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RISS 인기검색어
- 검색키워드
- 저자 : Gamze Erzin (검색결과 4 건)
- 무료
- 기관 내 무료
- 유료
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Thiol/Disulfide Homeostasis in Bipolar and Unipolar Depression
Gamze Erzin,Güven Özkaya,Canan Topçuoğlu,Rabia Nazik Yüksel,Özcan Erel,Emine Feyza Yurt,Erol Göka,Sinan Gülöksüz 대한정신약물학회 2020 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.18 No.3
Objective: Bipolar disorder and unipolar depressive disorder are complex phenotypes. There appear to be phenotypical, mechanistic, and therapeutic differences between bipolar depression (BD) and unipolar depression (UD). There is a need for understanding the underlying biological variation between these clinical entities. The role of oxidative processes underlying bipolar disorder and depression has been demonstrated. Thiol-disulfide homeostasis (TDH) is a recent oxidative stress marker. In this study, we aimed to inspect patients with bipolar depression and unipolar depression in terms of thiol-disulfide balance and to compare them with healthy controls. Methods: Patients admitted to the outpatient clinic of Ankara Numune Training and Research Hospital and diagnosed either as a depressive episode with bipolar disorder (n = 37) or unipolar depression (n = 24) according to DSM-5 criteria, along with healthy controls (HC) (n = 50), were included in the study. Native thiol, total thiol, and disulfide levels were compared across the groups. Results: In comparison to HC, both BD and UD groups had higher disulfide levels, disulfide/native thiol ratio, and disulfide/total thiol ratio. No significant differences between BD and UD were detected in terms of disulfide level, disulfide/ native thiol ratio, and disulfide/total thiol ratio. Conclusion: Increased levels of disulfide, native thiol, and disulfide/total thiol ratios compared to healthy controls in both UD and BD groups may be indicative of the presence of oxidative damage in these two clinical conditions. To clarify the role of oxidative stress in the pathophysiology of depressive disorders and investigate TDH, longitudinal studies in patients with medication-free UD and BD are required.
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Could Irisin Levels be Affected by Physical Activity in Patients with Schizophrenia?
Gamze Erzin,Olga Güriz,Ali Yalçındağ,Akfer Kahıloğulları,Sibel Örsel 대한정신약물학회 2021 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.19 No.4
Objective: The aim of this study was to explore the effect of physical activity and metabolic parameters on irisin levels in patients with schizophrenia and healthy controls. Methods: Ninety-six patients with schizophrenia and 63 healthy controls comprised the study population. The participants were separated into three groups: inactive, low activity, and sufficiently active according to International Physical Activity Questionnaire short form (IPAQ-SF). We measured irisin levels using Enzyme linked immunosorbent assay. We also calculated exercise levels by using the IPAQ-SF for each individual. The independent samples t test was used in the data analysis to compare irisin levels according to the activity levels of the patients with schizophrenia and controls. Results: The levels of irisin were higher in the healthy controls (p < 0.001) compared to schizophrenia groups. When the activity levels of the schizophrenia and healthy control groups were compared, the irisin levels of the low activity and sufficiently active groups with schizophrenia were found to be lower than those of the low activity and sufficiently active groups in the healthy controls (respectively p = 0.014; p < 0.001). Conclusion: Irisin levels could be affected by physical activity and these results must be supported with new studies.
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Hatice Ayça Kaloğlu,Sibel Örsel,Gamze Erzin 대한정신약물학회 2023 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.21 No.4
Objective: Irisin is a myokine that is involved in neurogenesis, neuronal proliferation, and neuronal differentiation. Many research examine the relationship between irisin and schizophrenia. In this study, we aimed to evaluate the relationship between irisin levels and cognitive functions in individuals with schizophrenia. Methods: Ninety-six individuals who were diagnosed with schizophrenia were included. The Brief Psychiatric Rating Scale (BPRS) was used to assess disease severity. To evaluate the cognitive functions of the patients, the trail-making test was evaluated with the A and B forms and the verbal memory processes scale. After a 12-hour night fast, samples of fasting blood were obtained from the participants. Results: There was no significant correlation between irisin, duration of disease, and BPRS total score. In the analysis performed, a positive correlation was found between the plasma irisin level and the error score of the trail-making test form B. Other than that, no correlation was found between irisin level and cognitive performance in schizophrenia patients. In addition, in subgroup analysis between genders, it was determined that the duration of the trail-making test B was longer in female schizophrenia patients. Conclusion: In this study, there was a positive correlation between the trail-making test B-form error scores and the irisin levels. This relationship between impaired executive functions and irisin levels may suggest that the irisin level is increased as compensation for the impairment in executive functions. More research is needed to understand the role of irisin in cognitive impairment and schizophrenia.
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An Overview of Deep Learning Algorithms and Their Applications in Neuropsychiatry
Gokhan Guney,Busra Ozgode Yigin,Necdet Guven,Yasemin Hosgoren Alici,Burcin Colak,Gamze Erzin,Gorkem Saygili 대한정신약물학회 2021 CLINICAL PSYCHOPHARMACOLOGY AND NEUROSCIENCE Vol.19 No.2
Deep learning (DL) algorithms have achieved important successes in data analysis tasks, thanks to their capability of revealing complex patterns in data. With the advance of new sensors, data storage, and processing hardware, DL algo-rithms start dominating various fields including neuropsychiatry. There are many types of DL algorithms for different data types from survey data to functional magnetic resonance imaging scans. Because of limitations in diagnosing, esti-mating prognosis and treatment response of neuropsychiatric disorders; DL algorithms are becoming promising approaches. In this review, we aim to summarize the most common DL algorithms and their applications in neuro-psychiatry and also provide an overview to guide the researchers in choosing the proper DL architecture for their research.
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