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Pancreatic Stone Protein/ regenerating Protein (PSP/reg) as a Biochemical Marker for prediction of Microvascular Complications of Type 2 Diabetes Mellitus
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Background: Type 2 diabetes mellitus (T2DM) characterized by insulin resistance (IR) and progressive decline in functional beta (β) cell mass partially due to increased β cell apoptosis rate. Pancreatic stone protein /regenerating protein (PSP/reg) is produced mainly by the pancreas and elevated drastically during pancreatic disorder. Beta cells are experiencing apoptosis that stimulate the expression of PSP/reg gene in surviving neighboring cells, and that PSP/reg protein is subsequently secreted from these cells which could play a role in their regeneration.

Objectives: To analyze serum levels of PSP/reg protein in T2DM patients and evaluate its correlation with the microvascular complications of the disease.

Subjects and Methods: One hundred fifty participants (64 males, 86 females; aged 40–70 years) include T2DM patients with and without microvascular complications as well as healthy controls were enrolled in this study. Biochemical parameters like random blood glucose (RBG), glycated hemoglobin (HbA1c), lipid profile, urea and creatinine (Cr) were measured. Serum values of PSP/reg protein were measured by enzyme- linked immunosorbent assay (ELISA).

Results: Serum levels of PSP/reg protein were found significantly elevated in T2DM patients with microvascular complications compared with those of controls (p<0.001) and T2DM patients without microvascular complications (p< 0.001).PSP/reg protein is correlated with type 2 DM duration (p<0.001), RBG (p<0.001), and HbA1c (p<0.001). The area under the curve (AUC) for the presence of microvascular complications was 0.973.

Conclusion: PSP/reg protein may be used as biochemical marker to predict microvascular complications of T2DM.

 

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
Determination the optimum orbit for low Earth satellites by changing the eccentricity
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Abstract<p>The main objective of this paper is to determine an acceptable value of eccentricity for the satellites in a Low Earth Orbit LEO that are affected by drag perturbation only. The method of converting the orbital elements into state vectors was presented. Perturbed equation of motion was numerically integrated using 4<sup>th</sup> order Runge-Kutta’s method and the perturbation in orbital elements for different altitudes and eccentricities were tested and analysed during 84.23 days. The results indicated to the value of semi major axis and eccentricity at altitude 200 km and eccentricity 0.001are more stable. As well, at altitude 600 km and eccentricity 0.01, but at 800 km a</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Interdisciplinary Mathematics
Studying the result involution graphs for HS and McL Leech lattice groups
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Let G be a finite group, the result is the involution graph of G, which is an undirected simple graph denoted by the group G as the vertex set and x, y ∈ G adjacent if xy and (xy)2 = 1. In this article, we investigate certain properties of G, the Leech lattice groups HS and McL. The study involves calculating the diameter, the radius, and the girth of ΓGRI.

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
An Evolutionary Algorithm for Task scheduling Problem in the Cloud-Fog environment
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Abstract<p>The rapid and enormous growth of the Internet of Things, as well as its widespread adoption, has resulted in the production of massive quantities of data that must be processed and sent to the cloud, but the delay in processing the data and the time it takes to send it to the cloud has resulted in the emergence of fog, a new generation of cloud in which the fog serves as an extension of cloud services at the edge of the network, reducing latency and traffic. The distribution of computational resources to minimize makespan and running costs is one of the disadvantages of fog computing. This paper provides a new approach for improving the task scheduling problem in a Cloud-Fog environme</p> ... Show More
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Publication Date
Mon Mar 23 2020
Journal Name
International Journal Of Nanoscience
Gold Nanoparticles Synthesis Using Environmentally Friendly Approach for Inhibition Human Breast Cancer
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In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air And Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Wed Nov 01 2023
Journal Name
Biocatalysis And Agricultural Biotechnology
Enhancing the prodigiosin pigment by adding Ag\TiO2 synergism for antibacterial activity
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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Publication Date
Thu Dec 31 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ASTUDYON THERECORDOF EVALUATINGTHE SUPPLIERSACCORDING TO THE CONCEPT OF QUALITY AND BENEFITING FROM IT IN PRACTICE IN AL-FURAT STATE COMPANY AND FINDING POSSIBLE PROPOSALS FOR ITS DEVELOPMENT: ASTUDYON THERECORDOF EVALUATINGTHE SUPPLIERSACCORDING TO THE CONCEPT OF QUALITY AND BENEFITING FROM IT IN PRACTICE IN AL-FURAT STATE COMPANY AND FINDING POSSIBLE PROPOSALS FOR ITS DEVELOPMENT
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Success in selecting the best among the sources of supply is one of the most important factors in the efficiency of the procurement activity in the company, because the proper selection of the source of the supply significantly affect the achievement of what is desired by the factors of quality, quantity, price and service, and the ability of the competent supplier to meet everything associated with this Factors of commitments, hereby supporting the procurement function's efforts to fully discharge its responsibilities, and in view of adopting of Al-Furat company quality management system by applying the standards of ISO (9001: 2015) and purpose of getting the on-demand benefits from the application of international standards reg

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