Background: Although expression of the HER-
2/neuoncogene may be of some prognostic importance
in advanced ovarian cancer, its role in early-stage
disease has not been established. The current study
examined the prevalence and significance of HER-
2/neu expression in different grades of different types
of surface epithelial ovarian carcinoma.
Methods: Thirty eight female patients with surface
epithelial ovarian cancer were included in this study.
The blocks of corresponding formalin fixed, paraffinembedded
ovarian biopsies were retrieved from the
archives and hematoxylin-eosin slides of each ovarian
biopsy were reviewed and marked their grades of
differentiation , then a new sections from each sample
stained by her2/neu as immunohistochemical
technique and classified according to degree of
intensity regarding to dependable scoring system ,
also ten cases taken as control group from normal
ovarian tissue.
Results :-Thirty eight sample of surface ovarian
carcinoma were collected , twenty six were serous
ovarian carcinoma , eleven cases were mucinous
carcinoma type and one case was endometriod
carcinoma . The samples were classified according to
their histological types and according to their grading .
The mean age of SC type was 54.52 with SD 7.17
while the mean age of mucinous carcinoma was 49.36
with SD 4.9. There is no significant relation between
each type and grading system ( P Value = 0.9 ) ,also
there is no significant relation between age group
distribution and types of ovarian carcinoma ( P value
= 0.14 ).Instate that statically no significant relation
between intensity of expression Her2/neu and high
grading of each types of collected sample ( P value
=0.22) and this may be due to small sample size but
still there are obvious criteria showing that her2/neu
expression relatively increase in higher grade of each
types of studied ovarian surface epithelial carcinoma.
Conclusion :-In conclusion, the overexpression of
the HER-2/neu gene product appears to be an unusual
occurrence in early epithelial ovarian cancer and may
occur less frequently than in advanced disease. Early
ovarian cancer will eventually progress to advanced
disease if undiagnosed and untreated, then, HER-
2/neu overexpression does not appear to be a general
early event in the development of ovarian cancer.
Instead, it seems that increased expression develops in
many instances after the malignant phenotype has
already arisen.
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters wer
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