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    Basics of artificial intelligence for assisted reproductive technologies
    (IGI Global, 2024) Gökhan, Aylin; Kilic, Kubilay Dogan; Çavuşoğlu, Türker; Uyanikgil, Yiğit
    In 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.
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    Effects of vitrification solution supplemented with platelet-rich plasma in rat ovarian tissue cryopreservation
    (Tubitak Scientific & Technological Research Council Turkey, 2023) Gokhan, Aylin; Cavusoglu, Tuerker; Kilic, Kubilay Dogan; Sirin, Cansin; Tomruk, Canberk; Yigitturk, Guerkan; Erbas, Oytun
    Background/aim: The subject of this study was to investigate the utility of platelet-rich plasma (PRP) in the cryopreservation process to reduce cryodamage and increase tissue viability.Materials and methods: Twenty-one female Wistar rats were randomly allocated to three groups. In Group 1 (G1), rats were not subjected to vitrification (n = 7). Group 2 (G2) was the vitrification group in which PRP was added to the basic vitrification solution (n = 7). Group 3 (G3) was the vitrification group in which fetal bovine serum was added to the basic vitrification solution (n = 7). Warmed tissues were evaluated with histochemical (HC) and immunohistochemical (IHC) staining, the TUNEL method, immunofluorescence (IF) staining, and biochemical analyses.Results: The percentages of IHC staining, TUNEL method positivity, and IF staining were significantly higher in G2 compared to both G1 and G3 (P < 0.05). G2 ovaries exhibited a significant increase in both malondialdehyde and catalase values in comparison to G1 (P < 0.05). In HC staining, degenerations in primary and secondary follicles and in ovarian tissue were more common in the PRP-supplemented group. The calcium used in PRP activation was suspected to have increased the degeneration and prevented the possible positive effects of PRP.Conclusion: To the best of our knowledge, PRP-supplemented vitrification solution was used for the first time in the literature in this study in whole rat ovarian tissue vitrification. If PRP is to be used as a component in vitrification solution for rat ovarian tissue, the use of lower amounts of calcium or different methods in PRP activation, or the use of nonactivated PRP, should be considered from the beginning.
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    Platelet-Rich Plasma in Vitrification; is it Helpful or Harmful?
    (Univ Agriculture, Fac Veterinary Science, 2023) Cavusoglu, Turker; Gokhan, Aylin; Tomruk, Canberk; Sirin, Cansin; Kilic, Kubilay Dogan; Yigitturk, Guerkan
    Human and animal studies on cryoprotectants and freezing solutions are still needed to establish a simple yet reliable protocol and increase the success of cryopreservation. The main aim of this study was to evaluate the short- and long-term effects of platelet-rich plasma, a well-known antioxidant substance due to its contents including bioactive molecules and growth factors, on whole ovarian tissue cryopreservation. Fresh tissues (control group, G1) were subjected to histological tissue processing without any treatment. Ovaries treated with platelet-rich plasma (PRP)-supplemented vitrification solution were subjected to tissue processing without cryostorage group 2 (G2) or following six months of cryostorage group 3 (G3). Steps in G2 and G3 were also performed for group 4 (G4) and group 5 (G5), respectively, except that the vitrification solution was supplemented with fetal bovine serum. PRP was activated with calcium chloride (CaCl2) after double centrifugation. Ethylene glycol, dimethyl sulfoxide, and sucrose were used as cryoprotective agents in all groups. Histomorphological changes were evaluated with the semi-quantitative histochemical-scoring algorithm. Apoptotic and antiapoptotic effects and intercellular connections were evaluated with immunohistochemical staining of Bax, Bcl-2, Caspase-3 (C3), Connexin-43 (Cx-43), and TUNEL analysis. Cryopreservation with PRP-supplementation (G3) significantly increased tissue degeneration (p<0.05). There was an increase in the number of degenerated both primary and secondary follicles (p<0.05), and an increase in the immune expression of Bax, C3 and Cx-43 and TUNEL assay in G3 was observed compared to other groups (p<0.05). Since the morphology of primordial follicles was more preserved than other follicles in all groups, primordial follicles were not included in the follicle count. Our study suggested that cryopreservation with PRP-supplemented vitrification solution caused excessive damage to rat ovaries. We assumed that CaCl2 might have further provoked this cellular damage.
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    The transformative role of artificial intelligence in advancing bovine reproductive biology
    (IGI Global, 2024) Kilic, Kubilay Dogan; Gökhan, Aylin; Çavuşoğlu, Türker
    The 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.