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Surface enhanced Raman spectroscopy based sensitive and specific detection of vitamin D3, glycated hemoglobin, and serum lipid profile of breast cancer patients
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Considering the expanding frequency of breast cancer and high incidence of vitamin D3 [25(OH)D3] insufficiently, this investigate pointed to explain a relation between serum [25(OH)D3] (the sunshine vitamin) level and breast cancer hazard. The current study aimed to see how serum levels of each [25(OH)D3], HbA1c%, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were affected a woman’s risk of getting breast cancer. In 40 healthy volunteers and 69 untreated breast cancer patients with clinical and histological evidence which include outpatients and hospitalized admissions patients at the Oncology Center, Medical City / Baghdad - Iraq. Venous blood samples were withdrawn from breast cancer patients and healthy women between June – Dec., 2020. Serum lipid profiles including [total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG)], [25(OH)D3] and HbA1c% were determined under aseptic conditions using a standard fully automatic Chemistry Analyzer. The independent sample t-test was used in the statistical analysis to compare the mean serum levels of lipid profile and other biomarkers determined between breast cancer patients and compared with apparently healthy women. TG, TC, LDL-C, and HDL-C levels are 190. 7 mg/dl, 104.3 mg/dl, 108.1 mg/dl, and 53 mg/dl, respectively. Breast cancer caused a significant increase in serum TC, LDL-C, and TG while decreasing HDL-C significantly. Breast cancer development could be one of the factors causing changes in Vit. D, HbA1c, and lipid profile levels.

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Publication Date
Sat Dec 30 2023
Journal Name
Al-kindy College Medical Journal
Radiological Significance of Shear-Wave Elastography Technique for Evaluation of Solid Breast Masses with Histopathological Correlation
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Background: Although various imaging modalities are available for evaluating suspicious breast lesions, ultrasound-based Shear-Wave Elastography (SWE) is an advanced, non-invasive technique complementary to grayscale sonography. This technique evaluates the elasticity of a specific tissue by applying sonic pressure to that tissue.

Objective: The aim is to assess the role of SWE in evaluating solid breast masses in correlation to histopathological study results.

Subjects and Methods: This prospective study was done in a tertiary care teaching hospital from September 2019 to August 2020. A study population of 50 women aged 18 years or above with an

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Changes in the serum level of the trace elements in chronic renal
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Were studied changes in the concentration of copper, iron and zinc in blood serum of one hundred patients with chronic kidney and treated dialysis blood were also measured the level of calcium kidney and phosphate Calciotropic in serum of these patients took samples of blood from these patients before and after treatment dialysis vessels as well as the statement of changes in those standards Alkimaahiatih Results were compared with twenty-five healthy people (control group)

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Publication Date
Tue Jun 30 2009
Journal Name
Al-kindy College Medical Journal
The impact of advancing age on total serum IgE in asthmatic patient
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Abstract

The current study was conducted to assess the effect of advancing age on total serum IgE level in asthmatic patients. To this purpose, 90 asthmatic patients and 30 healthy individuals ( control group ) were enrolled. Asthmatic patients were categorized into four groups. Group A consisted of asthmatic patients (9) whose age was more than 20 and up to 30 y. Group B contained asthmatics (13) of age more than 30 and up to 40 y. Group C comprised those (23) of more than 40 and up to 50 y. Group D consisted asthmatic patients (45) of age more than 50 y. Total serum IgE level significantly changed in group D patients when compared with those of

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Demonstration of the value of diffusion weighted MR imaging for differentiation of benign from malignant breast lesions
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Background: 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

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Publication Date
Tue Dec 19 2023
Journal Name
Journal Of Madenat Alelem College
Review Article: Amygdalin as Anti-Cancer Agent
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Amygdalin (d-Mandelonitrile 6-O-β-d-glucosido-β-d-glucoside) and its semi synthetic product is Laetrile ( also called vitamin B17): a natural cyanogenic glycoside occurring in the seeds of some edible plants, such as bitter almonds and peaches. Early in the 19th century, Amygdalin was first isolated in 1830 by two French chemists, Robiquet and Boutron-Charlard, as active components in various fruit pits and raw nuts. However, the systematized study of vitamin B17 started when chemist Bohn (1802) discovered that a hydrocyanic acid is released during distillation of the water from bitter almonds. The various pharmacological effects of Laetrile include antiatherogenic, activity in renal fibrosis, pulmonary fibrosis, immune regulation, ant

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Publication Date
Wed May 22 2024
Journal Name
Journal Of Biotechnology Research Center
Review Article: DNA Methylation in Cancer Immunity
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Background: The transcriptional control of various cell types, especially in the development or functioning of immune system cells involved in either promoting or inhibiting the immune response against cancer, is significantly influenced by DNA or RNA methylation. Multifaceted interconnections exist between immunological or cancer cell populations in the tumor's microenvironment (TME). TME alters the fluctuating DNA (as well as RNA) methylation sequences in these immunological cells to change their development into pro- or anti-cancer cell categories (such as T cells, which are regulatory, for instance). Objective: This review highlights the impact of DNA and RNA methylation on myeloid and lymphoid cells, unraveling their intricate

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Local wheat peel as a solid surface to remove Azure B dye from aqueous solution:Equilibrium isotherms and thermodynamic study
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In this research local wheat peel was used as an adsorbent surface for removal of Azure B (AB) dye from the aqueous solution. The adsorption process was performed at different experimental parameters, equilibrium time, temperature, ionic strength and solution pH. The isotherms of adsorption are of H-type as compared with Giles curves and the adsorption data were coincide with Freundlich equation. The adsorption kinetic data were analyzed using pseudo- first and second order kinetic models. The effect of temperature was studied and the amount of dye adsorbed was found to increase with the increasing of temperature from 25 to 50 oC. The values of thermodynamic functions like enthalpy and entropy have been estimated. The quantity of adso

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Publication Date
Thu Aug 01 2024
Journal Name
Water Practice & Technology
Artificial neural network and response surface methodology for modeling oil content in produced water from an Iraqi oil field
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ABSTRACT<p>The majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value &lt;0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe</p> ... Show More
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Publication Date
Fri Nov 24 2023
Journal Name
Iraqi Journal Of Science
Effect of Different Percentages of Titanium Dioxide Additives on the Enamel Protecting of Steel Surface
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This work involves the development of ceramic coating to steel surfaces (enamel).This enamel high quality consisted of two ceramic layers to ensure excellent bonding with the steel surfaces. The first is called the ground coat which proved bonding between the steel base and the second outer layer called the cover coat. Various concentrations of TiO2 were separately added to the mixture of the cover coat, resulting in to much better densification of the ceramic outer layer, the hardness, thermal shock resistances, and glossiness were improved also .Moreover this addition has raised the corrosion resistances of the ceramic in harsh acidic environment and at higher temperatures Also this enamel was used to protect the surfaces of steels whi

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

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