Zonguldak Karaelmas University

About: Zonguldak Karaelmas University is a based out in . It is known for research contribution in the topics: Population & Copolymer. The organization has 1939 authors who have published 4296 publications receiving 62466 citations.

The effects of peritoneal dialysis and hemodialysis on serum tumor necrosis factor-alpha, interleukin-6, interleukin-10 and C-reactive-protein levels.

Abstract: BACKGROUND: Markers of an acute phase reaction, such as C-reactive protein (CRP) or tumor necrosis factor-alpha (TNF-alpha) and interleukin (IL)-6, are predictive for cardiovascular morbidity and mortality in normal subjects and in chronic renal failure patients. In this study, we aimed to investigate serum TNF-alpha, IL-6, IL-10 and CRP levels in continuous ambulatory peritoneal dialysis (CAPD) and hemodialysis (HD) patients. MATERIALS AND METHODS: Serum levels of TNF-alpha, IL-6, IL-10 and CRP levels were measured in 30 patients who were just diagnosed with end-stage renal failure and treated, with 16 CAPD (nine female, seven male) and 14 HD (eight female, six male) patients, before CAPD or HD treatment and after 3 months from the beginning of CAPD or HD in patients with no clinical signs of infection. The control groups were 20 healthy persons of similar age and sex. Serum levels of TNF-alpha, IL-6, IL-10 and CRP were measured by enzyme-linked immunosorbent assay in stable CAPD and HD patients and in healthy persons. RESULTS: The mean serum levels of TNF-alpha, IL-6, IL-10 and CRP showed no significant differences between the CAPD and HD patients for the beginning values and the third month of treatment. However, serum TNF-alpha, IL-6, IL-10 and CRP levels were higher than the control group in the CAPD and HD patients regarding the beginning values and the third month of treatment (p < 0.001). CONCLUSIONS: CAPD and HD of the renal replacement therapy have no effects on serum CRP and cytokines.

Double inverse stochastic resonance with dynamic synapses.

Abstract: We investigate the behavior of a model neuron that receives a biophysically realistic noisy postsynaptic current based on uncorrelated spiking activity from a large number of afferents. We show that, with static synapses, such noise can give rise to inverse stochastic resonance (ISR) as a function of the presynaptic firing rate. We compare this to the case with dynamic synapses that feature short-term synaptic plasticity and show that the interval of presynaptic firing rate over which ISR exists can be extended or diminished. We consider both short-term depression and facilitation. Interestingly, we find that a double inverse stochastic resonance (DISR), with two distinct wells centered at different presynaptic firing rates, can appear.

Melatonin provides neuroprotection by reducing oxidative stress and HSP70 expression during chronic cerebral hypoperfusion in ovariectomized rats.

Abstract: Oxidative stress is believed to contribute to functional and histopathologic disturbances associated with chronic cerebral hypoperfusion (CCH) in rats. Melatonin has protective effects against cerebral ischemia/reperfusion injury. This effect has mainly been attributed to its antioxidant properties. In the present study, we evaluate the effects of melatonin on chronic cerebral hypoperfused rats and examined its possible influence on oxidative stress, superoxide dismutase (SOD) activity, reduced glutathione (GSH) levels, and heat shock protein (HSP) 70 induction. CCH was induced by permanent bilateral common carotid artery occlusion in ovariectomized female rats. Extensive neuronal loss in the hippocampus at day 14 following CCH was observed. The ischemic changes were preceded by increases in malondialdehyde (MDA) concentration and HSP70 induction as well as reductions in GSH and SOD. Melatonin treatment restored the levels of MDA, SOD, GSH, and HSP70 induction as compared to the ischemic group. Histopathologic analysis confirmed the protective effect of melatonin against CCH-induced morphologic alterations. Taken together, our results document that melatonin provides neuroprotective effects in CCH by attenuating oxidative stress and stress protein expression in neurons. This suggests melatonin may be helpful for the treatment of vascular dementia and cerebrovascular insufficiency.

Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

Abstract: The human brain is characterized by complex structural, functional connections that integrate unique cognitive characteristics. There is a fundamental hurdle for the evaluation of both structural and functional connections of the brain and the effects in the diagnosis and treatment of neurodegenerative diseases. Currently, there is no clinically specific diagnostic biomarker capable of confirming the diagnosis of major depressive disorder (MDD). Therefore, exploring translational biomarkers of mood disorders based on deep learning (DL) has valuable potential with its recently underlined promising outcomes. In this article, an electroencephalography (EEG)-based diagnosis model for MDD is built through advanced computational neuroscience methodology coupled with a deep convolutional neural network (CNN) approach. EEG recordings are analyzed by modeling 3 different deep CNN structure, namely, ResNet-50, MobileNet, Inception-v3, in order to dichotomize MDD patients and healthy controls. EEG data are collected for 4 main frequency bands (Δ, θ, α, and β, accompanying spatial resolution with location information by collecting data from 19 electrodes. Following the pre-processing step, different DL architectures were employed to underline discrimination performance by comparing classification accuracies. The classification performance of models based on location data, MobileNet architecture generated 89.33% and 92.66% classification accuracy. As to the frequency bands, delta frequency band outperformed compared to other bands with 90.22% predictive accuracy and area under curve (AUC) value of 0.9 for ResNet-50 architecture. The main contribution of the study is the delineation of distinctive spatial and temporal features using various DL architectures to dichotomize 46 MDD subjects from 46 healthy subjects. Exploring translational biomarkers of mood disorders based on DL perspective is the main focus of this study and, though it is challenging, with its promising potential to improve our understanding of the psychiatric disorders, computational methods are highly worthy for the diagnosis process and valuable in terms of both speed and accuracy compared with classical approaches.