Browsing by Author "Kelestimur, H."

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The antidepressant-like effects of kisspeptin-10 are reversed by kisspeptin antagonist peptide 234 in male rats
(Cellular and Molecular Biology Association, 2024) Keleştimur, Haluk; Kacar, E.; Yardimci, A.; Ertugrul, N.U.; Bulmus, O.; Ercan, Z.; Kelestimur, H.; Fizyoloji / Physiology
Kisspeptins are reported to be the most potent activators of the hypothalamus-pituitary-gonadal (HPG) axis known to date. Kisspeptin potently elicits gonadotropin-releasing hormone (GnRH) release and luteinizing hormone (LH) secretion, even in the pre-pubertal period. Beyond the hypothalamus, kisspeptin is also expressed in limbic and paralimbic brain regions, which are areas of the neurobiological network primarily implicated in emotional behaviors alongside sexual functions. Therefore, an increasing body of studies has implicated kisspeptin as having many influences on emotional behaviors. The study was set out to explore if the kisspeptin/GPR54 signaling system is required for the anti-depressant-like effect of kisspeptin-10 (KP-10), besides the regulation of the HPG axis. To test this concept, peptide 234 (P234), a kisspeptin antagonist, was given to the male rats, and its modulatory effect on the anti-depressant-like effects of kisspeptin was investigated by using a forced swimming test (FST). The study has also sought to know whether kisspeptin can exert its effects through adrenergic and serotonergic receptors. To investigate this, the agents yohimbine (Yoh), an alpha-2 adrenergic receptor antagonist, and cyproheptadine (Cry), a non-selective 5-HT2 serotonergic receptor antagonist, were administered in the experiments. Our results indicate that, in rats, the anti-depressant-like effects of KP-10 in a modified rat FST are mediated by GPR54 receptors since the kisspeptin antagonist peptide 234 reversed kisspeptin-induced anti-depressant-like effects. Our data also demonstrate that the antidepressant-like effects of kisspeptin, at least in part, are mediated by an interaction of the alpha-2 adrenergic and 5-HT2 serotonergic receptors. © 2024 Cellular and Molecular Biology Association. All rights reserved.
Citation Count: 0
A New Method Based on Local Binary Gaussian Pattern for Classification of Rat Estrous Cycle Stages Using Smear Images
(Elsevier Ltd, 2025) Keleştimur, Haluk; Kilic, I.; Yaman, O.; Kacar, E.; Oz, Z.D.; Ozdede, M.R.; Kelestimur, H.; Fizyoloji / Physiology
In this study, a unique dataset was created by classifying the images of vaginal smears taken from rats under a microscope for 4 different cycles. Classifying a new case image with the help of this dataset is a computer vision problem. In this study, to improve the weaknesses of the LBP algorithm, a new feature extraction method called Local Binary Gaussian Pattern (LBGP) is developed based on the Gaussian matrix, which helps to remove noise in images. Local Binary Gaussian Pattern proposes a Gaussian-like filter inspired by the Gaussian matrix. After converting the smearing image to the gray histogram, the image features obtained with the help of the Local Binary Pattern (LBP) and our proposed Local Binary Gaussian Pattern (LBGP) feature extractor are combined to obtain features that we call hybrid features. From these features, the ones above a certain threshold value are selected with the help of Neighborhood Component Analysis (NCA), and a Hybrid + Neighborhood Component Analysis (NCA) approach is presented. All hybrid features and hybrid features reduced by Neighborhood Component Analysis were trained with Support Vector Machine (SVM), Decision Trees (DT), Naive Bayes (NB), and k-nearest Neighbors (k-NN) classifiers. According to the classification results, it is seen that the Support Vector Machine (SVM) is effectively classified with the trained classifier. With the Support Vector Machine (SVM) classifier, a success rate of over 90 % (90.25 %) was achieved. Considering the difficulty of classifying smearing images, this result is promising for the future stages of this study. © 2024 Elsevier Ltd