8-hydroxyguanosine (8-OHdG) is considered as an indicator of the oxidative stress. Pro inflammatory cytokines are critical parts of the pathophysiological processes to which treatment can be applied. The aim of this study was to evaluate 8-OHdG and pro inflammatory cytokines concentration in colon carcinoma patients. Blood samples were taken before treatment from 50 incident cases with colon cancer (stage III) admitted for health examination at the Nanakali Hospital in Erbil city with 45 healthy samples of controls with age range between 38-69 years for both groups. All studied parameters were estimated by ELISA. Participants at this study were 95 Participants ranged in age from 38 to 69 years, 50 Participants had been newly diagnosed with colorectal cancer (without treatment) with 45 individuals were healthy used as controls. The data showed a non-significant elevation by comparing the normal participants with colorectal cancer cases for (8-OHdG) by P-value 0.054 and a significant elevation for Tumor necrosis factor alpha (TNF-α) by P-value 0.019 and interleukin-6 (IL6) by P-value <0.0001. While the data showed a significant depletion by P-value <0.0001 for SOD and POX. The findings of the current study reveal that 8-OHdG refers to the local oxidative stress in colorectal cancer and TNF-α is accountable for increasing the concentrations of IL6, which is linked with inflammation process in the surrounding of cancer cell.
The main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
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