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

The study aimed to measure the concentration of some heavy metal elements and represented by (Pb, Cd,Cu) through the use of atomic absorption spectrometer Flame AAS-7000 type SHIMADZU underwent a process modeling to twelve samples from the soil of electricity Dezlat al Jadiriyah station in the Baghdad University compound at a depth of 30-60 cm from the surface and divided the samples into two groups first included six samples from inside the station while the second included six samples from outside the station. For the element of Pb was higher concentration reached by 29.32ppm and less concentration 17.56ppm. were elements Cd and Cu are growing and less and proportions of certain while the highest concentration of copper 9.69 ppm and le

In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

All the prepared metal complexes of Pt (IV), Au(III), Rh (III), Co (II) and V(IV) with new ligand sodium [5-(p-nitro phenyl)-/4-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide] (TRZ.DTC) have been synthesized and characterized in solid state by using flame atomic absorption, elemental analysis C.H.N.S, FT-IR ,UV-Vis Spectroscopy, conductivity and magnetic susceptibility measurements. The nature of the complexes formed in ethanolic solution has been studied following the molar ratio method also was studied stability constant and found to be stable in molar ratio1:1 of VL (IV) and CoL(II) while Pt(IV), Au(III) and Rh(III) complexes stable in molar ratio 1:2 as well as the molar absorptivity for these complexes were calculated. From the prev

Azo-Schiff base compounds (L1 and L2) have been synthesized from the reaction of m-hydroxy benzoic acid with 1,5-dimethyl-3-[2-(5-methyl-1H-indol-3-yl)-ethylimino]-2-phenyl-2,3- dihydro-1H-pyrazol-4-ylamine and with 3-[2-(1H-indol-3-yl)-ethylimino]-1,5-dimethyl-2-phenyl- 2,3-dihydro-1H-pyrazol-4-ylamine. The free ligands and their complexes were characterized based on elemental analysis, determination of metal, molar conductivity, (1H, 13C) NMR, UV–vis, FT-IR, mass spectra and thermal analysis (TGA). The molar conductance data revealed that all the complexes are non-electrolytes. The study of complex formation via molar ratio in DMF solution has been investigated and results were consistent to those found in the solid complexes with a rat

In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty.

He mentioned in this article the main types of corruption, which are political, moral, financial and administrative. Others may add other types of corruption, such as religious, scientific, media, informational and statistical corruption. At the global level, the focus is largely on financial corruption, although other types of corruption are no less bad than it. Financial corruption can be defined as all financial deviations in violation of general laws or the provisions of regulations, legislation, and procedures regulating the work of the state, private institutions and individuals and applied in state institutions and the private sector in general and inconsistent with the controls and instructions of financial control.

In th

Background: Neudesin is a peptide secreted in brain and adipose tissues that has neural and metabolic functions. Its role as regulator of energy expenditure leads to assumption that its level may be regulated depending on thyroid gland pathology. Objective: This study aimed to investigate serum neudesin levels in patients with thyroidism and to evaluate1 any possible relationship between plasma neudesin levels and thyroid hormone levels. Methods: The study included 100 women with newly diagnosed thyroidisim were subdivided into two groups: hyperthyroidism group (50 female patients with age ranged from 18 to 60 years) and hypothyroidism group (50 female patients with age ranged from 18 to 75 years). A control group (30 healthy females with a

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc