The study included the collection of 75 bronchial wash samples from patients suspected to have lung cancer. These samples were subjected to a diagnostic cytological study to detect the dominant type of lung cancer. It was noticed that 33 patients proved to have a lung cancer out of 75 (44%) of these, 19 cases (57.6%)were diagnosed having Squamus cell carcinoma,7cases (21.21%) showed Adenocarcinoma ,6 cases (18.18%) were having small cell carcinoma while only one case (3.03%)was large cell carcinoma .Nearly 70% of cases were correlated with smokers .Bacteria were isolated from 53 patients in which 33 isolates were associated with the cancer cases while 20 of them from non infected patients. By using different morphological ,biochemical tests followed by api20 ,the bacterial isolates correlated with cancer were diagnosed and were characterized as 12 isolates (36.36%) of Pseudomonas aeruginosa ,6 isolates (18.18%) were Klebsiella pneumoniae ,Pseudomonas fluorescence and Esherichia coli for each while only 3 isolates (9.09%)of Acinetobacter baumannii were isolated. Some of bacterial virulence factors were determined in which,24 isolates (72.7%) were capable of agglutinating red blood cells, 16 isolates (48.5%) had the ability to adhere to epithelial cells , in addition ,15 isolates (45.5%) proved to have capsule and 24 isolates(72.7%) gave a positive results in heamolysin test beside ,25 isolates (75.8%) were ß –Lactamase producers. The isolates were highly resisted Ampicillin, Amoxicillin and Cefotaxime while they were inhibited by low concentrations of Ciprofloxacin and Cefepime the 4th generation cephalosporins.
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreBackground: Radiologic evaluation of breast lesions is being achieved through several imaging modalities. Mammography has an established role in breast cancer screening and diagnosis. Still however, it shows some limitations particulary in dense breast.
Methods : Magnetic resonance imaging is an attractive tool for the diagnosis of breast tumors1 and the use of magnetic resonance imaging of the breast is rapidly increasing as this technique becomes more widely available.1 As an adjunct to mammography and ultrasound, MRI can be a valuable addition to the work-up of a breast abnormality. MRI has the advantages of providing a three-dimensional view of the breast, performing wit
... Show MoreBackground Psoriasis is one of the most prevalent chronic inflammatory skin conditions; its prevalence ranges from 1 to 3%. Tumor necrosis factor-alpha (TNF-α), a cytokine that enhances inflammation, is overexpressed in synovium and skin plaques in psoriasis. TNF-α plays a critical role in the pathogenesis of psoriasis. IL-10 is the most crucial cytokine for reducing excessive immune responses and decreasing pro-inflammatory reactions in all autoimmune disorders. Objective To evaluate the effect of Apremilast on ILـ10, TNFـα, and BMI in obese psoriatic patients. Methods Thirty patients included in this investigative study to measure the concentrations of TNFـα, ILـ10 and BMI, before and after receiving Apremilast. TNFـα and
... Show MoreRenal failure is a disease of the kidney, in which the renal excretory function is failed to process due to depression of the GFR. Renal failure is divided into acute and chronic depending on the period of the disease. The study was designed to investigate the level of oxidative stress in RF patients. Seventy-five subjects had enrolled in the study, who divided into three groups equally, in which they are healthy control, ARF patients, and CRF patients. The results had shown a significant
To determine the relationship between Helicobacter pylori infection and skin disorders, sixty six patients who suffering from skin diseases include chronic urticarial (CU) and atopic dermatitis (AD) who attended at Dermatological Clinic/ Al-Numan Teaching Hospital from the beginning of October 2015 to the end of January 2016 with age (6-62) have been investigated and compared to twenty two samples of apparently healthy individuals were studied as control group. All the studied groups were subjected to measurement of antiHelicobacter pylori IgG antibodies by enzyme linked immuno sorbent assay (ELISA) and detection of 16S rRNA and CagA genes by using singleplex and multiplex PCR methods. The results of current study revealed that there was a
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