Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate

Abstract: E2F6 is a member of the E2F family of transcription factors involved in regulation of a wide variety of genes through both activation and repression. E2F6 has been reported as overexpressed in breast cancers but whether or not this is important for tumor development is unclear. We first checked E2F6 expression in tumor cDNAs and the protein level in a range of breast cancer cell lines. RNA interference-mediated depletion was then used to assess the importance of E2F6 expression in cell lines with regard to cell cycle profile using fluorescence-activated cell sorting and a cell survival assay using (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The overexpression of E2F6 was confirmed in breast tumor cDNA samp

Multiple single-nucleotide polymorphisms (SNPs) located in the intergenic region between estrogen receptor 1 and CCDC170 (especially at rs3757318) are thought to be associated with breast cancer risk. additionally, the serum level of vitamin D is believed to be linked to different aspects of breast carcinogenesis.

STAG proteins, which are part of the cohesin complex and encoded by the STAG genes, are known as Irr1/Scc3 in yeast and as SA/STAG/stromalin in mammals. There are more variants as there are alternate splice sites, maybe three open reading frames (ORFs) code for three main proteins, including: SA1 (STAG1), SA2 (STAG2) and SA3 (STAG3). The cohesin protein complex has various essential roles in eukaryotic cell biology. This study compared the expression of the STAG1 gene in four different breast cancer cell lines, including: MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 and normal breast tissue. RNA was extracted from these cell lines and mRNA was converted to cDNA, and then expression of the STAG1 gene was quantified by three sets of specific prim

Ceruloplasmin is considered the main copper transport protein which is proposed to have a role in cancer. Ceruloplasmin is an acute phase reactant and antioxidant enzyme, has been found to be increased in sera of patients with several types of cancers including breast cancer.

The aim of present study was to determine of ceruloplasmin oxidase activity, specific activity, iron concentration in sera of patients with breast cancer and comparing with healthy group, and the ability of using enzyme as a tumor marker for breast cancer.

This study was performed from November 2018 to January 2019, blood samples were collected from breast cancer patients in Nanakeli Hospital in Erbil city. Study was included (65) female patients wit

The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

As modern radiotherapy technology advances, radiation dose and dose distribution have improved significantly. As part of a natural evolution, there has recently been renewed interest in therapy, particularly in the use of heavy charged particles, because these types of radiation serve theoretical advantages in all biological and physical aspects. The interactions of alpha particle with matter were studied and the stopping powers of alpha particle with Breast Tissue were calculated by using Beth-Bloch equation, Zeigler's formula and SRIM software, also the Range and Liner Energy Transfer (LET) and Breast Thickness As well as Dose and Dose equivalent for this particle were calculated by using Mat lab language for (0.01-200) MeV alpha ene

Breast carcinoma is one of the greatest popular neoplasms in females. It is a major reason of demise in the world, and it is the first cancer in ranking diagnosed in Iraqi women. This study aimed to determine aminoacyltRAN-synthetase complex interacting multifunctional protein 1 and liver enzymes levels in Iraqi females with stage II breast malignance, and study the effect of chemotherapy (after surgery) on these markers. This study included 50 females patients with stage II breast malignance (before and after surgery and second dose of chemotherapy) attending the Oncology Teaching Hospital in Medical City/ Baghdad, in addition to 20 persons as controller group were chosen without any chronic diseases. Their ages ranged from (30-55) years.