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Effects of Different Concentrations of Melatonin on the Time-course of Nitrite–induced Oxidation of Hemoglobin: In vitro Study
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         Melatonin is a potent scavenger of reactive oxygen species or free radicals like superoxide and hydroxyl radicals. The oxidation of hemoglobin to methemoglobin (meth-Hb) by oxidizing compounds has been widely studied. The present work was designed to evaluate the ability of different concentrations of melatonin to inhibit nitrite–induced oxidation of hemoglobin. Blood samples were obtained from apparently healthy individuals from which erythrocyte hemolysate was prepared. Different concentrations of melatonin (10-9-1.0 mg/ml) were incubated for 10 min with the hemolysate, then to the resultant mixture 1 ml of sodium nitrite (final concentration 0.6 mM) was added, and the formation of meth-Hb was measured by monitoring absorbance of light at 631 nm each min for 30 min. Control samples without melatonin were utilized for comparison. Nitrite caused rapid oxidation of hemoglobin to meth-Hb in control samples; in the presence of melatonin, the oxidation process was delayed in a dose–dependent manner. The effect of melatonin on the time course of nitrite-induced oxidation of Hb showed that melatonin has a protective effect initiated early after addition along with nitrite. Melatonin also affect the time required for the formation of meth-Hb, the   time required to convert 50% of the available Hb to meth-Hb was 4 min in the absence of melatonin, and became  17, 22, 26, 30, 114 and 383  min with increasing melatonin concentrations (10-9, 10-6, 0.001, 0.01, 0.1, and 1.0 mg/ml  respectively). In conclusion, melatonin in a concentration  and time dependent manner can protect Hb from oxidation by nitrite; melatonin delays the onset of autocatalytic stage and the protective effect extended over long period of time.

Key words: melatonin, erythrocytes oxidation

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Ghrelin and Leptin and Their Relations with Insulin Resistance in Diabetes Mellitus Type 2 Patients
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Ghrelin and leptin are hunger hormones related to type 2 diabetes mellitus (T2DM), and the pathogenesis of T2DM is the abnormality in insulin secretion and insulin resistance (IR). The aim of this study is to evaluate ghrelin and leptin concentrations in blood and to specify the relationship of these hormones as dependent variables with some biochemical and clinical measurements in T2DM patients. In this study, forty one T2DM and forty three non-diabetes mellitus (non-DM) subjects, aged between 40-60 years and with normal weight, were enrolled. Fasting serum ghrelin and leptin were estimated by enzyme-linked immunosorbent assay (ELISA). In our results ghrelin was significantly increased, and leptin was significantly decreased, in T2DM pa

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Publication Date
Sat Apr 01 2023
Journal Name
Digital Communications And Networks
Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
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Publication Date
Mon Mar 10 2025
Journal Name
Proceedings On Engineering Sciences
WAREHOUSE IN INDUSTRY 4.0 BASED DRONE, COMPUTER VISION, AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES: A LITERATURE REVIEW
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Publication Date
Mon Oct 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Robot Path Planning in Unknown Environments with Multi-Objectives Using an Improved COOT Optimization Algorithm
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Publication Date
Mon Jul 18 2022
Journal Name
Ieee Access
Moderately Multispike Return Neural Network for SDN Accurate Traffic Awareness in Effective 5G Network Slicing
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

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Publication Date
Wed Nov 05 2025
Journal Name
Irrigation And Drainage
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
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ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector funct</p> ... Show More
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Publication Date
Fri Dec 20 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
MEASURING RETURNSS TO SCALE, DISTRIBUTION EFFICIENCY AND ESTIMATING WHEAT PRODUCTION FUNCTION IN DHI QAR PROVINCE
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The aim of this research was to estimate the production function to measure returns to scale and distribution efficiency of  resources used in the production of wheat. Cross sectional data used of a random sample of 130 farmers in Dhi Qar Province. The results of the quantitative analysis of estimating production function showed that the double logarithmic form was the best estimated model based on economic and statistical indicators. However, that form suffered from heteroscedasticity and autocorrelation, so the robust regression technique was chosen. Value of returns to scale was 0.89 and this indicates decreasing returns to scale. This means that production function is in the second stage of the function. The results of the dist

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Causal Relationship between Stock Market Indices Volatility and Oil Prices Volatility: Empirical Evidence from Iraqi Stock Exchange
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The study investigates the relationship between the volatility of the Iraqi Stock Exchange Index (ISX), and the volatility of global oil prices benchmarks, Brent and West Intermediate Texas (WTI), in additional to the Iraqi Oil, Basra Crude Light (BSL) which represents the most exported Iraqi oil and the major influential factor on the Iraqi governmental revenues. Using monthly data covering the period: 1/2005-12/1205, econometrical and technical tools represented by Co-incretion, Vector Error Correction Model – VECM, Granger Causality, and Bollinger band were employed in order to explore the relationship between the variables.

The econometric analysis revealed the impact of the oil prices volatility on

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of The Iraqi University
Exclusion optimal portfolio from outlier by using fuzzy c-means clustering - analytical research at the Iraqi Stock Exchange
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This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

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Publication Date
Fri Sep 15 2023
Journal Name
Al-academy
Four Women: The E. Cassirer’s Theory and Its Analytical Potential for Understanding Iraqi Symbolic Painting by J. Saleem
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Based on the theoretical ideas of E. Cassirer, a methodology is developed and an analysis of the painting work by J. Saleem, a representative of modern Iraqi painting, is carried out. While comparing the artistic programme of J. Saleem and the views of E. Cassirer, the methodological potential of the theory of the symbol for the art criticism analysis of the regional painting is clarified. Comparative analysis with the inclusion of the works of B. Buffet, B. Turetsky, J. Miro helps to see the multiple meanings of the same cultural symbol in thematically similar works of different years, created in different socio-cultural circumstances. The article shows that for regions with a shorter history (France, Russia, Spain, etc.), which have lo

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