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Öğe Anticancer activity of linalool: comparative investigation of ultrastructural changes and apoptosis in breast cancer cells(Taylor & Francis Inc, 2022) Elbe, Hülya; Öztürk, Feral; Yiğittürk, Gürkan; Baygar, Tuba; Çavuşoğlu, TürkerBreast cancer is the most common cancer in women in the world. Many anticancer drugs are currently used clinically have been isolated from plant species or are based on such substances. Linalool is aromatic compounds from the monoterpene group. It is the main constituents of essential oils and show antiproliferative, antioxidant, and antiseptic properties. The aim of this study was to investigate the antiproliferativeand apoptotic, effects of linalool in MCF-7 and MDA-MB-231 human breast cancer cells. MCF-7 and MDA-MB-231 human breast cancer cells were treated with different concentrations of linalool (100, 200, 400, 600, 800, 1000 mu M) at 24 h and 48 h. MTT assay for cell proliferation and Annexin V assay for apoptosis was done. The morphology of breast cancer cells was investigated by light microscope and scanning electron microscope (SEM). The study show that linalool significantly induced apoptosis in all groups as dose and time-dependent (p < .05). Linalool has apoptotic and antiproliferative properties in a concentration and time-dependent manner in breast cancer cells. The cytotoxic effects of linalool on MCF-7 and MDA-MB-231 human breast cancer cells was found to be associated with apoptotic cell death. Linalool was more effective on MCF-7 human breast cancer cells in smaller amounts.Öğe Basics of artificial intelligence for assisted reproductive technologies(IGI Global, 2024) Gökhan, Aylin; Kilic, Kubilay Dogan; Çavuşoğlu, Türker; Uyanikgil, YiğitIn the field of assisted reproductive technologies (ART), each cycle brings high cost and long-term clinical and laboratory studies. In order to eliminate the negative effects of this process on families, the necessity of standardized ART protocols that can be applied to each individual with low cost and fast results is essential. Although artificial intelligence has the potential to respond strongly to this need, the integration of artificial intelligence into ART is slower compared to other branches of medicine. Increasing understanding of artificial intelligence by researchers will accelerate this integration. In order to understand and be able to use artificial intelligence, this chapter will first discuss the conceptual confusion in artificial neural networks, deep learning, machine learning, and artificial intelligence. Finally, gaps will be filled with artificial intelligence-related application areas and examples in ART. © 2024, IGI Global. All rights reserved.Öğe Classification of Bovine Cumulus-Oocyte Complexes with Convolutional Neural Networks(2023) Çavuşoğlu, Türker; Gökhan, Aylin; Şirin, Cansın; Tomruk, Canberk; Kılıç, Kubilay Doğan; Ölmez, Emre; Er, OrhanAim: Determining oocyte quality is crucial for successful fertilization and embryonic development, and there is a serious correlation between live birth rates and oocyte quality. Parameters such as the regular/irregular formation of the cumulus cell layer around the oocyte, the number of cumulus cell layers and the homogeneity of the appearance of the ooplasm are used to determine the quality of the oocytes to be used in in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI) methods. Material and Methods: In this study, classification processes have been carried out using convolutional neural networks (CNN), a deep learning method, on the images of the cumulus-oocyte complex selected based on the theoretical knowledge and professional experience of embryologists. A convolutional neural network with a depth of 4 is used. In each depth level, one convolution, one ReLU and one max-pooling layer are included. The designed network architecture is trained using the Adam optimization algorithm. The cumulus-oocyte complexes (n=400) used in the study were obtained by using the oocyte aspiration method from the ovaries of the bovine slaughtered at the slaughterhouse. Results: The CNN-based classification model developed in this study showed promising results in classifying three-class image data in terms of cumulus-oocyte complex classification. The classification model achieved high accuracy, precision, and sensitivity values on the test dataset. Conclusion: Continuous research and optimization of the model can further improve its performance and benefit the field of cumulus-oocyte complexes classification and oocyte quality assessment.Öğe Effects of hyperbaric oxygen therapy on the morphological characteristics and survival of MCF-7 breast cancer cells(2023) Uyanıkgil, Yiğit; Yiğittürk, Gürkan; Elbe, Hülya; Yücel, Anıl; ALLI, Hakan; Ergözen, Serkan; Çavuşoğlu, TürkerAim: This study aims to determine the effects of hyperbaric oxygen therapy at different pressure values on cell morphology and cell survival in the MCF-7 breast cancer cell line. Materials and Methods: The experimental groups were formed by applying 100% oxygen to MCF-7 breast cancer cells at 1.5, 2, and 2.5 atmospheres for 2 hours. The control group did not receive treatment. At the end of the experiment, cell survival was investigated by CCK-8 analysis, cell shapes were determined by cresyl violet staining, and cell surface morphologies were determined by scanning electron microscope. Results: Cell viability was significantly reduced at atmospheric pressure of 1.5, 2, and 2.5 compared to the control group (p < 0.005). As pressure increased, the surface area of the cell decreased, nuclear condensation increased, and the cell borders became irregular. Cell membrane bleb and cell membrane porosity increased at 2 and 2.5 atmospheres. Conclusion: Hyperbaric oxygen therapy severely reduces the viability of MCF-7 breast cancer cells under increased pressure. It can induce apoptosis and change the shape and surface morphology of MCF-7 breast cancer cells. Although further studies are needed, our study supports the potential use of hyperbaric oxygen therapy in the treatment of breast cancer.Öğe Investıgatıon of ursodeoxycholıc acıd effects on sırolımus treated adıpose tıssue-derıved mesenchymal stem cells(2022) Uyanıkgil, Yiğit; Gündüz, Cumhur; Yiğittürk, Gürkan; Çavuşoğlu, Türker; Gökçe, Burak; None, Senem; Tomruk, CanberkObjective The usage of mesenchymal stem cells (MSC) with immunosuppressive drugs after organ transplantation is becoming remarkable in clinical applications. However, the drugs negatively affect MSCs. Ursodeoxycholic acid (UDCA), which is an antioxidant molecule, may reverse these effects. The study aims that to determine the effects of sirolimus and UDCA on human adipose tissue-derived MSCs (ADMSCs) individually and in combination. Material and Method The cytotoxicity of the agents was evaluated by WST-1 test in time and dose-dependent manner. The combinational effects were determined using isobologram analysis. Muse cell analyzer was used for the evaluation of apoptosis and cell cycle. Oxidative stress markers were measured by biochemical methods. Results IC50 dose of sirolimus was determined as 18.58?M in the 48th hour. Because no cytotoxic effect was observed at the studied doses of UDCA, the apoptosis, cell cycle, and oxidative stress indicator analyses were continued with a safe dose of 100 ?M. Sirolimus promoted apoptosis and inhibited cell proliferation. It was determined that UDCA reduced the apoptotic and anti-proliferative effects of sirolimus on ADMSCs with its anti-oxidant property. Conclusion The UDCA treatment in combination with immunosuppressive therapy after organ and tissue transplantation may have positive effects on ADMSCs.Öğe The effects of the urotensin-II receptor antagonist palosuran treatment on the corpora cavernosa of streptozotocin-induced diabetic rats(Elsevier Singapore Pte Ltd, 2025) Olukman, Murat; Can, Cenk; Ulker, Sibel; Uyanikgil, Yigit; Çavuşoğlu, Türker; Duzenli, Neslihan; Coskunsever, DenizObjective: This study aimed to investigate the effects of treatment with palosuran, a urotensin receptor blocker, on molecular changes in the corpora cavernosa (CC) in diabetic rats. Methods: Streptozotocin-induced diabetic rats were treated with palosuran 300 mg/kg per day for 6 weeks. Contraction of CC induced by potassium chloride, phenylephrine, and NG-nitro-L-arginine methyl ester and relaxation of CC induced by electrical field stimulation (EFS) and sodium nitroprusside (SNP) (endothelium-dependent and endothelium-independent stimuli, respectively), and Y-27632 (Rho-kinase inhibitor) were examined in organ baths. Direct contraction or relaxation induced by palosuran and urotensin-II (U-II) were also evaluated. The expression levels of nitric oxide synthetases (NOSs), RhoA, oxidative stress regulators, and U-II were analyzed by Western blotting or immunohistochemistry. Results: Induction of diabetes in rats resulted in the decreased relaxant response to SNP, decreased pD2 value of SNP, attenuated relaxant response to Y-27632 as well as the decreased RhoA expression in CC. Palosuran treatment of diabetic rats reversed all of these parameters; however, it further impaired the already weakened relaxation of diabetic CC in response to EFS. Although induction of diabetes did not change U-II expression in CC significantly, palosuran treatment reduced U-II expression in diabetic CC. The expression level of nNOS was lowered in diabetic CC; however, palosuran treatment did not change the decreased the neuronal NOS expression. In vitro exposure of diabetic CC strips to palosuran produced a direct relaxant response. Conclusion: Palosuran treatment did not affect the expression of NOSs or reduce nitrergic conduction induced by EFS stimulation in diabetic CC. However, while directly triggering a relaxant response, it did not induce a prominent contraction either by decreasing U-II expression, or increasing the sensitivity of CC to nitric oxide which suggested that palosuran has the potential to support erectile function. Further and comprehensive studies are required to clarify this issue. (c) 2025 Editorial Office of Asian Journal of Urology. Production and hosting by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).Öğe The transformative role of artificial intelligence in advancing bovine reproductive biology(IGI Global, 2024) Kilic, Kubilay Dogan; Gökhan, Aylin; Çavuşoğlu, TürkerThe integration of deep learning technologies into bovine reproductive biology heralds a significant paradigm shift that improves our approach to cattle breeding and reproductive health management. This chapter examines the versatile applications of deep learning, including image analysis, genomic information, and behavioral predictions, to advance the understanding and optimization of cattle reproduction. Adoption of these technologies facilitates a more detailed understanding of the genetic and physiological determinants of fertility and disease, contributing to the development of targeted breeding programs and improved herd health strategies. Despite the promise of deep learning to revolutionize greater efficiency and sustainability in livestock production, challenges around data privacy, security, and model interpretability remain. These issues require a concerted effort to develop ethical frameworks and transparent algorithms to ensure the responsible deployment of deep learning tools. This review highlights the transformative potential of deep learning in bovine reproductive biology and advocates for continued interdisciplinary collaboration to address the complexities of applying advanced computational techniques in agriculture. From this perspective, the future of livestock production is envisioned as a place where technological innovations and animal welfare converge, marking a new era in precision agriculture. © 2024, IGI Global. All rights reserved.
