Abstract

The comet test, also known as single cell gel electrophoresis (SCGE), is a fast, highly sensitive, and very simple technique used to identify DNA damage at the cellular level. This methodology integrates the simplicity of biochemical techniques for detecting DNA single strand breaks, soluble base labile sites, and connecting, in addition to the conventional cell-by-cell method used in cytogenetic assays. The Comet test, often used in Geno toxicological and biomonitoring investigations, typically involves the examination of prepared utilizing a fluorescent microscope (indicated by green light) and subsequent visible scoring. The fundamental goal of this study was to use image processing methods to automatically classify and measure DNA damage by analyzing comet test pictures, rather than relying on vision assessment of comet photographs.

References

• Blaschke, T. (2010). Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1), 2-16.
• Cotelle, S., & Férard, J. F. (1999). Comet assay in genetic ecotoxicology: a review. Environmental and Molecular Mutagenesis, 34(4), 246-255.
• Da Rocha, C. A. M., De Lima, P. D. L., Santos, R. A. D., & Burbano, R. M. R. (2009). Evaluation of genotoxic effects of xenobiotics in fishes using comet assay—a review. Reviews in Fisheries Science, 17(2), 170-173.
• Ekstrom, M. P. (2012). Digital image processing techniques (Vol. 2). Academic Press.
• Fatima, M., Usmani, N., Firdaus, F., Zafeer, M. F., Ahmad, S., Akhtar, K., Hossain, M. M. (2015). In vivo induction of antioxidant response and oxidative stress associated with genotoxicity and histopathological alteration in two commercial fish species due to heavy metals exposure in northern India (Kali) river. Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology, 176, 17-30.
• Frenzili, G., Nigro, M., Lyons, B. P. (2009). A review: Use of the comet assay in aquatic environmental impact assessments. Mutation Research, 681, 80-92.
• Glenys Morgan, histogram image 17 Mart 2024, https://www.shootpetals.com/histogram.html#gallery[pageGallery]/2/
• Güner, U., & Muranlı, F. D. G. (2013). Balıklarda tek hücre jel elektroforezi (comet assay). Karadeniz Fen Bilimleri Dergisi, 3(9), 103-114.
• Hartmann, S., & Lucius, R. (2003). Modulation of host immune responses by nematode cystatins. International Journal for Parasitology, 33(11), 1291-1302.
• Jha, A. N. (2008). Ecotoxicological applications and significance of the comet assay. Mutagenesis, 23(3), 207-221.
• Kacar, A., Pazi, I., Gonul, T., Kucuksezgin, F. (2016). Marine pollution risk in a coastal city: use of an eco-genotoxic tool as a stress indicator in mussels from the Eastern Aegean Sea. Environmental Science and Pollution Research, 23(16), 16067-16078.
• Kleinjans, J. C., van Schooten, F. J. (2002). Ecogenotoxicology: the evolving field. Environmental Toxicology and Pharmacology, 11(3-4), 173-179.
• Klobučar, G. I., Štambuk, A., Pavlica, M., Perić, M. S., Hackenberger, B. K., Hylland, K. (2010). Genotoxicity monitoring of freshwater environments using caged carp (Cyprinus carpio). Ecotoxicology, 19(1), 77.
• Końca, K., Lankoff, A., Banasik, A., Lisowska, H., Kuszewski, T., Góźdź, S., Wojcik, A. (2003). A cross-platform public domain PC image-analysis program for the comet assay. Mutation Research/Genetic Toxicology and Environmental Mutagenesis, 534(1-2), 15-20.
• Lee, R. F., Steinert, S. (2003). Use of the single cell gel electrophoresis/comet assay for detecting DNA damage in aquatic (marine and freshwater) animals. Mutation Research/Reviews in Mutation Research, 544(1), 43-64.
• Li, Xiaoli, and Bing Liu (2014): Data Classification: Algorithms and Applications "Rule-Based Classification." , 121-156. ISBN 9780367659141, Chapman & Hall
• Liu, Y., Browne, W.N. & Xue, B. (2022). Visualizations for rule-based machine learning. Natural Computing, 21, 243–264 (2022).
• Mitchelmore, C. L., Chipman, J. K. (1998). DNA strand breakage in aquatic organisms and the potential value of the comet assay in environmental monitoring. Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis, 399(2), 135-147.
• Rottensteiner, F., Trinder, J., Clode, S., Kubik, K. (2005). Using the Dempster–Shafer method for the fusion of LIDAR data and multi-spectral images for building detection. Information Fusion, 6(4), 283-300.
• Singh, R. J., Hymowitz, T. (1988). The genomic relationship between Glycine max (L.) Merr. and G. soja Sieb. and Zucc. as revealed by pachytene chromosome analysis. Theoretical and Applied Genetics, 76(5), 705-711.
• Şekeroğlu, Z. A., Şekeroğlu, V. (2011). Genetik toksisite testleri. TÜBAV Bilim Dergisi, 4(3), 221-229.
• Uzar Dinlemek, M. (2012). Otomatik bina çıkarımı uygulamalarında çoklu algılama sistemi verilerinin kullanım olanaklarının analizi.
• Kutlu, Y., Turan, C. (2018). An Intelligent Software for Measurements of Biological Materials: BioMorph. Natural and Engineering Sciences, 3(2), 225-232.
• Weiss, S. M., Indurkhya, N. (1995). Rule-based machine learning methods for functional prediction. Journal of Artificial Intelligence Research, 3, 383-403.
• Zhou, Y., Yang, H., Liu, S., Yuan, X., Mao, Y., Liu, Y., Zhang, F. (2006). Feeding and growth on bivalve biodeposits by the deposit feeder Stichopus japonicus Selenka (Echinodermata: Holothuroidea) co-cultured in lantern nets. Aquaculture, 256(1-4), 510-520.