Background: While two-thirds of breast cancers express hormone receptors for either estrogen (ER) and/or progesterone (PR) , genetically altered PI3K pathway was found in more than 70% of ER-positive breast cancers.An aberrant activity of cyclin-dependent kinase 1 (CDK1) in a wide variety of human cancers has selectively constituted an attractive pharmacological targets in MYC-dependent human breast cancer cells.

Aim of the study:  Role of p110-beta as well as and CDK 1  in the pathogenesis of subset of breast cancers and contribution in their carcinogenesis.

Type of the study: is a retrospective study

Methods: This retr

KE Sharquie, AA Al-Nuaimy, WJ Kadhum, Saudi medical journal, 2006 - Cited by 3

Abstract

The Classical Normal Linear Regression Model Based on Several hypotheses, one of them is Heteroscedasticity as it is known that the wing of least squares method (OLS), under the existence of these two problems make the estimators, lose their desirable properties, in addition the statistical inference becomes unaccepted table. According that we put tow alternative,  the first one is  (Generalized Least Square) Which is denoted by (GLS), and the second alternative is to (Robust covariance matrix estimation) the estimated parameters method(OLS), and that the way (GLS) method neat and certified, if the capabilities (Efficient) and the statistical inference Thread on the basis of an acceptable

The research aims to improve operational performance through the application of the Holonic Manufacturing System (HMS) in the rubber products factory in Najaf. The problem was diagnosed with the weakness of the manufacturing system in the factory to meet customers' demands on time within the available resources of machines and workers, which led to time delays of Processing and delivery, increased costs, and reduced flexibility in the factory, A case study methodology used to identify the reality of the manufacturing system and the actual operational performance in the factory. The simulation was used to represent the proposed (HMS) by using (Excel 2010) based on the actual data and calculate the operational performance measures

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

In most manufacturing processes, and in spite of statistical control, several process capability indices refer to non conformance of the true mean (µc ) from the target mean ( µT ), and the variation is also high. In this paper, data have been analyzed and studied for a blow molded plastic product (Zahi Bottle) (ZB). WinQSB software was used to facilitate the statistical process control, and process capability analysis and some of capability indices. The relationship between different process capability indices and the true mean of the process were represented, and then with the standard deviation (σ ), of achievement of process capability value that can reduce the standard deviation value and improve production out of theoretical con

The nanostructured MnO2 /carbon fiber (CF) composite electrode was prepared using the anodic electrodeposition process. The crystal structure and morphology of MnO2 particles were determined with X-ray diffraction and field-emission scanning electron microscopy. The electrosorptive properties of the prepared electrode were investigated in the removal of cadmium ions from aqueous solution, and the effect of pH, cell voltage, and ionic strength was optimized and modeled using the response surface methodology combined with Box–Behnken design. The results confirm that the optimum conditions to remove Cd(II) ions were: pH of 6.03, a voltage of 2.77 V, and NaCl concentration of 3 g/L. The experimental results showed a good fit for the Freundli

In this research, the electrical characteristics of glow discharge plasma were studied. Glow discharge plasma generated in a home-made DC magnetron sputtering system, and a DC-power supply of high voltage as input to the discharge electrodes were both utilized. The distance between two electrodes is 4cm. The gas used to produce plasma is argon gas which flows inside the chamber at a rate of 40 sccm. The influence of work function for different target materials (gold, copper, and silver), - 5cm in diameter and around 1mm thickness - different working pressures, and different applied voltages on electrical characteristics (discharge current, discharge potential, and Paschen’s curve) were studied. The results showed that the discharge cur