There are many parameters that have effects the success of athletes, like exercise, motivation, determination, nutrition, all of which have genetic backgrounds. To have the optimal approach, all of these conditions should complement each other. In this study, we aimed to analyze and compare the monocarboxyl transferase 1 (MCT1) rs1049434 polymorphism, which is important to determine the lactate levels, in long and short distance running athletes. A total of 30 athletes, 15 of which were power athletes and 15 were endurance, were enrolled for the study. DNA isolations were carried out by using commercially available DNA isolation Kit, and genotyping process was by real-time PCR. Of the 15 power athletes, 14 (93%) and 1 (7%) athletes had AT and TT genotypes, respectively. We detected no AA genotype in power athletes. In endurance cohort, 4 (27%), 8 (53%) and 3 (20%) athletes had AA, AT and TT genotypes, respectively. When we count the alleles, A allele was counted as 14 (47%) and 16 (53%) in power and endurance athletes. For T allele, 16 (53%) and 14 (47%) were counted in power and endurance cohorts. No statistically significant difference was found between groups in the terms of genotype and allele. In our cohort, AT genotype was higher in both groups, whereas both alleles were equal in our cohort. Our basic goal is to be able to channel the athlete correctly and carry it to maximum success in a shorter period of time considering the genetic predisposition.

Objective: Genetic and environmental risk factors constitute the major part of the etiology of autism, a multifactorial disorder. In this study, we aimed to investigate the MTHFR (Methyltetrahydrofolate Reductase Gene) C677T polymorphism in autistic children who were subjected to glutamate - caseinous and GAPS (Bowel and Psychology Syndrome) diets and to determine whether autism was related to decrease of enzyme activity caused by 677T allele of MTHFR gene.
Materials and Methods: Thirty autistic and 90 healthy children were included in the study. DNA was obtained using a special commercial kit (GeneAll, Korea). Genotyping was performed by PCR - RFLP (Polymerase Chain Reaction-Restriction Fragment Length Polymorphism) protocol and images were obtained by agarose gel electrophoresis.
Results and Discussion: No statistically significant difference was found in the MTHFR 677T allele frequency as 13.33% in the patient group and 19.4% in the control group as p = 0.285. Due to the fact that the number of patients included in the study was not desired and not homogeneous, we recommend looking at MTHFR A1298C polymorphism and COMT (catechol-O-methyltransferase), BDNF (brain-derived neurotrophic factor), PTEN (phosphate and tensin homolog) genes.

This study aimed to investigate the radiation attenuation properties of seven brain regions namely Frontal, Occipital, Parietal, Temporal cortexes, Hippocampus, Thalamus and Cerebellum in terms of their elemental compositions. Monte Carlo N-Particle Transport Code System-extended (MCNPX) version 2.6.0 (Los Alamos National Lab, USA) general purpose Monte Carlo code has been employed in order to calculate the mass attenuation coefficients of those aforementioned brain regions. A satisfactory agreement has been obtained on the mass attenuation coefficients (µ/ρ) calculated by MCNPX and XCOM for those brain regions under investigation. The results underlined that Cerebellum has the highest mass attenuation coefficients in terms of the radiological energy values. This can be explained by the elemental mass fraction value of Chlorine (Cl) in Cerebellum. It could be deduced that the intensity of diagnostic radiation can be more attenuated in Cerebellum than rest of the brain regions during the brain CT or brain PET examinations. The data from the present paper would be useful for the use of standard simulation geometry and mass attenuation coefficients for medical physics as well as the applications of radiation physics.

Genomic information obtained from robust analysis methods such as microarray and next generation sequencing reveals underlying disease mediating factors and potential diagnostic biomarkers. Data mining methods have been widely chosen for classification and regression studies of health sciences as well as other disciplines since the beginning. In the present study, public Gene Expression Omnibus (GEO) genome wide expression dataset (ID: GSE12679) consisting of mRNA transcripts of post-mortem brain tissues in schizophrenic and normal patients were analyzed by using Multilayer Perceptron Neural Network (MLP NN) algorithm. A set of most differentially expressed genetic features (p<0.001) were used for creating the classifier which can predict disease states in test set with ~82% accuracy. Differentially expressed genes used as classifying biomarkers gain utmost importance for revealing hidden underlying genetic factors associated with important psychiatric diseases. We could also suggest that such data mining tools might be applicable for developing genome-based diagnostic tools.

The serotonin transporter (5-hydroxytryptamine transporter, 5- HTT) gene (SLC6A4) is considered to be one of the most important candidate genes for genetic involvement in psychiatric conditions like anxiety, self- confidence and motivation. In the present study, we aimed to analyze the distribution of SLC6A4 promoter long and short (L and S, respectively) polymorphism in young Turkish basketball players. We enrolled 24 players in the study, 17 were females and 7 were males. 12%, 35% and 53% of the females had SS, LS and LL genotype, respectively; whereas 28,5% of the males had SS and the same percentage of them had LS, and 43% had LL genotype. When we examined the allelic counts, L allele was recorded as 71% in females and 57% in males; S allele was 29% in females and 43% in males. Our results were in agreement with the previous ones, indicating the presence of L allele in individuals dealing with sport. We suggest that SLC6A4 promoter analysis is important for genetic counseling for the individuals who are prone to be successful in sports.