The study was trail to treated secondary hydatid cysts in white micepost-infection with Echinococcosis of sheep origin, by immunization with a mixture of CFAgs/PSAgs prepared from haydatid Cyst Fluid antigens (CFAgs) and Proto scolices antigens (PSAgs) respectively, two concentrations (7.5 &15 mg/ml) in addition to two derivatives of benzimidazole; albendazole (A) and mebendazole (M) 10 and 40μg/gm body weight, respectively, one week after challenged dose with protoscolices. to determine the efficacy of immunization and chemotherapy simultaneously in reduction the number of growing cysts, then measured both humoral and cell-mediated immunity. Results: elevation the immune responses that reflected decrease number and diameter of hydatid cysts. Conclusions: efficacy of immunotherapeutic state in regression the growing of hydatid cysts in mice. WR Ali, ZI Ibrahim, AAJ Ibrahim, international Journal of Research Studies in Biosciences (IJRSB), 2015 - Cited by 1
Study the Histopathology of Immuno-Therapytrail in Mice Infected with Hydatidcysts
Echinococcosis (Hydatid cysts)
therapy and immunization
Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Different Estimation Methods for System Reliability Multi-Components model: Exponentiated Weibull Distribution
Exponentiated Weibull Distribution (EWD)
Reliability of multi-component Stress – Strength models R(s
k)
Maximum likelihood estimator (MLE)
Moment estimator (MOM)
shrinkage method (Sh)
Least Squares Estimator (LS)
Rank Set Sampling (RSS). and mean squared error (MSE).
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
(1)
