Several toxigenic cyanobacteria produce the cyanotoxin (microcystin). Being a health and environmental hazard, screening of water sources for the presence of microcystin is increasingly becoming a recommended environmental procedure in many countries of the world. This study was conducted to assess the ability of freshwater cyanobacterial species Westiellopsis prolifica to produce microcystins in Iraqi freshwaters via using molecular and immunological tools. The toxigenicity of W. prolifica was compared via laboratory experiments with other dominant bloom-forming cyanobacteria isolated from the Tigris River: Microcystis aeruginosa, Chroococcus turigidus, Nostoc carneum, and Lyngbya sp. signifi

A significant increase in the incidence of non-O157 verotoxigenic Escherichia coli (VTEC) infections have become a serious health issues, and this situation is worsening due to the dissemination of plasmid mediated multidrug-resistant microorganisms worldwide. This study aims to investigate the presence of plasmid-mediated verotoxin gene in non-O157 E. coli. Standard microbiological techniques identified a total of 137 E. coli isolates. The plasmid was detected by Perfectprep Plasmid Mini preparation kit. These isolates were subjected to disk diffusion assay, and plasmid curing with ethidium bromide treatment. The plasmid containing isolates were subjected to a polymerase chain reaction (PCR) for investigating

Background: The anticancer impact of Epigallocatechin gallate (EGCG) the highly active polyphenol of green tea was abundantly studied.  Though, the exact mechanism of its cytotoxicity is still under investigation. Objectives: Hence, the current study designed to investigate the molecular target of EGCG in HepG2 cells on thirteen autophagy- and/or apoptosis- related genes. Methods: The apoptosis detection analyses such as flow cytometry and dual apoptosis assay were used. The genes expression profile was explored by the real-time quantitative-PCR. Results: EGCG increases G0/G1 cell cycle arrest and the real-time apoptosis markers proteins leading to stimulate apoptos

Background: The isatin molecule is present in many natural substances, including plants and animals, and is used to prepare compounds with various biological activities. Objectives: To synthesize a new series of isatin derivatives with the expectation that they will have antimicrobial activity. Methods: Thiazole Schiff bases were synthesized from various Mannich bases of isatin to evaluate their antimicrobial properties. Initially, Mannich bases (2a–e) were synthesized by reacting isatin with formaldehyde and different secondary amines. Subsequently, they were treated with 2-aminothiazole to yield the final compounds (3a–e). Spectroscopic characterization was done via FT-IR and 1H-NMR. The antimicrobial screening was conducted o

Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet