Browsing by Subject "Case control study"

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Open Access
BRAPH: A graph theory software for the analysis of brain connectivity
(Public Library of Science, 2017) Mijalkov, M.; Kakaei, E.; Pereira, J. B.; Westman, E.; Volpe, G.
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. © 2017 Mijalkov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Open Access
MDM2 T309G polymorphism is associated with bladder cancer
(International Institute of Anticancer Research, 2006) Onat, O. E.; Tez, M.; Özçelik, T.; Törüner, G. A.
Recently, a functional T to G polymorphism at nucleotide 309 in the promoter region of the MDM2 gene (rs: 2279744, SNP 309) has been identified. This polymorphism has an impact on the expression of the MDM2 gene, which is a key negative regulator of the tumor suppressor molecule p53. The effect of T309G polymorphism of the MDM2 gene on bladder cancer susceptibility was investigated in a case-control study of 75 bladder cancer patients and 103 controls from Turkey. The G/G genotype exhibited an increased risk of 2.68 (95% CI, 1.34-5.40) for bladder cancer compared with the combination of low-risk genotypes T/T and T/G at this locus. These results show an association between MDM2 T309G polymorphism and bladder cancer in our study group. To the best of our knowledge, this is the first study reporting that MDM2 T309G polymorphism may be a potential genetic susceptibility factor for bladder cancer.
Open Access
Progesterone change in the late follicular phase affects pregnancy rates both agonist and antagonist protocols in normoresponders: a case-controlled study in ICSI cycles
(Taylor & Francis, 2016) Demir, B.; Kahyaoglu, I.; Guvenir, A.; Yerebasmaz, N.; Altinbas, S.; Dilbaz, B.; Dilbaz, S.; Mollamahmutoglu, L.
Objective: The aim of the presented study is to investigate the impact of progesterone change in the late follicular phase on the pregnancy rates of both agonist and antagonist protocols in normoresponders.Study design: A total of 201 normoresponder patients, who underwent embryo transfer were consecutively selected. 118 patients were stimulated using a long luteal GnRH agonist protocol and 83 using a flexible antagonist protocol. The level of change in late follicular phase progesterone was calculated according to the progesterone levels on the hCG day and pre-hCG day (1 or 2 days prior to hCG day) measurement.Results: Clinical pregnancy rates were comparable between long luteal and antagonist group (35.6 and 41%, respectively). The incidence of progesterone elevation on the hCG day was 11% in long luteal and 18% in antagonist group (p = 0.16). In pregnant cycles, p levels both on the hCG day and pre-hCG day measurement were significantly higher in antagonist than agonist cycles (p = 0.029, p = 0.038, respectively). The change of p level was statistically significant in non-pregnant cycles both for the agonist (-0.17 ± 0.07; 95% CI: -0.29 to -0.37) and antagonist groups (-0.18 ± 0.07; 95%CI: -0.31 to -0.04).Conclusions: Late follicular phase progesterone levels were stable during the cycles of pregnant patients irrespective of the protocols and were shown to be higher in pregnant patients in antagonist cycles when compared to agonist cycles.