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Adyaman, Turkey

Adıyaman University is a state university, established in 2006 in Adıyaman province, Turkey. Wikipedia.


Aim: The tumor suppressor gene Ras association domain family 1 isoform A (RASSF1A) regulates cell cycle regulation, apoptosis and microtubule stability and is inactivated by promoter hypermethylation at a high frequency in hepatocellular carcinoma (HCC). A guanine (G)/thymine (T) common single nucleotide polymorphism (SNP) at first position of codon 133 in RASSF1A gene determines an alanine (Ala) to serine (Ser) (Ala133Ser) amino acidic substitution which may alter cancer risk by influencing the function of RASSF1A protein. Methods: To determine the association of the RASSF1A Ala133Ser polymorphism with the risk of HCC development in a Turkish population, a hospital-based case-control study was designed consisting of 236 subjects with HCC and 236 cancer-free control subjects matched for age, gender, smoking and alcohol status. The genotype frequency of the RASSF1A Ala133Ser polymorphism was determined by using a polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay. Results: Allele and genotype associations of RASSF1A Ala133Ser polymorphism with HCC susceptibility were observed in comparisons between the patient and control samples (P< 0.001). Risk of HCC development in this Turkish population was significantly increased in carriers of the Ser133 variant allele of Ala133Ser polymorphism (Ala/Ser and Ser/Ser genotypes) when compared with homozygote Ala/Ala genotype (OR = 5.47, 95% CI = 3.63-8.25, P= 0.001). Conclusion: Because our results suggest for the first time that the Ser133 allele of RASSF1A Ala133Ser polymorphism may be a genetic susceptibility factor for HCC in the Turkish population, further independent studies are required to validate our findings in a larger series, as well as in patients of different ethnic origins. © 2012 Elsevier B.V.


This research was undertaken to determine the sugars, organic acids, phenolic compositions and antioxidant capacities of grapefruits (cvs. Rio red, Star ruby, Ruby red and Handerson) grown in Turkey. High-performance liquid chromatographic methods were used to identify and quantify three sugars (sucrose, glucose and fructose) and five organic acids (oxalic, citric, ascorbic, malic and succinic acids). The major organic acid was found as citric acid. With regard to sugars, sucrose was present in the largest amounts for grapefruit juices. The sum of sugars ranged from 75.81 to 85.43gL-1 and the sum of organic acids ranged from 22.50 to 26.78gL-1. A total of 15 phenolic compounds were identified and quantified in grapefruit juices, including hydroxybenzoic acids (4), hydroxycinnamic acids (5), and flavanones (6) compounds. Total phenolic content ranged from 441.09 (Ruby red) to 725.71mgL-1 (Star ruby) and antioxidant activity (AE) ranged from 34.51(Ruby red) to 128.37×10-3 (Star ruby). © 2010 Elsevier B.V.


Bugutekin A.,Adiyaman University
Energy Education Science and Technology Part A: Energy Science and Research | Year: 2011

Solar Chimney Power Plants (SCPP) consists of three main components: solar collector, chimney and the turbine. Air under the collector is heated by the greenhouse effect, the air density is reduced and the air rises toward the chimney at the center of the collector. Thus, electricity is produced by the turbine located at the entrance of the chimney. In this study, a Solar Chimney Power Plants (SCPP) system, 15 m in height, 0.8 m in diameter of chimney, a 0.004 m thick transparent glass floor and a collector having maximum of 27 m in diameter, has been established into Adiyaman University campus area at 669 altitude of Adiyaman province placed over 38° 11′ -37° 25′ north latitude and 39° 14′ - 37° 31′ east longitude at Turkey's Southeastern Anatolia region. The aim of this study is to investigate the effect of the collector diameters on air flow rate and temperature in the chimney by using mathematical theories. For this purpose at certain times of the day, air flow rate and temperature in the chimney, ambient temperature, ambient air velocity, surface temperature of collector and solar radiation values of Adiyaman are measured and evaluated for collectors having different diameters. As a result, collector having large diameter means more solar energy. As the collector area grows, the ground temperature increases %35-55 compared to ambient temperature and at further studies, it is observed that temperature and air flow rate at the point turbine placed (C 2) increase quickly as diameter of collector increases. © Sila Science.


Subasi A.,International BURCH University | Gursoy M.I.,Adiyaman University
Expert Systems with Applications | Year: 2010

In this work, we proposed a versatile signal processing and analysis framework for Electroencephalogram (EEG). Within this framework the signals were decomposed into the frequency sub-bands using DWT and a set of statistical features was extracted from the sub-bands to represent the distribution of wavelet coefficients. Principal components analysis (PCA), independent components analysis (ICA) and linear discriminant analysis (LDA) is used to reduce the dimension of data. Then these features were used as an input to a support vector machine (SVM) with two discrete outputs: epileptic seizure or not. The performance of classification process due to different methods is presented and compared to show the excellent of classification process. These findings are presented as an example of a method for training, and testing a seizure prediction method on data from individual petit mal epileptic patients. Given the heterogeneity of epilepsy, it is likely that methods of this type will be required to configure intelligent devices for treating epilepsy to each individual's neurophysiology prior to clinical operation. © 2010 Elsevier Ltd. All rights reserved.


Diner I.,Adiyaman University
Advances in Engineering Software | Year: 2011

Determination of deformation modulus and coefficient of subgrade reaction of soils have major importance, whether the projects are in design, and construction or compaction assessment stage of earth filling structures. Plate load test is one of the frequently used method to directly determine the parameters but the method is both costly and time consuming. For this reason, this paper is concerned with the applications of artificial neural networks (ANN) and simple-multiple regression analysis to predict deformation modulus and coefficient of subgrade reaction of compacted soils from compaction parameters (such as maximum dry density (MDD) and optimum moisture content (OMC), field dry density (FDD), and field moisture content (FMC)). Regression analysis and artificial neural network estimation indicated that there are acceptable correlations between deformation modulus and coefficient of subgrade reaction and these parameters. Artificial neural networks model exhibits higher performance than traditional statistical model for predicting deformation modulus and coefficient of subgrade reaction. © 2010 Elsevier Ltd. All rights reserved.

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