Benign prostate hyperplasia (BPH), non-cancerous enlargement of prostate, is the most prevalent disease entity in elderly men. BPH affects 40% of men after the age of 60year worldwide. BPH causes problems for patients with significant lower urinary tract obstructive symptoms, if not responding to medical therapy, surgical intervention is instituted. One method of the treatment of symptomatic BPH is laser prostatectomy. The understanding of tissue effects by laser radiation is very important for the safe clinical application of laser. Objective: study the 2100 nm Ho: YAG laser gross tissue effects in the prostate at different laser dose settings in an vitro model prostate tissue samples harvested from same specimen of open surgery prostat

Objective(s): to assess the effectiveness of educational program on nurses' knowledge concerning the side
effects of chemotherapy among children with leukemia.
Methodology: A descriptive analytic (quasi – experimental) design study was carried out at Baghdad City from
2
nd of October to 27th of June 2015. Non-probability sample of (35) male and female nurses was selected from
the Oncology Wards in Children Welfare, Child's Central and Baghdad Teaching Hospital. The study
instruments consisted of two major parts to meet the purposes of study. The first part is related to nurses'
demographic characteristics and the second part (four domains) is related to nurses' knowledge concerning the
side effects of chemothera

The study in duded isolation and identification of microbial isolates from oral cavity to 10 volunteers, diagnosed within the three groups: Staphylococcus aureus, Staphylococcus epidermidis, Streptococcus spp. and Candida albicans . The sensitivity test of all isolates bacteria Streptococcus spp. , S. aureus and S. epidermidis showed high resistance to Ampicillin(100)%,followed Methicillin (88.88)% and Amoxicillin / clavulanic acid(77.77)%, while the resistance for each of Vancomycin and Amoxicillin were (66.66)%, and the resistance to Erythromycin and Pencillin (55.55)% to each of them. The results showed less resistance to Trimethoprim (22.22)% and Cefalotine (11.11)% of all bacteria isolate. Investigation of the pre

98 samples were collected from various clinical sources included (Burns, wounds, urines, sputums, blood) From the city of Baghdad, After performing the biochemical and microscopic examination, 52 isolates were obtained for Pseudomonas aeruginosa, 17 (32.7%) isolates from burn infection, 12 (23%) isolates from Wound infection 11 (21.2%) isolates from urine infection, 7 (13.5%) isolates of sputum and 5 (9.6%) isolates from blood. Bacteria susceptibility to form biofilm has been detectedby microtiter plate method, The results showed that 80% of the bacterial isolates were produced the biofilm with different proportions, alg D gene (alginate production) has been detected by polymerase chain reaction (PCR) Which plays an essential role in the fo

Background: Metabolic syndrome (Mets) is partially heritable. High mobility group AT-hook1 (HMGA1), an architectural transcription factor, affects the homeostasis of glucose. The marked inter-individual differences between T

Chronic periodontitis (CP) is an inflammatory disease affecting tooth supporting structures in response to bacterial dental plaque causing irreversible tissue destruction. Cyclooxygenase-2 (COX-2) is an effective mediator in the pathogenesis of periodontitis. Polymorphisms in the COX-2 gene may contribute to its overexpression and increased disease susceptibility. To evaluate the association between -1195 A/G single nucleotide polymorphism (SNP) in the promotor area of the cyclooxygenase-2(COX-2) gene and severity of chronic periodontitis in a sample of Iraqi population. -1195A/ G COX-2 SNP was investigated in 70 chronic periodontitis (CP) cases and 30 healthy controls. CP cases composed of 2 subgroups (35 moderate CP cases and 35 severe CP

Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential