Endophytic fungi live inside plants or any part of them without creating any visible pathogenic signs. Endophytic fungi are found within medicinal plants and have shown strong biologic activity, such as anticancer and antioxidant activities, as well as producing extracellular enzymes. In this study, different fungal strains were isolated from the leaves of the medicinal plant Ziziphus spina, including Aspergillus flavus, Aspergillus fumigatus, Aspergillus niger, Cladosporium sp., Rhizopus sp., and Mucor sp. Extracellular enzymes have been quantified using agar plate-based methods in which fungi were grown in specified growth media to detect the enzymes produced. The results showed that A. niger has the highest ability to produce amy

In this study, (50–110 nm) magnetic iron oxide (α-Fe2O3) nanoparticles were synthesized by pulsed laser ablation of iron target in dimethylformamide (DMF) and sodium dodecyl sulfate (SDS) solutions. The structural properties of the synthesized nanoparticles were investigated by using Fourier Transform Infrared (FT-IR) spectroscopy, UV–VIS absorption, scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD). The effect of laser fluence on the characteristics of these nanoparticles was studied. Antibacterial activities of iron oxide nanoparticles were tested against Gram-positive; Staphylococcus aureus and Gram-negative; Escherichia coli, Pseudomonas aeruginosa and Serratia marcescens. The results sh

This study was established to investigate the correlation between the expression of matrix metalloproteinases (MMP-1) and the pathogenesis of osteoarthritis (OA). Blood samples were collected from 55 female patients with inflammatory OA and controls for estimation of serum (MMP-1) levels. In the current study, there is significant increase (p<0.001) in the mean of serum MMP-1 levels in osteoarthritis females (4027.73 ± 1345.28 pg/ml) than that in control females (798.76 ± 136.79 pg/ml). It was concluded that MMP-1 may be associated with the pathogenesis of osteoarthritis.

Specialized Escherichia coli (E. coli) isolates, called uropathogenic E. coli (UPEC), cause most of urinary tract infections (UITs). Once bacteria reached the urinary tract of the host, they have to adhere to the host cell for the colonization. For this purpose, bacteria have different structures including fimbrial adhesins. Most of the UPECs contain type 1 fimbriae encoded by fim operon (fimB, E, A, I, C, D, F, G, H) which is responsible for the adhesive ability in these isolates. Ninety-four isolates of UPEC were obtained from UTI patients in Baghdad hospitals and their diagnosis were confirmed by the PCR method using 16srDNA as a housekeeping gene. The UPEC isolates were tested for their ability of adherence to the urothelial cells obtai

For two years, from January 1995 till December 1996, a survey on helminth parasites of aquatic birds of Bahr Al-Najaf depression, mid Iraq, was achieved. A total of 663 birds, belonging to 11 species, were captured and examined for helminth parasites. These birds were infected with seven trematodes (Notocotylus gibbus, Cyclocoelum mutabile, Echinostoma chloropodis, Patagifer parvispinosus, Psilochasmus oxyurus, Diplostomum spathaceum and Apharyngostrigea cornu), seven cestodes (Paricterotaenia porosa, Dicranotaenia tsengi, Diorchis brevis, D. inflatus, Tatria acanthorhyncha, T. decacantha and Diplophallus polymorphus) and four nematodes (Capillaria sp., Eustrongylides tubifex, Con

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar