Background: Non-small cell lung cancer (NSCLC) is caused of 85% of all lung cancers. Among the most important factors for lung tumor growth and proliferation are the tyrosine kinase receptors that coded by the epidermal growth factor recep-tor (EGFR) gene. Activation of EGFR ultimately leads to developing of lung cancer. The present study was undertaken with an objective to detect EGFR mutations in bronchial wash from Iraqi patients with NSCLC before treatment. Methods: DNA was extracted from bronchial wash samples collected from 50 patients with NSCLC by using a Qiamp DNA Mini Kit (Qiagen, Hilden, Germany). Then, EGFR mutations were determined by using real-time RCR combined with two technologies, Amplification Refractory Mutation System (ARMS) and Scorpions. Results: A point mutation, G719X, in exon−18 with three different profiles, G719A, G719S, and G719C was significantly diffused in EGFR. L858R in the same exon and T790M in exon−20 was also detected. While no deletions in exon −19, and no substitutions or insertions in exon −20 were found. Moreover, no significant differences (P≤0.05) in EGFR mutations were seen between males (28.57%) and females (30.76%). In contrast, EGFR mutations were significantly (P≤0.05) prevalent in smoker’s males (26.6%) than females 6.6%). Conclusion: Using the bronchial wash samples was efficient for detection of mutations in lung cancer. Moreover, Iraqi patients with NSCLC were discriminated in EGFR genotype; the point mutation G179X in exon−20 was dominant and L858R in the same exon and T790M in exon−20 were detected while no mutations in exon− 19 and −20 were investigated.
Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification
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Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,
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Introduction: Rheumatoid arthritis (RA) is one of the most prevalent systemic inflammatory diseases worldwide. Cardiac complications present the most common mortality cause among RA patients. One of the most important comorbid conditions with RA is diabetic hyperglycemia mainly type 2 diabetes mellitus (T2DM). Aim of the study: The present study was conducted to assess prevalence of T2DM among patients diagnosed with RA from Iraq. Methodology: We included a randomly selected 100 rheumatoid arthritis. All included patients were subjected to anthropometric measurements, diabetic profile assessment and ESR, CRP and rheumatoid factor measurement. Results: Among the included RA patients, 28 patients were diagnosed with new-onset DM. Our
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Background: the coronavirus leads to upper respiratory tract-associated manifestations like nasal congestion, sore throat, and smell disorder
Objectives: To reveal the impact of COVID-19 pandemic on otolaryngology symptoms using our daily medical practice.
Subject and Methods: A cross-sectional study that was carried on in the isolation wards at Al-Kindy and Al-Nu’man Teaching Hospitals during three months from the 1st of Jun. till the end of Aug. 2020. It included 1270 patients who were diagnosed with COVID-19 infection seen in the ENT consultation clinic and admitted to the isolation wards.
Results: Otolaryngological manifestations were shown
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Background: Because of many factors play a role in the developing of late lower arch crowding, therefore the objective of the current study is to do vertical analysis for subjects with late lower dental arch crowding. The conducted study is the first attempt to do vertical analysis for Iraqi subjects with late lower arch crowding to see if there is a vertical discrepancy in such patients. Subjects and methods: Eighty subjects were selected according to certain inclusion criteria from patients attending the Orthodontic Department in the College of Dentistry, Baghdad University, patients ranged between 18-25 years old. The 80 patients were divided into two groups (crowding and normal), 40 patients each (20 males and 20 females). A study cast
... Show MoreBackground. Nocturnal enuresis (NE), defined as intermittent involuntary urine leakage during sleep, affects approximately 16% of children at age 5 and 10% at age 7, with prevalence declining with age. Aim. To evaluate the urodynamic features of patients with non-monosymptomatic nocturnal enuresis (NMNE). Methods. This cross-sectional study was conducted from June 2015 to September 2020 in a surgical subspecialty hospital within a major medical city complex, including 237 patients. Eligible patients were older than seven years, diagnosed with NMNE, and had refractory enuresis, defined as persistent symptoms despite at least six months of continuous medical treatment. All patients underwent a detailed history, bladder diary review, c
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Background: The novel coronavirus disease (COVID-19) is caused by Severe acute respiratory syndrome coronavirus 2 (SARS-Cov2) which utilizes angiotensin converting enzyme2 (ACE2) to invade the host cells. This membrane-bound peptidase is widely distributed in the body; its activity antagonizes the renin-angiotensin-aldosterone system (RAAS). Once SARS-Cov2 enters the cell, it causes downregulation of ACE2, resulting in the unopposed activation of RAAS. The unregulated activity of the RAAS system can deteriorate the prognosis in COVID-19 patients. A soluble form of ACE2 (sACE2) was reported to have a role in the SARS-Cov2 invasion of the susceptible cells.
Aim of the study: This study aims to inve
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