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bsj-6797
Revision of some Biomarkers with Cytokines in Breast Cancer
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Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following cytokines such as: interleukin 12 (IL-12), interleukin 6 (IL-6), interleukin 4 (IL-4), 8-hydroxydeoxyguanosine (8-OHdG), tumor necrosis factor (TNF) and interferon-γ (IFN-γ) levels with other bio-pointers such as:
 malondialdehyde (MDA), catalase, and 8-nitroguanine (8-NG). The results displayed  that the levels of blood and saliva samples of IL-12 (P<0.0001), IL-6 (P<0.0001), IL-4 (P<0.001), 8-OHdG (P<0.0001), 8-NG (P<0.001, and P<0.004), TNF (P<0.002, and P<0.001)  and IFN-γ (P<0.0001) were significantly higher in breast cancer, whereas there were significant lowering (P<0.0001)  in catalase activates in breast cancer in both samples as compared with healthy subjects. The exchanging of blood to salivary components evaluation in this investigation may be utilized as a diagnostic tool, and designates the potential part for MDA, Catalase, and cytokines as important biochemical in breast cancer. Accordingly, the salivary diagnosis embraces a non-invasive process and tumor progression in breast malignancy patients. Beside saliva may well signify as an active new gate as blood evaluation but easier and cheaper.

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Publication Date
Wed Apr 03 2024
Journal Name
International Journal Of Economics And Finance Studies
THE IMPACT OF ARTIFICIAL INTELLIGENCE ON ACCOUNTING PERFORMANCE: SUSTAINABLE DEVELOPMENT AS A MEDIATING VARIABLE
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The UN plans to achieve several development objectives by 2030. These objectives address global warming, a major issue. This method aims to improve sustainable accounting performance (AP). In this circumstance, AI is being applied in various fields, notably in economic, social, and environmental (ESE) domains. This research investigates how sustainable development (SD) influences AI methodologies and AP improvement. The research examined a sample of Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2022. AI was measured by ATM and POS prevalence. A three-dimensional approach examined economic, social, and environmental (ESE) sustainability. Meanwhile, the performance of sustainable accounting was measured through the return on asse

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
An Improved Cuckoo Search Algorithm for Maximizing the Coverage Range of Wireless Sensor Networks
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The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

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Publication Date
Wed Nov 27 2019
Journal Name
Environmental Science And Pollution Research
Application of emulsion and Pickering emulsion liquid membrane technique for wastewater treatment: an overview
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Publication Date
Wed Nov 22 2023
Journal Name
Drug And Chemical Toxicology
Preparation, characterization, and toxicity evaluation of microemulsion formulation containing prunetin for potential oral applications
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Publication Date
Wed Apr 01 2015
Journal Name
Mathematical Methods In The Applied Sciences
An inverse problem of finding the time-dependent diffusion coefficient from an integral condition
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Publication Date
Thu Jan 12 2023
Journal Name
Journal Of Inorganic And Organometallic Polymers And Materials
Nanoarchitectonics of Silver/Poly (Methyl Methacrylate) Films: Structure, Optical Characteristics, Antibacterial Activity, and Wettability
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Publication Date
Sat Apr 25 2020
Journal Name
Asian Journal Of Agriculture And Biology
Biodegradation of plastic wastes by confused flour beetle Tribolium confusum Jacquelin du Val larvae
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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Modeling and Analyzing the Influence of Fear on the Harvested Modified Leslie-Gower Model
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A modified Leslie-Gower predator-prey model with a Beddington-DeAngelis functional response is proposed and studied. The purpose is to examine the effects of fear and quadratic fixed effort harvesting on the system's dynamic behavior. The model's qualitative properties, such as local equilibria stability, permanence, and global stability, are examined. The analysis of local bifurcation has been studied. It is discovered that the system experiences a saddle-node bifurcation at the survival equilibrium point whereas a transcritical bifurcation occurs at the boundary equilibrium point. Additionally established are the prerequisites for Hopf bifurcation existence. Finally, using MATLAB, a numerical investigation is conducted to verify the va

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