Sixty urine samples were collected from women with urinary tract infection in different ages. The aims of this study were determined the dominancy of pathogens isolated from urine of women with UTI and evaluating the antibacterial activity of Rosmarinus officinalis L. essential oil against these pathogenic isolates. Identification of bacteria was done on Chromogenic orientation agar while disc diffusion method was used for determination the sensitivity of bacterial isolates to antibiotics and Agar well diffusion method was used for evaluation the antibacterial effect of Rosemary essential oil on these isolates. The results showed that 50% of women infected with Escherichia coli, it was dominants in ages above 15 years old while Staphyl

Sixty urine samples were collected from women with urinary tract infection in different ages. The aims of this study were determined the dominancy of pathogens isolated from urine of women with UTI and evaluating the antibacterial activity of Rosmarinus officinalis L. essential oil against these pathogenic isolates. Identification of bacteria was done on Chromogenic orientation agar while disc diffusion method was used for determination the sensitivity of bacterial isolates to antibiotics and Agar well diffusion method was used for evaluation the antibacterial effect of Rosemary essential oil on these isolates. The results showed that 50% of women infected with Escherichia coli, it was dominants in ages above 15 years old while Staphylococc

In vitro antifungal susceptibility test of itraconazole was carried out against 38 isolates from nails, skin, oral cavity, vagina and wounds, This study was done in Ramadi Teaching Hospital in period from January to August 2010. According to the National Committee for Clinical Laboratory Standard (NCCLS ) M 27- A by using the broth dilution method. Inoculum size was 1-5X10³ CFU/ ml, while final concentrations of itraconazole ranged from 0.025 – 6.4 μg / ml by using RPMI – 1640 broth media and the fungus was incubated at 35 ^oC.  No resistant stain was recorded. MIC ranged from 0.05 – 6.4 μg / ml and the Mean ± SEM was 0.89 ± 0.28. MIC for nail isolates was 0.05 –

The current study included details of the anatomical characteristics of vegetative parts including the root, stem, leaf in cultivated Iraq for the species Brassciaaleraceacabbage, where the study dealt with the stomatal index and the rate of both the length and width of the stomatal complex and the thickness of the periderm, the tissue, cortex, vascular cylinder and pith. The parts were taken and measured after the plant was treated with brassinolide and the treated species with brassinolide and non-treated were measured and the study showed that there was a clear variation in the properties above.

Diabetic nephropathy (DN) is the foremost cause of end-stage renal disease. Early detection of DN can spare diabetic patients of severe complications. This study aimed to evaluate the diagnostic value of red cell distribution width (RDW) and neutrophil-lymphocyte ratio (NLR) in the detection of DN in patients with type 2 diabetes mellitus (T2DM). This cross-sectional study included a total of 130 patients with T2DM, already diagnosed with T2DM. The albumin creatinine ratio (ACR) in urine samples was calculated for each patient, according to which patients were divided into two groups: with evidence of DN when ACR ? 30 mg/g, and those with no evidence of DN when ACR < 30 mg/g. According to multivariate analysis, each of disease duration (OR

Background: Diabetic neuropathy can affect any peripheral nerve, including sensory neurons, motor neurons, and the autonomic nervous system. Therefore, diabetic neuropathy has the potential to affect essentially any organ and can affect parts of the nervous system like the optic nerve, spinal cord, and brain. In addition, chronic hyperglycemia affects Schwann cells, and more severe patterns of diabetic neuropathy in humans involve demyelization. Schwann cell destruction might cause a number of changes in the axon. study aims to evaluate serum myelin protein level as a predicting marker in the diagnosis of diabetic neuropathy and to prevent early neuropathy complications of type 2 diabetes.

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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

The aim of this research is to determine the most important and main factors that lead to Preeclampsia. It is also about finding suitable solutions to eradicate these factors and avoid them in order to prevent getting Preeclampsia. To achieve this, a case study sample of (40) patients from Medical City - Oncology Teaching Hospital was used to collect data by a questionnaire which contained (17) reasons to be investigated. The statistical package (SPSS) was used to compare the results of the data analysis through two methods (Radial Bases Function Network) and (Factorial Analysis). Important results were obtained, the two methods determined the same factors that could represent the direct reason which causes Preecla

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac