Gold nanoparticles (Au NPs) have been synthesized via reduction of sodium tetrachloroaurate dihydrate (NaAuCl4.2H2O) with 2-(2-methyl-5-amino -1H-imidazol-1-yl) ethanol (2-MAE) in presence and absence of ascorbic acid as reducing and stabilizing agents. The resulting Au NPs were characterized by UV–Vis spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD), FT-IR spectroscopy. The absorption spectra of gold nanoparticles solutions in the uv-visible and near IR regions were studied at different amine concentrations and pH media.

Gold nanoparticles (Au NPs) have been synthesized via reduction of sodium tetrachloroaurate dihydrate (NaAuCl4.2H2O) with 2-(2-methyl-5-amino -1H-imidazol-1-yl) ethanol (2-MAE) in presence and absence of ascorbic acid as reducing and stabilizing agents. The resulting Au NPs were characterized by UV–Vis spectroscopy, scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD), FT-IR spectroscopy. The absorption spectra of gold nanoparticles solutions in the uv-visible and near IR regions were studied at different amine concentrations and pH media.

     The human epidermal growth factor receptor-2 (HER2) gene plays a critical role in breast cancer development and progression. HER2 overexpression characterizes a biologically and clinically aggressive breast cancer subtype. In this study, 60 samples from Iraqi women with breast cancer were collected and investigated for HER2 protein in the tissue by immunohistochemistry. Also, 20 samples from healthy Iraqi women were used as a control. The results showed that 18 (30 %) patients expressed the HER2 protein. A molecular study for single nucleotide polymorphism (SNP) was conducted on samples metastasizing to lymph nodes. DNA was extracted and polymerase chain reaction (PCR) was performed to amplify e

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

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

This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Background : Breast cancer is the most common cancer of
women. When breast cancer is detected and treated early,
the chances for survival are better. Surgery is the most
important treatment for non-metastatic breast cancer.
Al-Kindy Col Med J 2008 Vol.5(1) 40 Original Article
Objectives : The aim of this study is to review different
clinical presentation and to evaluate types of surgical
procedures and complications in treatment of nonmetastatic breast cancer.
Method : During the period from Jun 1998 to May 2005,
93 patients with non-metastatic breast cancer were
diagnosed and treated surgically in 2 hospitals in Baghdad (
Hammad Shihab military hospital and Al-Kindy teaching
hospital).
Results : Wo

Breast cancer is the second deadliest disease infected women worldwide. For this
reason the early detection is one of the most essential stop to overcomeit dependingon
automatic devices like artificial intelligent. Medical applications of machine learning
algorithmsare mostly based on their ability to handle classification problems,
including classifications of illnesses or to estimate prognosis. Before machine
learningis applied for diagnosis, it must be trained first. The research methodology
which isdetermines differentofmachine learning algorithms,such as Random tree,
ID3, CART, SMO, C4.5 and Naive Bayesto finds the best training algorithm result.
The contribution of this research is test the data set with mis