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Estimation of Some Biomarkers and Cholesterol / HDL Ratio to Predict the Risk of Cardiovascular Disease in Rheumatoid Arthritis
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Rheumatoid arthritis (AR) is one of the chronic diseases resulting in many complications such as cardiovascular disease (CVD). Any change in the lipid profiles and myocardial markers indicates cardiovascular disease risk, so this study is designed to monitor the pattern of lipid profiles and myocardial markers in newly diagnosed RA patients. Blood samples were collected from 70 Iraqi patients newly diagnosed with rheumatoid arthritis (male and female) and 30 healthy served as control. These individuals were aged 35-65 years. The serum samples were obtained to determine myocardial markers; included troponin, creatinine kinase (CK), lactate dehydrogenase (LDH), and glutamic oxaloacetic transaminase GOT; and lipid profiles; such as cholesterol, triglyceride, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and very-low-density lipoprotein (VLDL); using a kit from Roch (Germany), measured automatically with Minividas, Biomerieux (France). No differences between levels of all lipid profiles and myocardial markers in newly diagnosed RA patients compared with the healthy group were found as well as they were within the normal values, but interestingly, the cholesterol/HDL ratio increased significantly in RA patients comparing with healthy, so it could conclude that the risk of CVD could be increase also among the newly diagnosed of RA patients. Moreover, the cholesterol/HDL ratio should be probably included in a model to predict the risk of cardiovascular disease for RA in addition to the gender, age at the disease onset, and severity markers of disease.

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Publication Date
Tue Oct 20 2020
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Artificial Neural Network and Box- Jenkins Models to Predict the Number of Patients with Hypertension in Kalar
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    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

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Publication Date
Fri May 12 2023
Journal Name
Journal Of Population Therapeutics And Clinical Pharmacology
Effect of Maternal Variables on some Physiological and Immunological Biomarkers in Iraqi Women Undergoing Caesarean Section
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Pregnancy and childbirth are physiological states characterized by sudden hormonal and immunologically described changes. The current study aimed to investigate the influence of maternal variables (age, previous abortion, placental position, and fetal position) on some physiological biomarkers, such as oxytocin (OT), prolactin (PRL), cortisol, and insulin growth factor 2 (IGF -2) and some immune biomarkers such as programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1) and interleukin 6 (IL-6) in Iraqi women undergoing caesarean section (CS). Blood samples were collected from 48 pregnant women in the age range (16-43 years) and serum was obtained to determine the levels of the above biomarkers. The effect of

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Publication Date
Sun May 01 2022
Journal Name
International Journal Of Multiphase Flow
Application of artificial neural network to predict slug liquid holdup
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Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Utilizing the R.E.N.A.L Nephrometry Score to predict the Surgical Technique and Peri-operative Outcomes of Renal Masses
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Background: despite the rise in the incidence of renal cell carcinoma attributed to availability of medical imaging, a considerable decline in mortality is an association. Morbidity-wise, the shift from radical nephrectomy to partial nephrectomy is the trend for now. Multiple scoring systems have been introduced over the past decades to help surgeons choose between radical and partial nephrectomy. One commonly used system is the RENAL nephrometry score that was first introduced by Kutikov and Uzzo in 2009.

Objective: to evaluate the role of RENAL nephrometry scoring system in predicting the surgical technique to use to resect renal masses and associated perioperative outcomes.

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Publication Date
Sat Sep 15 2018
Journal Name
Journal Of The College Of Education For Women
Estimation of the Risk of Water Erosion in Jawarta District in Sulaymaniyah Governorate Using the Global Equation for Soil Loss (USLE)
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The present research deals with the spatial variance analysis in Jwartadistrict and conducting a comparison on the spatial and seasonal changes of the vegetation cover between (2007-2013) in order to deduce the relationship between the vegetation density and the areas which are exposed to the risk of water erosion by using Plant Variation Index  NDVI) C (coefficient and by using Satellite images of Landsat satellite which are taken in 2/7/2007 and Satellite images of Landsat satellite taken in 11/1/ 2013, the programs of remote sensitivity and the Geographic Information Systems.

    The study reveals that there is a variance in the density of vegetation cover of the area under study betwee 2007 and 2013. Howev

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Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Determination of Toxoplasmosis Disease Activity by Estimation of IL-6 Cytokine
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Toxoplasma gondii (Nicolle and Manceaux ) infects all warm-blooded animals,
including humans. Early diagnosis and determining the infective stage are critical for
treating immunosuppressed individuals and pregnant women with toxoplasmosis.
This parasite modulates pro- and anti-inflammatory responses to regulate parasite
multiplication and host survival. The aim of this study was to investigate the
probability of using IL-6 as a marker of toxoplasmosis disease activity (acute and
chronic) in different groups of women (miscarriage, pregnant and single) and estimate
the relationship between infection and gestational age and history of abortion in
miscarriage and pregnant women. The most abortion were occurred at the

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Publication Date
Sat Feb 01 2025
Journal Name
Al-rafidain University College For Sciences
Use GARCH model to predict the stock market index, Saudi Arabia
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In this paper has been building a statistical model of the Saudi financial market using GARCH models that take into account Volatility in prices during periods of circulation, were also study the effect of the type of random error distribution of the time series on the accuracy of the statistical model, as it were studied two types of statistical distributions are normal distribution and the T distribution. and found by application of a measured data that the best model for the Saudi market is GARCH (1,1) model when the random error distributed t. student's .

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Publication Date
Sun Feb 14 2021
Journal Name
Biochemical And Cellular Archives
A RETROSPECTIVE STUDY TO EVALUATE SOME POTENTIAL RISK INDICATORS ON OSSEOINTEGRATED DENTAL IMPLANTS IN A SAMPLE OF IRAQI PATIENTS
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Determining risk indicators for dental implants is an essential strategy for preventing peri-implant diseases and effective diagnosis of dental implant success. To investigate the impact of certain potential factors on the osseointegrated dental implant. Eighty-four individuals were included in our study, 50 cases as a patient’s group and 34 participants as a control group. All cases were diagnosed based on certain criteria, 30 (60%) of patients had peri-implantitis, 20 (40%) with severe periimplantitis, 36(72%) were generalized, and 15 (30%) as localized peri-implantitis cases. The study has indicated that 44.7% of dental implants were in the anterior maxilla, followed by (27.3%) posterior maxilla, (17.4%) posterior mandible, and (10.4%)

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index
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Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
Role of Glycine-to-Nitrate Ratio in Physical and Magnetic Properties of Zn-Ferrite Powder
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     We report  the influence of different glycine-to-nitrate ratios on the physical and magnetic properties for synthesized zinc-ferrite by  microwave-assisted combustion route. Phase impurity and surface morphology investigated with XRD analysis and field emission- scanning electron microscopy, indicated that  spinel structure  were  formed.Average particles size increased  with the decrease of glycine to nitrate ratio. Magnetic measurement  results indicated that  high values of saturation magnetization  were produced with low  glycine/nitrate ratio. Optical properties of  the investigated ferrites exhibited photo absorption from UV to visible region with 

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