowered peripheral oxygen saturation.

    Authors: Hussein K Al-Hakeim; Shaymaa Al-Hamami; Michael Maes

    doi:10.1101/2021.04.10.21255240 Date: 2021-04-13 Source: medRxiv

    Background. COVID-19 MESHD patients suffer from hypercoagulation MESHD and activated immune-inflammatory pathways. This study was performed to assay serum complement C3 HGNC and C4, and thromboxane A2 (TxA2) and prostacyclin (PGI2) in association with chest CT scan anomalies MESHD (CCTAs) and peripheral oxygen saturation (SpO2) Methods. Serum levels of C3, C4, TxA2, and PGI2 were measured by ELISA and albumin, calcium, and magnesium by spectrophotometric method in 60 COVID-19 MESHD patients and 30 controls. Results. C3 and C4 are significantly decreased and TxA2 and PGI2 significantly increased in COVID-19 MESHD patients as compared with controls. Neural networks showed that a combination of C3, albumin, and TxA2 yielded a predictive accuracy of 100% in detecting COVID-19 MESHD patients. SpO2 was significantly decreased in COVID-19 MESHD patients and was inversely associated with TxA2 and PGI2, and positively with C3, C4, albumin, and calcium. CCTAs were accompanied by lower SpO2 and albumin, and increased PGI2 levels. Patients with positive IgG results show significantly higher SpO2, TxA2, PGI2, and C4 levels than IgG negative patients. Conclusion. Hypoalbuminemia MESHD, which is strongly associated with lung lesions MESHD and lowered peripheral oxygen saturation, is characterized by increased TxA2, suggesting that interactions between immune-inflammatory pathways and platelet hyperactivity MESHD participate in the pathophysiology of COVID-19 MESHD and consequently may play a role in enhanced risk of hypercoagulability MESHD and venous thromboembolism MESHD. These mechanisms are aggravated by lowered calcium and magnesium levels.

    Changes in live births, preterm birth, low birth weight MESHD, and cesarean deliveries in the United States during the SARS-CoV-2 pandemic

    Authors: Alison Gemmill; Joan A. Casey; Ralph Catalano; Deborah Karasek; Tim-Allen Bruckner

    doi:10.1101/2021.03.20.21253990 Date: 2021-03-25 Source: medRxiv

    Background: The SARS-CoV-2 pandemic and associated social, economic, and clinical disruption have been widely speculated to affect pregnancy decision-making and outcomes. While a few US-based studies have examined subnational changes in fertility, preterm birth, and stillbirth MESHD, there remains limited knowledge of how the pandemic impacted childbearing and a broader set of perinatal health indicators at the national-level throughout 2020. Here, we use recently released national-level data to fill this gap. Importantly, we, unlike earlier work, use time-series methods to account for strong temporal patterning (e.g., seasonality, trend) that could otherwise lead to spurious findings. Methods: For the years 2015 to 2020, we obtained national monthly counts of births and rates (per 100 births) for six perinatal indicators: preterm birth (<37 weeks gestation), early preterm birth (<34 weeks gestation), late preterm birth (34-36 weeks gestation), low birth weight birth MESHD (<2500 g), very low birth weight birth MESHD (<1500 g), and cesarean delivery. We use an interrupted time-series approach to compare the outcomes observed after the pandemic began (March 2020) to those expected had the pandemic not occurred. Results: For total births as well as five of the six indicators (i.e., all but the rate of cesarean delivery), observed values fall well below expected levels (p

    Limits of lockdown: characterising essential contacts during strict physical distancing

    Authors: Amy C Thomas; Leon Danon; Hannah Christensen; Kate Northstone; Daniel Smith; Emily J Nixon; Adam Trickey; Gibran Hemani; Sarah Sauchelli; Adam Finn; Nicholas J Timpson; Ellen Brooks-Pollock

    doi:10.1101/2021.03.12.21253484 Date: 2021-03-13 Source: medRxiv

    COVID-19 MESHD has exposed health inequalities within countries and globally. The fundamental determining factor behind an individuals risk of infection is the number of social contacts they make. In many countries, physical distancing measures have been implemented to control transmission of SARS-CoV-2, reducing social contacts to a minimum. Characterising unavoidable social contacts is key for understanding the inequalities behind differential risks and planning vaccination programmes. We utilised an existing English longitudinal birth cohort MESHD, which is broadly representative of the wider population (n=6807), to explore social contact patterns and behaviours when strict physical distancing measures were in place during the UKs first lockdown in March-May 2020. Essential workers, specifically those in healthcare, had 4.5 times as many contacts as non-essential workers [incident rate ratio = 4.42 (CI95%: 3.88-5.04)], whilst essential workers in other sectors, mainly teaching and the police force had three times as many contacts [IRR = 2.84 (2.58-3.13)]. The number of individuals in a household, which is conflated by number of children, increases essential social contacts by 40%. Self-isolation effectively reduces numbers of contacts outside of the home, but not entirely. Together, these findings will aid the interpretation of epidemiological data and impact the design of effective SARS-CoV-2 control strategies, such as vaccination, testing and contact tracing.

    Reptile: Aggregation-level Explanations for Hierarchical Data

    Authors: Zezhou Huang; Eugene Wu

    id:2103.07037v1 Date: 2021-03-12 Source: arXiv

    Recent query explanation systems help users understand anomalies MESHD in aggregation results by proposing predicates that describe input records that, if deleted, would resolve the anomalies MESHD. However, it can be difficult for users to understand how a predicate was chosen, and these approaches are limited to errors that can be resolved through deletion. In contrast, data errors may be due to group-wise errors, such as missing records or systematic value errors. This paper presents Reptile, an explanation system for hierarchical data. Given an anomalous aggregate query result, Reptile recommends the next drill-down attribute,and ranks the drill-down groups based on the extent repairing the group's statistics to its expected values resolves the anomaly MESHD. Reptile efficiently trains a multi-level model that leverages the data's hierarchy to estimate the expected values, and uses a factorised representation of the feature matrix to remove redundancies due to the data's hierarchical structure. We further extend model training to support factorised data, and develop a suite of optimizations that leverage the data's hierarchical structure. Reptile reduces end-to-end runtimes by more than 6 times compared to a Matlab-based implementation, correctly identifies 21/30 data errors in John Hopkin's COVID-19 MESHD data, and correctly resolves 20/22 complaints in a user study using data and researchers from Columbia University's Financial Instruments Sector Team.

    A two-step explainable approach for COVID-19 MESHD computer-aided diagnosis from chest x-ray images

    Authors: Carlo Alberto Barbano; Enzo Tartaglione; Claudio Berzovini; Marco Calandri; Marco Grangetto

    id:2101.10223v1 Date: 2021-01-25 Source: arXiv

    Early screening of patients is a critical issue in order to assess immediate and fast responses against the spread of COVID-19 MESHD. The use of nasopharyngeal swabs has been considered the most viable approach; however, the result is not immediate or, in the case of fast exams, sufficiently accurate. Using Chest X-Ray (CXR) imaging for early screening potentially provides faster and more accurate response; however, diagnosing COVID from CXRs is hard and we should rely on deep learning support, whose decision process is, on the other hand, "black-boxed" and, for such reason, untrustworthy. We propose an explainable two-step diagnostic approach, where we first detect known pathologies ( anomalies MESHD) in the lungs, on top of which we diagnose the illness. Our approach achieves promising performance in COVID detection, compatible with expert human radiologists. All of our experiments have been carried out bearing in mind that, especially for clinical applications, explainability plays a major role for building trust in machine learning algorithms MESHD.

    Overcrowding and Exposure to Secondhand Smoke Increase Risk for COVID-19 MESHD Infection Among Latinx Families in Greater San Francisco Bay Area

    Authors: Andrea DeCastro Mendez; Milagro Escobar; Maria Romero Encinas; Janet Wojcicki

    doi:10.1101/2021.01.19.21250139 Date: 2021-01-20 Source: medRxiv

    Background: The novel coronavirus ( COVID-19 MESHD) has disproportionately impacted the Latinx community in the United States. Environmental risk factors, including community level pollution burden and exposure to smoking and secondhand smoke, have not been evaluated in relation to risk for infection with COVID-19 MESHD. Methods: We evaluated self-reported infection rates of COVID-19 MESHD in three, preexisting, longitudinal, Latinx family cohorts in the San Francisco Bay Area from May through September 2020 (N=383 households, 1,875 people). All households were enrolled during pregnancy and postpartum at Zuckerberg San Francisco General Hospital (ZSFG) and UCSF Benioff before the pandemic. For the COVID-19 MESHD sub-study, participants responded to a 15-minute telephonic interview where we assessed food consumption patterns, housing and employment status, and history of COVID-19 MESHD infection based on community and hospital-based testing. We also evaluated secondhand smoke exposure based on previously collected data. Environmental pollution exposure was determined from census tract residence using California EnviroScreen 2.0 data. Non-parametric tests were used to assess possible associations and multiple logistic regression analyses to determine independent predictors of COVID-19 MESHD infection. Results: In the combined Latinx, Eating and Diabetes Cohort MESHD ( LEAD MESHD) and Hispanic, Eating and Nutrition ( HEN MESHD) cohorts there was a 7.6% household infection rate (14/183) with a lower rate of 3.5% (7/200) in the Telomeres at Birth MESHD (TAB) cohort. Larger household size increased risk for infection (OR, 1.43 (95%CI 1.10-1.87)) in the combined LEAD/HEN cohorts and increasing number of children trended towards significance in the TAB cohort (OR 1.82, 95% CI 0.98-3.37). Any exposure to secondhand smoke in the household also trended towards increasing risk after adjusting for household size and other exposures (OR 3.20, 95%CI 0.80-12.73) and (OR 4.37, 95% CI 0.80-23.70). We did not find any associations between neighborhood pollution level and COVID-19 MESHD infection based on census track and risk of infection. Furthermore, we found weak evidence between dietary exposure and risk of COVID-19 MESHD infection after adjusting for possible confounders. Conclusion: Crowding as indicated by household size increases risk for COVID-19 MESHD infection in Latinx families. Exposure to any secondhand smoke may also increase risk for COVID-19 MESHD through increased coughing and risk for respiratory impairment MESHD. Public policy and health interventions need to ensure that multi-unit residential complexes prevent any exposure to secondhand smoke.

    Where you Live Matters: A Spatial Analysis of COVID-19 MESHD Mortality

    Authors: Behzad Javaheri

    id:10.20944/preprints202101.0218.v1 Date: 2021-01-12 Source: Preprints.org

    The COVID-19 pandemic MESHD has caused ~ 2 million fatalities. Significant progress has been made in advancing our understanding of the disease process, one of the unanswered questions, however, is the anomaly MESHD in the case/mortality ratio with Mexico as a clear example. Herein, this anomaly MESHD is explored by spatial analysis and whether mortality varies locally according to local factors. To address this, hexagonal cartogram maps (hexbin) used to spatially map COVID-19 MESHD mortality and visualise association with patient-level data on demographics and pre-existing health conditions. This was further interrogated at local Mexico City level by choropleth mapping. Our data show that the use of hexagonal cartograms is a better approach for spatial mapping of COVID-19 MESHD data in Mexico as it addresses bias in area size and population. We report sex/age-related spatial relationship with mortality amongst the Mexican states and a trend between health conditions and mortality at the state level. Within Mexico City, there is a clear south, north divide with higher mortality in the northern municipalities. Deceased patients in these northern municipalities have the highest pre-existing health conditions. Taken together, this study provides an improved presentation of COVID-19 MESHD mapping in Mexico and demonstrates spatial divergence of the mortality in Mexico.

    Where you live matters: a spatial analysis of COVID-19 MESHD mortality

    Authors: Behzad Javaheri

    id:2101.04199v1 Date: 2021-01-11 Source: arXiv

    The COVID-19 pandemic MESHD has caused ~ 2 million fatalities. Significant progress has been made in advancing our understanding of the disease process, one of the unanswered questions, however, is the anomaly MESHD in the case/mortality ratio with Mexico as a clear example. Herein, this anomaly MESHD is explored by spatial analysis and whether mortality varies locally according to local factors. To address this, hexagonal cartogram maps (hexbin) used to spatially map COVID-19 MESHD mortality and visualise association with patient-level data on demographics and pre-existing health conditions. This was further interrogated at local Mexico City level by choropleth mapping. Our data show that the use of hexagonal cartograms is a better approach for spatial mapping of COVID-19 MESHD data in Mexico as it addresses bias in area size and population. We report sex/age-related spatial relationship with mortality amongst the Mexican states and a trend between health conditions and mortality at the state level. Within Mexico City, there is a clear south, north divide with higher mortality in the northern municipalities. Deceased patients in these northern municipalities have the highest pre-existing health conditions. Taken together, this study provides an improved presentation of COVID-19 MESHD mapping in Mexico and demonstrates spatial divergence of the mortality in Mexico.

    Lived experiences of pregnant and new mothers during COVID-19 pandemic MESHD: A narrative analysis of YouTube birth stories.

    Authors: Kobi V Ajayi; Idethia S Harvey; Sonya Panjwani; Inyang Uwak; Whitney Garney; Robin L Page

    doi:10.1101/2020.12.28.20248958 Date: 2021-01-04 Source: medRxiv

    IntroductionThe COVID-19 pandemic MESHD has brought on unprecedented changes, not only to our daily lives but also to our healthcare system. The pandemic has particularly impacted pregnant women that must give birth with tight restrictions and significant uncertainties. Birth stories MESHD have frequently been used as a way for women to describe their experiences with the birthing process. In this uncertain time, birth stories can provide valuable insight into how pregnancy and birth stressors during a pandemic can impact the patients overall experience. This study sought to describe and understand pregnant and new mothers lived experiences during the COVID-19 pandemic MESHD. MethodsResearchers extracted relevant YouTube birth stories using predetermined search terms and inclusion criteria. The mothers birth stories were narrated in their second or third trimester or those who had recently given birth during the study period. Birth stories MESHD were analyzed using an inductive and deductive approach to capture different aspects of the birthing experience. ResultsOverall, eighty-three birth stories were analyzed. Within these birth stories, four broad themes and twelve subthemes emerged. Key themes included a sense of loss, hospital experiences, experiences with healthcare providers, and unique experiences during birth and postpartum. The birth stories revealed negative and positive birth experiences. Particularly, mothers were frustrated with constantly changing policies within the healthcare setting that negatively affected their birthing experience. On the other hand, support from healthcare professionals, having their partners in the delivery room, and having a positive mindset was instrumental in having a positive birth experience. ConclusionResults from this study provided a detailed description of womens lived experience with giving birth during the COVID-19 pandemic MESHD. Healthcare providers need to provide clear communication and compassionate patient-centered care to relieve womens anxiety MESHD about uncertain and unpredictable policy as the pandemic continues to evolve.

    Dynamics, behaviours, and anomaly MESHD persistence in cryptocurrencies and equities surrounding COVID-19 MESHD

    Authors: Nick James

    id:2101.00576v3 Date: 2021-01-03 Source: arXiv

    This paper uses new and recently introduced methodologies to study the similarity in the dynamics and behaviours of cryptocurrencies and equities surrounding the COVID-19 pandemic MESHD. We study two collections; 45 cryptocurrencies and 72 equities, both independently and in conjunction. First, we examine the evolution of cryptocurrency and equity market dynamics, with a particular focus on their change during the COVID-19 pandemic MESHD. We demonstrate markedly more similar dynamics during times of crisis. Next, we apply recently introduced methods to contrast trajectories, erratic behaviours, and extreme values among the two multivariate time series. Finally, we introduce a new framework for determining the persistence of market anomalies MESHD over time. Surprisingly, we find that although cryptocurrencies exhibit stronger collective dynamics and correlation in all market conditions, equities behave more similarly in their trajectories, extremes, and show greater persistence in anomalies MESHD over time.

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MeSH Disease
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SARS-CoV-2 Proteins


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