Background: The SARS-CoV-2 virus causes COVID-19, a respiratory syndrome. It causes inflammation and damages several organs in the body. miRNAs play a role in regulating the infection resulting from SARS-CoV-2. MicroRNA-155, a kind of microRNA linked to viral defences, can affect the immune responses during COVID-19. Objectives: Examination of the involvement of microRNA-155 in the development and severity of COVID-19, as well as finding the correlation between microRNA-155 and viral load (copies/mL) in severe cases of the disease. Materials and Method: A case-control research study was performed between October 2022 and June 2023. It included a cohort of 120 hospitalised individuals with severe cases of COVID-19, together with 115 individuals with mild cases of COVID-19 and apparently healthy individuals. A real-time PCR procedure was applied to determine microRNA-155 expression in the studied groups and the viral load (copies/mL) in severe cases of the disease. Results: MicroRNA-155 was expressed in severe cases threefold more than its expression in mild cases of COVID-19 and healthy individuals. Also, a strong association was demonstrated between microRNA-155 and viral load (copies/mL) in severe COVID-19. Conclusion: MicroRNA-155 could be used as a biomarker for severe COVID-19 conditions and could have a role in disease severity and infectious particles of the virus. Since it is positively correlated with viral load (copies/mL) in severe cases of the disease
In this paper, we are mainly concerned with estimating cascade reliability model (2+1) based on inverted exponential distribution and comparing among the estimation methods that are used . The maximum likelihood estimator and uniformly minimum variance unbiased estimators are used to get of the strengths and the stress ;k=1,2,3 respectively then, by using the unbiased estimators, we propose Preliminary test single stage shrinkage (PTSSS) estimator when a prior knowledge is available for the scale parameter as initial value due past experiences . The Mean Squared Error [MSE] for the proposed estimator is derived to compare among the methods. Numerical results about conduct of the considered
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