Neuroendocrine differentiation has been mentioned in many cancers of non-neuroendocrinal organs, involving the gastrointestinal tract. In contrast, the correlation of focally diffused neuroendocrine differentiation in colorectal adenocarcinoma with neuroendocrine cell hyperplasia has not been somewhat reported. The objective of this research is to study the relationship between neuroendocrine cell hyperplasia and neuroendocrine differentiation in colorectal adenocarcinoma and to find the correlation of neuroendocrine differentiation and VEGF expression with clinicopathological parameters of colorectal adenocarcinoma. Methods employed in the current study were including eighty-one patients with colorectal cancer. Formalin fixed paraffin e

This study was carried out in Plant Tissue Culture Labs, College of Agricultural Engineering Sciences, University of Baghdad from November 2018 to June 2019. Fresh stem cuttings, 5 cm long were selected from 6-month old C-35 Citrange rootstock. Five concentrations of BA (0, 1, 1.5, 2 and 2.5 mg.L-1) were studied and addition of meta-Topolin (mT) at four concentrations (0, 1, 5 and 10 mg.L-1) was also studied to find out its effect individually on shoot number and shoot length in multiplication stage. Rooting media supplemented with four concentrations of IBA (0, 1, 2 and 3 mg.L-1) was also studied to find out its effect on rooting percentage, root number and root length. Results showed that BA as concentration of 2.5mg.L-1 significantly gav

The last decade has seen a variety of modifications of glass-ionomer cements (GICs), such as inclusion of bioactive glass particles and dispensing systems. Hence, the aim was to systematically evaluate effect of mixing modes and presence of reactive glass additives on the physical properties of several GICs.

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall