The non-specific response of immunity has developed as the initial barrier for human protection from invading pathogens, which comprises certain pathogen recognition receptors (PRR) for instance toll-like receptors (TLRs). Toll like receptor 2 (TLR 2) is capable of recognizing pathogen associated molecular patterns (PAMP) coded by Mycobacterium tuberculosis. To evaluate TLR 2 level in sera of pulmonary tuberculosis (TB) patients. About 120 subjects, involving 80 patients with pulmonary TB including 40 multiple drug resistance (MDR), 20 recently diagnosed pulmonary TB (RD) and 20 recurrent TB patients named as old cases (OC), in addition to 40 apparently healthy individuals were studied as control group. Sera from 68 TB patients and 20 healthy controls were obtained for measuring TLR 2 levels by enzyme linked immunosorbent assay (ELISA). The present result revealed that serum levels of TLR 2 showed there is no significant differences between each patient's group and control except OC group given that, has decreased significantly (p<0.05). The mean ±SD of TLR 2 level in MDR, RD, OC and controls were 4.0± 2.4, 3.4±1.4, 2.2±0.9 and 4.1± 3.0 ng/ml, respectively. The results exhibited that during treatment of tuberculosis, patients with pulmonary tuberculosis showed elevated TLR 2 concentration, which looks probably in charge of regulating inflammation and infection. Consequently, this study proposes that killing of MTB could occur in the time of disease management because of effective treatment, in addition to activation and releasing of different immune system mediators via TLR 2.
The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s
... Show More
(4)
(1)
This study aimed to study the inhibition activity of purified bacteriocin produced from the local isolation Lactococcuslactis ssp. lactis against pathogenic bacteria species isolated from clinical samples in some hospitals Baghdad city. Screening of L. lactis ssp. Lactis and isolated from the intestines fish and raw milk was performed in well diffusion method. The results showed that L. lactis ssp. lactis (Lc4) was the most efficient isolate in producing the bacteriocin as well observed inhibitory activity the increased that companied with the concentration, the concentration of the twice filtrate was better in obtaining higher inhibition diameters compared to the one-fold concentration. The concentrate
... Show MoreThis study has applied digital image processing on three-dimensional C.T. images to detect and diagnose kidney diseases. Medical images of different cases of kidney diseases were compared with those of healthy cases. Four different kidneys disorders, such as stones, tumors (cancer), cysts, and renal fibrosis were considered in additional to healthy tissues. This method helps in differentiating between the healthy and diseased kidney tissues. It can detect tumors in its very early stages, before they grow large enough to be seen by the human eye. The method used for segmentation and texture analysis was the k-means with co-occurrence matrix. The k-means separates the healthy classes and the tumor classes, and the affected
... Show More
Abstract: The M(II) complexes [M2(phen)2(L)(H2O)2Cl2] in (2:1:2 (M:L:phen) molar ratio, (where M(II) =Mn(II), Co(II), Cu(II), Ni(II) and Hg(II), phen = 1,10-phenanthroline; L = 2,2'-(1Z,1'Z)-(biphenyl-4,4'-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-1- ylidene)diphenol] were synthesized. The mixed complexes have been prepared and characterized using 1H and13C NMR, UV/Visible, FTIR spectra methods and elemental microanalysis, as well as magnetic susceptibility and conductivity measurements. The metal complexes were tested in vitro against three types of pathogenic bacteria microorganisms: Staphylococcus aurous, Escherichia coli, Bacillussubtilis and Pseudomonasaeroginosa to assess their antimicrobial properties. From this study shows that a
... Show More
(22)
(5)