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Effect of x- ray on the treatment of breast cancer combined with amygdalin and doxorubicin separately
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Background: Radiation therapy has the ability to destroy healthy cells in addition to cancer cells in the area being treated. However, when radiation combines with doxorubicin, it becomes more effective on breast cancer treatment. Objective: This study aims to clarify the effect of X-ray from LINAC combined with amygdalin and doxorubicin on breast cancer treatment, and the possibility of using amygdalin with X-ray instead of doxorubicin for the breast cancer treatment. Method: Two cell lines were used in this study, the first one was MCF-7 cell line and second one was WRL- 68 normal cell line. These cells were preserved in liquid nitrogen, prepared, developed and tested in the (place). The effect of three x-ray doses combined with amygdalin and with doxorubicin was studied on these strains. Results: Combination of radiation with amygdalin and with doxorubicin, separately, exam revealed no statistically significant difference between x-rays doses (1Gy, 3Gy and 5 Gy) combined with amygdalin and x-rays doses (1Gy, 3Gy and 5 Gy) combined with doxorubicin for MCF-7 and WRL-68.In conclusion: there is possible to be considered amygdalin as a promise breast cancer treatment instead of doxorubicin combined with x-ray.

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Fri Oct 01 2021
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
The Use of Logistic Regression Model in Estimating the Probability of Being Affected By Breast Cancer Based On the Levels of Interleukins and Cancer Marker CA15-3
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Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

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Publication Date
Thu Jun 25 2020
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Preparation and Characterization of Topical Letrozole Nanoemulsion for Breast Cancer
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Letrozole (LZL) is a non-steroidal competitive aromatase enzyme system inhibitor. The aim of this study is to improve the permeation of LZL through the skin by preparing as nanoemulsion using various numbers of oils, surfactants and co-surfactant with deionized water. Based on solubility studies, mixtures of oleic acid oil and tween 80/ transcutol p as surfactant/co-surfactant (Smix) in different percentages were used to prepare nanoemulsions (NS). Therefore, 9 formulae of (o/w) LZL NS were formulated, then pseudo-ternary phase diagram was used as a useful tool to evaluate the NS domain at Smix ratios: 1:1, 2:1 and 3:1.

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Publication Date
Fri Dec 31 2021
Journal Name
Onkologia I Radioterapia
Correlation between mammographic appearance of breast cancer and histopathological results
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Publication Date
Sun Dec 01 2019
Journal Name
Saudi Medical Journal
The diagnostic power of circulating micro ribonucleic acid 34a in combination with cancer antigen 15-3 as a potential biomarker of breast cancer
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Publication Date
Tue Dec 25 2018
Journal Name
Journal Of Engineering Science And Technology
RIETVELD TEXTURE REFINEMENT ANALYSIS OF LINDE TYPE A ZEOLITE FROM X-RAY DIFFRACTION DATA
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Publication Date
Thu Jan 04 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Evaluation of the Relationship between Osteoporosis and Body Fat Mass of the Upper and Lower Extremities by Dual-Energy X-Ray Absorptiometry
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Background: Using dual-energy X-ray absorptiometry, body fat mass has been determined. The assessment of body fat mass was conducted utilizing dual-energy X-ray absorptiometry analysis of the pelvis and vertebral column. While it is acknowledged that osteoporosis can impact both body fat mass and bone mineral density, the particulars of this relationship currently remain uncertain. Objective: The aim of the present investigation is to assess gender differences in the effects of osteoporosis on the body fat mass of the upper and lower extremities. Method: 170 individuals participated (85 males and 85 females) in this study. Patients who presented with bone discomfort consisted of 40 males and 40 females. In addition, 90 apparently he

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Quantitative Computed Tomography and Dual-Energy X-Ray Absorptiometry in the Detection of Osteoporosis in Postmenopausal Women
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Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

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Publication Date
Wed Sep 01 2021
Journal Name
Nanomedicine Research Journal
Preparation, Characterization, Antimicrobial and Antitumor Activity of Chitosan Schiff base / PVA / PVP Au, Ag Nanocomposite in Treatment of Breast Cancer Cell Line
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Objective(s): Biocompatibility, non-toxicity, minimal allergenicity, and biodegradability are all characteristics of chitosan. Other biological properties of chitosan have been reported, including antitumor, antimicrobial and antioxidant activities. This research aim is the synthesis of drug compounds by preparation and characterization of polymer chitosan Schiff base and chitosan Schiff base / Poly vinyl alcohol / poly vinyl pyrrolidone Nanocomposite and study applications (anticancer cell line, antimicrobial agents). Methods: Chitosan Schiff base was prepared from the reaction of chitosan with carbonyl group of 4-nitro benzaldehyde. Polymer blend have been prepared by solution casting method. Chitosan Schiff base mixing with PVA and PVP

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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