Out of 150 clinical samples, 50 isolates of Klebsiella pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 25 (50%) of isolates were resistant to gentamicin (≥16µg/ml), 22 (44%) of isolates were resistant to amikacin (≥64 µg/ml), 21 (42%) of isolates were resistant to ertapenem (≥8 µg/ml), 18 (36%) of isolates were resistant to imipenem (4- ≥16µg/ml), 43 (86%) of isolates were resistant to ceftriaxone (4- ≥64 µg/ml), 42 (84%) of isolates were resistant to ceftazidime (16-64 µg/ml), and 40 (80%) of isolates were resistant to cefepime (4- ≥16µg/ml). Co-Resistance for both β-lactams and aminoglycosides were detected among 25 (50%) of K. pneumoniae isolates. The extended spectrum beta-lactamases (ESBLs) were detected among 25 (50%) of K. pneumoniae isolates. Screening of 16S rRNA methylases encoding genes revealed that armA was found in 5 (10%) of K. pneumoniae isolates, whereas rmtB was not found among K. pneumoniae isolates. DNA sequencing of armA revealed that the presence of missense mutations in which affected in the translation of protein by substitutions of amino acids, leading to increase the resistance values of MICs for gentamicin and amikacin. These variants were registered in NCBI at the accession number LC373258. The phylogenetic tree of armA variants showed a slight deviation of these variants from K. pneumoniae species.
Background: The occurrence of seizures in bacterial meningitis is important, as it has been reported to increase the risk of complications; however, its frequency and predictors are not well studied yet. Objective: To assess the frequency, clinical, and biochemical predictors of seizures in children with acute bacterial meningitis. Method: A cross-sectional study recruited confirmed acute bacterial meningitis cases based on positive CSF culture and sensitivity among children aged 2 months to 15 years admitted to the Central Child Teaching Hospital emergency department in Iraq. Patients were divided into two groups based on seizure at presentation time. Demographic characteristics [age, gender, residence, duration of fever and disease, prese
... Show MoreThe aim of the work is synthesis and characterization of bidentate ligand [3-(3-acetylphenylamino)-5,5-dimethylcyclohex-3-enone][HL], from the reaction of dimedone with 3-amino acetophenone to produce the ligand [HL], the reaction was carried out in dry benzene as a solvent under reflux. The prepared ligand [HL] was characterized by FT-IR, UV-Vis spectroscopy, 1H, 13C-NMR spectra, Mass spectra, (C.H.N) and melting point. The mixed ligand complexes were prepared from ligand [HL] was used as a primary ligand while 8-hydroxy quinoline [HQ] was used as a secondary ligand with metal ion M(Π).Where M(Π) = (Mn ,Co ,Ni ,Cu ,Zn ,Cd and Pd) at reflux ,using ethanol as a solvent, KOH as a base. Complexes of the composition [M(L)(Q)] with (1
... Show MoreThe therapeutic value of the phenolic component and pure thymol was well known; this study comprised the extraction of crude phenol from two plants (Thymus vulgaris and Artemisia annua) which contain thymol with pure thymol and evaluate their effect on hematological and histological by using three different concentrations of each plant extract and pure thymol to tested them on lab mice. All the mice were allowed free access to water and feed for 21 days in laboratory conditions; orally, pure water was administered to the control mice (group I), while groups II, III, and IV were given orally with T. vulgaris, A. annua, combination of last two crude phenol plant extract 50:50 and pure thymol respectively. The levels of CHO, TRI, and HDL were
... Show MoreThe aim of the work is synthesis and characterization of bidentate ligand [3-(3-acetylphenylamino)-5,5-dimethylcyclohex-3-enone][HL], from the reaction of dimedone with 3-amino acetophenone to produce the ligand [HL], the reaction was carried out in dry benzene as a solvent under reflux. The prepared ligand [HL] was characterized by FT-IR, UV-Vis spectroscopy, 'H, 8C-NMR spectra, Mass spectra, (C.H.N) and melting point. The mixed ligand complexes were prepared from ligand [HL] was used as a primary ligand while 8-hydroxy quinoline [HQ] was used as a secondary ligand with metal ion M(IT).Where M(IT) = (Mn ,Co ,Ni ,Cu ,Zn ,Cd and Pd) at reflux ,using ethanol as a solvent, KOH as a
... Show MoreWith the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative
... Show MoreSeveral Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff
... Show MoreDeepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this asp
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