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Assessment of Six Polymorphic Variants as Genetic Risks for Coronary Artery Disease: A Case–Control Study
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Abstract<sec> <title>Background:

Coronary artery disease (CAD) is the leading cause of death worldwide. Certain genetic polymorphisms play an important role in this multifactorial disease, being linked with increased risk of early onset CAD.

Objective:

To assess six genetic polymorphisms and clinical risk factors in relation to early onset nondiabetic Iraqi Arab CAD patients compared to controls.

Materials and Methods:

This case–control study recruited 40 Iraqi patients with early onset CAD and 20 healthy controls. Demographic and clinical data were reported. Six genetic variants were tested: β-fibrinogen (FGB), human platelet antigen 1 (HPA1a/b), angiotensin-converting enzyme (ACE), two variants of endothelial nitric oxide synthase (eNOS), and lymphotoxin alpha (LTA), utilizing a ready-to-use kit.

Results:

The majority of patients were older males (85%), nonsmokers (52.5%), hypertensives (57.5%), had dyslipidemia (100%), and had a family history of ischemia (77.5%). This contrasts the findings in the control group (P < 0.001). From the six studied polymorphisms, a statistically significant difference was found between patients and controls in relation to ACE and LTA genes (P = 0.032 and 0.028), respectively. None (0%) of the participants had a genetic risk score >6. There was a statistically significant association between higher clinical risk scores and CAD group; eNOS G894T was found to be linked with increasing age, while LTA was linked to dyslipidemia.

Conclusions:

This study aids in CAD risk stratification. There is a need for longitudinal studies assessing more genetic risks to CAD as a national CAD preventive program for high-risk Iraqi people.

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Publication Date
Fri Jan 01 2010
Journal Name
Iraqi Journal Of Science
RETRIEVING DOCUMENT WITH COMPACT GENETIC ALGORITHM(CGA)
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Publication Date
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Genetic--Based Face Retrieval Using Statistical Features
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Publication Date
Sat Oct 17 2026
Journal Name
Journal Of Advanced Research Design
Sustainable Leaf Plant Disease Based on Salp Swarm Algorithm for Feature Selection
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Sustainable plant protection and the economy of plant crops worldwide depend heavily on the health of agriculture. In the modern world, one of the main factors influencing economic growth is the quality of agricultural produce. The need for future crop protection and production is growing as disease-affected plants have caused considerable agricultural losses in several crop categories. The crop yield must be increased while preserving food quality and security and having the most negligible negative environmental impact. To overcome these obstacles, early discovery of satisfactory plants is critical. The use of Advances in Intelligent Systems and information computer science effectively helps find more efficient and low-cost solutions. Thi

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Pre-operative serum TSH level estimation for predicting malignant nodular thyroid disease
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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
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It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

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Publication Date
Fri Sep 18 2020
Journal Name
Hal Open Science
Adaptive Approximation Control of Robotic Manipulators: Centralized and Decentralized Control Algorithms
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The regressor-based adaptive control is useful for controlling robotic systems with uncertain parameters but with known structure of robot dynamics. Unmodeled dynamics could lead to instability problems unless modification of control law is used. In addition, exact calculation of regressor for robots with more than 6 degrees of freedom is hard to be calculated, and the task could be more complex for robots. Whereas the adaptive approximation control is a powerful tool for controlling robotic systems with unmodeled dynamics. The local (partitioned) approximation-based adaptive control includes representation of the uncertain matrices and vectors in the robot model as finite combinations of basis functions. Update laws for the weighting matri

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Publication Date
Tue Mar 01 2022
Journal Name
Results In Engineering
Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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