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Detection of active human cytomegalovirus in patients with multiple myeloma
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Abstract:<sec><title>BACKGROUND:

Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

OBJECTIVES:

The aim of the study was to estimate the frequency of active HCMV in MM patients.

MATERIALS AND METHODS:

This is a case–control study involved 50 MM patients attending Hematology Center, Baghdad Teaching Hospital; 25 of them were newly diagnosed and 25 on treatment compared to 50 of apparently healthy control. HCMV-viral load was measured using a real-time polymerase chain reaction (RT-PCR).

RESULTS:

Active HCMV was detected in 8 patients out of 50 (16%); 6/25 (24%) in newly diagnosed and 2/25 (8%) on treatment and had autologous bone marrow transplant with mean ± standard deviation of 910 × 1010± 210 × 1010, and 32,000 × 1010± 1500 × 1010IU/mL, respectively. HCMV viremia is equally detected in both remission and relapsed cases.

CONCLUSION:

RT-PCR detected a significant number of MM patients infected by cytomegalovirus compared to healthy individuals. Further studies are needed to verify if this finding has a relation to etiology or disease progression.

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Evaluation of serum levels of Proinflammatory Cytokines IL-8, IL-17, and IL-22 in Helicobacter pylori infection and their association with the degree of gastritis histopathology in a sample of Iraqi patients
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Gastritis can be defined as histological inflammation of the gastric mucosa. It can be classified according to the time course of the disease as acute or chronic, histological findings, anatomic location, and pathological mechanisms. The objective of this study was to evaluation of serum levels of the proinflammatory cytokines IL-8, IL-17 and IL-22 in Helicobacter pylori infection and their association with the degree of gastritis histopathology in a sample of Iraqi patients. The case-control prospective study consists of 60 patients who attended the Gastrointestinal Tract Center at Al-Kindy Teaching Hospital during the period from December 2019 to April 2020. In addition, the control group included 60 apparently healthy individuals. Bio

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Publication Date
Sun Feb 03 2019
Journal Name
Iraqi Journal Of Physics
Change detection of remotely sensed image using NDVI subtractive and classification methods.
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Change detection is a technology ascertaining the changes of
specific features within a certain time Interval. The use of remotely
sensed image to detect changes in land use and land cover is widely
preferred over other conventional survey techniques because this
method is very efficient for assessing the change or degrading trends
of a region. In this research two remotely sensed image of Baghdad
city gathered by landsat -7and landsat -8 ETM+ for two time period
2000 and 2014 have been used to detect the most important changes.
Registration and rectification the two original images are the first
preprocessing steps was applied in this paper. Change detection using
NDVI subtractive has been computed, subtrac

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
Detection of Nutrients and Major Ions at Al Muthanna Storage Site Soil
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In the early 90s military operations and United Nations Special Commission “UNSCOM” teams have been destroyed the past Iraqi chemical program. Both operations led an extensive number of scattered remnants of contaminated areas. The quantities of hazardous materials, incomplete destructed materials, and toxic chemicals were sealed in two bunkers. Deficiency of appropriate destruction technology led to spreading the contamination around the storage site. This paper aims to introduce the environmental detection of the contamination in the storage site area using geospatial analysis technique. The environmental contamination level of nutrients and major ions such as sulphate (SO4), potassium (K), sodium (Na), magnesi

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Publication Date
Mon Apr 19 2010
Journal Name
Computer And Information Science
Quantitative Detection of Left Ventricular Wall Motion Abnormality by Two-Dimensional Echocardiography
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Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

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Publication Date
Sun May 11 2014
Journal Name
World Journal Of Experimental Biosciences
Detection of hydrolytic enzymes produced by Azospirillum brasiliense isolated from root soil
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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Detection and interpretation of clouds types using visible and infrared satellite images
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One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

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Publication Date
Wed Jun 16 2021
Journal Name
Cognitive Computation
Deep Transfer Learning for Improved Detection of Keratoconus using Corneal Topographic Maps
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Abstract <p>Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b</p> ... Show More
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Publication Date
Wed Jun 28 2023
Journal Name
The Iraqi Journal Of Veterinary Medicine
Haemoglobin Epsilon as a Biomarker for the Molecular Detection of Canine ‎Lymphoma
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Lymphoma is a cancer arising from B or T lymphocytes that are central immune system ‎components. It is one of the three most common cancers encountered in the canine; ‎lymphoma affects middle-aged to older dogs and usually stems from lymphatic tissues, ‎such as lymph nodes, lymphoid tissue, or spleen. Despite the advance in the management of ‎canine lymphoma, a better understanding of the subtype and tumor aggressiveness is still ‎crucial for improved clinical diagnosis to differentiate malignancy from hyperplastic ‎conditions and to improve decision-making around treating and what treatment type to use. ‎This study aimed to evaluate a potential novel biomarker related to iron metabolism,

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Levels of Glucose-6-phosphate Dehydrogenase in Type 1 Diabetes Mellitus patients with Nephropathy and Cardiovascular disease complication: Perry H. Saifullah|Saad M. Nida|Israa B. Raoof
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The aim of this study is to evaluate oxidative stress in diabetes mellitus (DM) Type1 by the measurement of Glucose-6-phosphate Dehydrogenase (G-6-PD), an enzyme expressed in human RBCs, is important in the generation of reduced glutathione which is the key product in oxidative stress controls. The Study was carried on 80 samples of blood and serum of National Diabetes Center (NDC). The study groups under fasting conditions and they divided as:20 samples of diabetes mellitus patients without complications and 20 samples of diabetes mellitus with cardiovascular (CV) complications and 20 samples of diabetes mellitus with Nephropathy (Neph) complications compared with 20 control group with average age (13-67) years.. The results sh

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