Covid-19 is a respiratory disease similar to pneumonia that results from an infection with SARS-CoV-2, a recently identified virus that became a global pandemic in 2020. The severe cases of the disease show a cytokine storm, which is excessive, uncontrolled production of pro inflammatory cytokines. MicroRNA-155 is an epigenetic microRNA that has the ability to control pro-inflammatory responses in many diseases. We aim to determine the relationship between microRNA-155 expression and some cytokines (interleukin-6, interleukin-8, and interleukin-1β) in severe covid-19 cases. A case-control study of 235 samples was collected from 120 patients with severe covid-19 and 115 of mild covid-19 cases and healthy individuals of different sexes and ages. After RNA extraction and conversion to cDNA, RT-PCR was performed on both studied groups. The levels of studied interleukins were determined for 50 severe covid-19 patients and 40 control individuals (mild and healthy). A substantial elevation in the expression of microRNA-155 was seen in severe COVID-19 patients compared to its expression in the control group consisting of mild cases and healthy individuals. Interleukin-6, interleukin-8, and interleukin-1β also show elevated levels in severe covid-19 serum than control individuals. This investigation revealed a strong and statistically significant correlation between the expression of microRNA-155 and interleukin-6, as well as a substantial correlation between the expression of microRNA-155 and interleukin-1β. MicroRNA-155 might have a role in inducing some pro-inflammatory interleukins that leads to cytokine storm.
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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In this paper, we introduce a new type of functions in bitopological spaces, namely, (1,2)*-proper functions. Also, we study the basic properties and characterizations of these functions . One of the most important of equivalent definitions to the (1,2)*-proper functions is given by using (1,2)*-cluster points of filters . Moreover we define and study (1,2)*-perfect functions and (1,2)*-compact functions in bitopological spaces and we study the relation between (1,2)*-proper functions and each of (1,2)*-closed functions , (1,2)*-perfect functions and (1,2)*-compact functions and we give an example when the converse may not be true .