The invasion and spread of cancer cells are two of the most notable characteristics of malignant tumors. Recent studies suggest that the epithelial-mesenchymal transition (EMT) has been linked to this significant occurrence. It is linked to the absence of the epithelial brow and the presence of mesenchymal facial hair. The aims of the present study were to explore the immunohistochemical staining of vimentin and E-cadherin ex vivo as EMT markers and assess their potential as predictive biomarkers for transitional cell cancer (TCC). In this study, 55 paraffin-embedded biopsies from TCC patients and 10 autopsies that appeared to be normal were included. Immunohistochemistry was used to produce patterns of vimentin and E-cadherin expression. W

 In this paper,we estimate the parameters and related probability functions, survival function, cumulative distribution function , hazard function(failure rate) and failure  (death) probability function(pdf) for two parameters Birnbaum-Saunders distribution which is fitting the complete data for the patients of  lymph glands cancer. Estimating the parameters (shape and scale) using (maximum likelihood , regression quantile and shrinkage) methods and then compute the value of mentioned related probability  functions depending on sample from real data which describe the duration of survivor for patients who suffer from the lymph glands cancer based on diagnosis of disease or the inter of patients in a hospital for perio

 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

One hundred twelve urine samples were collected from Baghdad hospitals and examined by different identification techniques. Seventy isolates (62.5%) were diagnosed as Escherichia coli after microscopic and cultural identifications. The result of PCR product electrophoresis on the isolates showed that thirteen isolates (18.57%) have Pap E gene which are uropathogenic E. coli. Antibiotic susceptibility test was done, and four high resistant strains were mixed with aqueous extract of Quercus infectoria plant in 96 well ELISA plate and incubated for different times. After 0, 6, and 12 hr. of incubation, the effect of the plant extract on the bacterial growth was determined by ELISA reader, and the effect on the expression of P

Despite extensive investigations, an effective treatment for sepsis remains elusive and a better understanding of the inflammatory response to infection is required to identify potential new targets for therapy. In this study we have used RNAi technology to show, for the first time, that the inducible lysophosphatidylcholine acyltransferase 2 (LPCAT2) plays a key role in macrophage inflammatory gene expression in response to stimulation with bacterial ligands. Using siRNA- or shRNA-mediated knockdown, we demonstrate that, in contrast to the constitutive LPCAT1, LPCAT2 is required for macrophage cytokine gene expression and release in response to TLR4 and TLR2 ligand stimulation but not for TLR-independent stimuli. In addition, cells transfe