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  1. Article: Impact of COVID-19 on Mitochondrial-Based Immunity in Aging and Age-Related Diseases.

    Ganji, Riya / Reddy, P Hemachandra

    Frontiers in aging neuroscience

    2021  Volume 12, Page(s) 614650

    Abstract: The coronavirus disease 2019 (COVID-19) has become a deadly pandemic with surging mortality rates and no cure. COVID-19 is caused by the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) with a range of clinical symptoms, including cough, ... ...

    Abstract The coronavirus disease 2019 (COVID-19) has become a deadly pandemic with surging mortality rates and no cure. COVID-19 is caused by the severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) with a range of clinical symptoms, including cough, fever, chills, headache, shortness of breath, difficulty breathing, muscle pain, and a loss of smell or taste. Aged individuals with compromised immunity are highly susceptible to COVID-19 and the likelihood of mortality increases with age and the presence of comorbidities such as hypertension, diabetes mellitus, cardiovascular disease, or chronic obstructive pulmonary disease. Emerging evidence suggests that COVID-19 highjacks mitochondria of immune cells, replicates within mitochondrial structures, and impairs mitochondrial dynamics leading to cell death. Mitochondria are the powerhouses of the cell and are largely involved in maintaining cell immunity, homeostasis, and cell survival/death. Increasing evidence suggests that mitochondria from COVID-19 infected cells are highly vulnerable, and vulnerability increases with age. The purpose of our article is to summarize the role of various age-related comorbidities such as diabetes, obesity, and neurological diseases in increasing mortality rates amongst the elderly with COVID-19. Our article also highlights the interaction between coronavirus and mitochondrial dynamics in immune cells. We also highlight the current treatments, lifestyles, and safety measures that can help protect against COVID-19. Further research is urgently needed to understand the molecular mechanisms between the mitochondrial virus and disease progression in COVID-19 patients.
    Language English
    Publishing date 2021-01-12
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2558898-9
    ISSN 1663-4365
    ISSN 1663-4365
    DOI 10.3389/fnagi.2020.614650
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Coronavirus (COVID-19) Spike in Georgia: An Epidemiologic Study of Data, Modelling, and Policy Implications to Understand the Gender-and Race-Specific Variations

    Mostafa, Fahad / Ganji, Riya / St. John, Julie / Khan, Hafiz

    medRxiv

    Abstract: Objective The purpose of this study was to investigate the gender and race specific predictive variations in COVID-19 cases and deaths in Georgia, USA. Methods The data were extracted from the Georgia Department of Public Health (GDPH). Statistical ... ...

    Abstract Objective The purpose of this study was to investigate the gender and race specific predictive variations in COVID-19 cases and deaths in Georgia, USA. Methods The data were extracted from the Georgia Department of Public Health (GDPH). Statistical methods, such as descriptive statistics, Artificial neural networks (ANN), and the Bayesian approach, were utilized to analyze the data. Results More Whites died from COVID 19 than African-Americans/Blacks in Cobb, Hall, Gwinnett, and non Georgia residents; however, more Blacks died in Dekalb and Fulton counties. The highest posterior mean for female deaths was obtained in Gwinnett County (77.17; 95% CI, 74.23 to 80.07) and for male deaths in Fulton County (73.48; 95% CI, 72.18 to 74.49). For overall race/ethnicity, Whites had the highest posterior mean for deaths (183.18; 95% CI, 128.29 to 238.27) compared with Blacks (162.48; 95% CI, 127.15 to 197.42). Assessing the classification of the chronic medical conditions using ANN, Cobb and Hall Counties showed the highest mean AUC under ROC of the models (78% and 79%, respectively). Conclusions The predictive models of COVID 19 transmission will help public health practitioners and researchers to better understand the course of the COVID-19 pandemic. The study findings are generalizable to populations with geographic and racial/ethnic similarities and may be used to determine gender/race-specific future virus models for effective interventions or policy modifications.
    Keywords covid19
    Language English
    Publishing date 2021-12-11
    Publisher Cold Spring Harbor Laboratory Press
    Document type Article ; Online
    DOI 10.1101/2021.12.09.21267571
    Database COVID19

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