Background: Mobile phones are approximately widely used everywhere like in hospital wards, clinics and universities as well as biomedical laboratories. They have become very important tool in students’ life. In contrast, these tools carry many harmful bacteria which are responsible for infectious diseases in human because they serve as a reservoir for different pathogens. Current study was aimed to isolate bacteria from students’ mobile phones at the Institute of Medical Technology/Al-Mansour/The Middle Technical University, Baghdad, Iraq. Also, the study investigated microbial resistance to many antimicrobial agents as well as the appropriate remedial measures. Method: Four hundred and fifty swabs from mobile phones were collected from

Used in the study especially calibrated Erwa to determine the number of neighborhood or the Alayoshi number of bacteria in the count modeling and casting method dishes in addition to using the drop method yielded significant results for a match between the methods used ..

Five serological methods for detection of Brucella were compaired in this study, Four of the methods are commonely used in the detections:- 1-Rose-Bengal: as primary screening test which depends on detecting antibodies in the blood serum. 2-IFAT: which detects IgG and IgM antibodies in the serum. 3-ELISA test: which detects IgG antibodies in the serum. 4-2ME test: which detects IgG antibodies The fifth methods. It was developed by a reasercher in one of the health centers in Baghdad. It was given the name of spot Immune Assay (SIA). Results declares that among (100) samples of patients blood, 76, 49, 49, 37, and 28. samples were positive to Rose Bengal, ELISA, SIA, 2ME and IFAT tests, respectively. When efficiency, sensitivity and specific

The current study focuses on the bacterium Acinetobacter baumannii due to its importance as a nosocomial infections source in addition to its increased resistance against antibiotics. Different clinical and hospital environment samples were collected, and cultured on A. baumannii selective media: Leed Acinetobacter agar and Herellea agar. A. baumannii have been identified by traditional methods, followed by confirmation using molecular identification to detect bla_{oxa-51 like} gene which is considered a diagnostic gene since it is present in genome of all A. baumannii strains. The result was, nineteen bacterial isolates of A.baumannii were obtained, from twenty-seven suspected isolate

Background: Nanotechnology has emerged as a pivotal domain in material science research with extensive applications across various sectors including biotechnology and medicine. Nanoparticles offer unique properties facilitating advancements in nanobiotechnology, particularly in nanomedicine, to combat bacterial infections and antibiotic resistance. This study aimed to determine the application of nanoparticles, specifically nano-TiO2, in treating plasmid-mediated antibiotic resistance in both Gram-negative and Gram-positive bacteria. Method: We evaluated antibiotic and nanomaterial sensitivity through disc diffusion and broth microdilution assays. Plasmid curing experiments were conducted using varying concentrations of nano-TiO2 an

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

Adhesion (type 1 fimbriae) and host defense avoidance mechanisms (capsule or lipopolysaccharide) have been shown to be prevalent in Escherichia coli isolates associated with urinary tract infections. In this work, 50 uropathogenic Escherichia coli (UPEC) isolated from children with urinary tract infections were genotypically characterized by polymerase chain reaction (PCR) assay. We used two genes; fimH and kpsMTII, both of them previously identified in uropathogenic E.coli (UPEC) isolates. The PCR assay results identified fimH (90.0)% and kpsMTII (72.0)% isolates. In the present study, was also demonstrated that these genes may be included in both or one of them within a single isolate.