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Detection of JAK2V617F Mutation and Serum Levels of Alkaline Phosphatase and Lactate Dehydrogenase in Chronic Myelogenous Leukemia.
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Chronic myelogenous leukemia (CML) is a myeloproliferative neoplasm arises from Bcr-Abl gene translocation (called Ph chromosome) in hematopoietic stem cells (HSCs). This genetic abnormality results in constitutive activation of tyrosine kinase and subsequent uncontrol growth and multiplication of granulocytes. The cornerstone in treatment of CML are tyrosine kinase inhibitors, of which imatinib is the most effectively used. JAK2V617F mutation is an acquired single nucleotide polymorphism (SNP) occurs in JAK2 gene and is associated with many hematological malignancy other than CML. It was thought that the two genetic abnormalities (Bcr-Abl and JAK2V617F) occur mutually; however, growing body of evidences suggested the reverse. This study aimed to investigate the prevalence of JAK2V617 mutation associated with serum levels of alkaline phophatase (ALK) and lactate dehydrogenase (LDH) in Ph+ CML Iraqi patients treated with imatinib. A total of 43 Ph+ CML patients (24 males and 18 females, age range 16-80 years) who attend Iraqi National Center of Hematology for Research and Treatment/Baghdad were enrolled in this study. Each patient has been received at least six month therapy with imatinib. A consent form involving age, gender, height, weight, smoking status, residency and first family relative history of leukemia was obtained from each patient. Besides, blood samples were collected, from which the granulocytes were separated and then DNA was extracted using a ready kit. Two assays were used for detection of JAK2V617F mutation; real time polymerase chain reaction (qPCR) using specific primers and probe, and allele specific PCR (AS-PCR) using specific primers. Total white blood corpuscles (WBC) as well as serum levels of ALP and LDH were measured. qPCR assay revealed 5 patients out of 43 (11.62%) were heterozygous for the muatant allele of JAK2V617F mutation (genotype GT). The concentration of this allele ranged from 0.01% to 0.12%. None of blood sample gave positive result for AS-PCR assay. From the all risk factors, only gender had significant association with the incidence of JAK2V617F mutation (p= 0.034, OR= 0.5, 95%CI= 0.364-0.687). Average total WBC count, and serum levels of ALP and LDH were higher in JAK2V617F-positive patients (9042±1512.55, 146.05±8.028 IU/L and 204±10.85 IU/L respectively) than that of JAK2V617F-negative patients (6039±1772.239, 64.45±40.15 IU/L and 178.33±13.693 IU/L respectively) with significant differences. These results indicate that JAK2V617F mutation can occur simultaneously with Ph chromosome in CML patients, and qPCR is a highly sensitive method for the detection of this mutation. Furthermore, serum activity of APL can be used as an indicator for the presence of JAK2V617F mutation in CML patients.

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Publication Date
Wed Jan 01 2014
Journal Name
Babylon University Journal\applied Pure Sciences
Detection of the perfect condition to produce the tannase from Aspergillus niger at different medium
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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
A Magnetic Field Concentration Method for Magnetic Flux Leakage Detection of Rail-Top Surface Cracks
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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Minimum Spanning Tree Algorithm for Skin Cancer Image Object Detection
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This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that

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Publication Date
Mon May 01 2017
Journal Name
Australian Journal Of Basic And Applied Sciences
Sprite Region Allocation Using Fast Static Sprite Area Detection Algorithm
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Background: Sprite coding is a very effective technique for clarifying the background video object. The sprite generation is an open issue because of the foreground objects which prevent the precision of camera motion estimation and blurs the created sprite. Objective: In this paper, a quick and basic static method for sprite area detection in video data is presented. Two statistical methods are applied; the mean and standard deviation of every pixel (over all group of video frame) to determine whether the pixel is a piece of the selected static sprite range or not. A binary map array is built for demonstrating the allocated sprite (as 1) while the non-sprite (as 0) pixels valued. Likewise, holes and gaps filling strategy was utilized to re

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
: financial fraud ,Audit risks ,inherent risk ,Detection risk, Data Mining .
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Abstract

The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th

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Publication Date
Fri May 17 2019
Journal Name
Lecture Notes In Networks And Systems
Features Selection for Intrusion Detection System Based on DNA Encoding
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Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

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Scopus (5)
Scopus
Publication Date
Tue Feb 01 2022
Journal Name
Svu-international Journal Of Engineering Sciences And Applications
Water Quality Detection using cost-effective sensors based on IoT
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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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