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Breast intraductal nanoformulations for treating ductal carcinoma in situ I: Exploring metal-ion complexation to slow ciclopirox release, enhance mammary persistence and efficacy
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Publication Date
Wed Jun 26 2024
Journal Name
Opera Medica Et Physiologica
The Impact of Global DNA Methylation and Hypoxia-Inducible Factor 1 Alpha Levels in the Progression of Breast Cancer
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Publication Date
Wed Feb 01 2023
Journal Name
Asian Pacific Journal Of Cancer Prevention
Cytotoxic Activity of the Ethyl Acetate Extract of Iraqi Carica papaya Leaves in Breast and Lung Cancer Cell Lines
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Publication Date
Sun Jan 01 2023
Journal Name
Caspian Journal Of Environmental Sciences
Efficacy of nanoparticle zinc oxide in the resistance of fungus Rhizoctonia solani causing black scurf disease in local potatoes
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Energy Storage
Multiple-segment metal foam application in the shell-and-tube PCM thermal energy storage system
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Publication Date
Fri Jan 23 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Dissolution of calcium ion from teeth treated with different concentrations of siwak water extract in comparison with sodium fluoride
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Background: The miswak is a teeth cleaning twig made from a twig of the Salvadora persica tree (known as arak in Arabic).A traditional alternative to the modern toothbrush, it has a long, well-documented history and is reputed for its medicinal benefits. It also features prominently in Islamic hygienical jurisprudence. Materials and methods: Twenty maxillary first premolars were treated with the selected solutions which included siwak water extract (5%, 10%) and sodium fluoride 0.05% for 2minutes once daily for 20 days interval, deionized water was used as control negative. Then the concentration of the dissolved calcium ion in the etching solution of 2N HCL was measured. Results: The least amount of the dissolved calcium ion was registere

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Fri May 25 2018
Journal Name
Open Public Health Journal
Comparative Study on the Clinicopathological Profiles of Breast Cancer Among Iraqi and British Patients
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Background: Breast cancer is the most common cancer in Iraq and the United Kingdom. While the disease is frequently diagnosed among middleaged Iraqi women at advanced stages accounting for the second cause of cancer-related deaths, breast cancer often affects elderly British women yielding the highest survival of all registered malignancies in the UK. Objective: To compare the clinical and pathological profiles of breast cancer among Iraqi and British women; correlating age at diagnosis with the tumor characteristics, receptor-defined biomarkers and phenotype patterns. Methods: This comparative retrospective study included the clinical and pathological characteristics of (1,940) consecutive female patients who were diagnosed with invasive b

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Research In Medical And Dental Science
The Efficacy of 4% Articaine Infiltration Anesthesia in the Extraction of Mandibular Molars: A Randomized Controlled Study
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Introduction: Articaine was developed in 1969, with reported advantages which are increased potency, increased duration of its anesthetic effect and superior diffusion through bony tissue. The effectiveness of using 4% articaine infiltration for extraction of mandibular molar teeth in comparison to 2% lidocaine inferior alveolar nerve block is not settled yet. Aim: The aim of this study was to evaluate the effectiveness of using 4% articaine infiltration for extraction of mandibular molars by comparing it to the use of 2% lidocaine inferior alveolar nerve block in terms of success, the volume of local anesthetic agents and the pain experienced during the procedure. Materials and methods: A prospective randomized controlled study included

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Publication Date
Wed Oct 16 2019
Journal Name
Journal Of Research In Medical And Dental Science
Evaluation of the Antibacterial Efficacy of Silver Nanoparticles as an Irrigant against Enterococcus faecalis In vitro Study
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Background: Successful root canal therapy depends on thorough chemo mechanical debridement of pulpal tissue, dentin debris and infective microorganisms. Objective: This study aimed to investigate the antibacterial effect of silver nanoparticles, sodium hypochlorite and chlorhexidine in reducing the bacterial infection of the root canals. Materials and Methods: The root canals of 55 single-rooted teeth were cleaned, shaped, and sterilized. All the teeth samples were inoculated with Enterococcus faecalis and incubated at 37°C for 2 weeks. Then, the teeth were divided into four groups. Group I (n=15): 100 ppm silver nanoparticles, Group II (n=15): 2.5 sodium hypochlorite, Group III (n=15): 2% chlorhexidine, IV (n=10): Normal saline as a contr

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