Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods
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Difenoconazole is a fungicide extensively used in agriculture. The aim of this study was to evaluate the effects of difenoconazole fungicide on the sperm quality of rats. Wistar rats were divided into four groups: control and exposed to 5 (D5), 10 (D10), or 50 mg−1 kg bw−1day (D50) of difenoconazole for 30 days, by gavage. Classical sperm parameters and surface-enhanced Raman scattering (SERS) were performed. Progressive motility, acrosomal integrity, and percentage of morphologically normal spermatozoa were reduced in the D10 and D50 groups in comparison with the control group. Sperm viability was reduced only in the D50 group. Sperm number in the testis and caput/corpus epididymis and daily sperm production were reduced in the three exposed groups. SERS measurements showed changes in the spectra of spermatozoa from D50 group, suggesting DNA damage. In addition, machine learning (ML) methods were used to evaluate the performance of three classification algorithms (artificial neural network—ANN, K-nearest neighbors—K-NN, and support vector machine—SVM) in the identification task of the groups exposed to difenoconazole. The results obtained by ML algorithms were very promising with accuracy ≥ 90% and validated the hypothesis of the exposure to difenoconazole reduces sperm quality. In conclusion, exposure of rats to different doses of the fungicide difenoconazole may impair sperm quality, with a recognizable classification pattern of exposure groups.
KeywordsFungicide Reproduction Spermatozoa Rat Raman spectroscopy Artificial intelligence
This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.
University of Western São Paulo (UNOESTE). FAPESP (2013/14262-7 and 2014/11410-8) and CNPq.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
- Abd-Alrahman SH, Elhalwagy ME, Kotb GA, Farid H, Farag AA, Draz HM, Isa AM, Sabico S (2014) Exposure to difenoconazole, diclofop-methyl alone and combination alters oxidative stress and biochemical parameters in albino rats. Int J Clin Exp Med 7:3637–3646Google Scholar
- Clegg ED, Perreault SD, Klinefelter GR (2001) Assessment of Male reproductive toxicology. In: Wallace H (ed) Principles and methods of toxicology, 4th edn. Taylor & Francis, Philadelphia, pp 1263–1299Google Scholar
- Goetz AK, Ren H, Schmid JE, Blystone CR, Thillainadarajah I, Best DS, Nichols HP, Strader LF, Wolf DC, Narotsky MG, Rockett JC, Dix DJ (2006) Disruption of testosterone homeostasis as a mode of action for the reproductive toxicity of triazole fungicides in the male rat. Toxicol Sci 95:227–239. https://doi.org/10.1093/toxsci/kfl124. CrossRefGoogle Scholar
- Haykin S (1999) Neural networks: a comprehensive foundation, 2nd edn. Prentice Hall, New JerseyGoogle Scholar
- Hinfray N, Porcher JM, Brion F (2006) Inhibition of rainbow trout (Oncorhynchus mykiss) P450 aromatase activities in brain and ovarian microsomes by various environmental substances. Comp Biochem Physiol C Toxicol Pharmacol 144:252–262. https://doi.org/10.1016/j.cbpc.2006.09.002. CrossRefGoogle Scholar
- Jankowska M, Łozowicka B, Kaczyński P (2019) Comprehensive toxicological study over 160 processing factors of pesticides in selected fruit and vegetables after water, mechanical and thermal processing treatments and their application to human health risk assessment. Sci Total Environ 652:1156–1167. https://doi.org/10.1016/j.scitotenv.2018.10.324. CrossRefGoogle Scholar
- Lang T, Dechant M, Sanchez V, Wistuba J, Boiani M, Pilatz A, Stammler A, Middendorff R, Schuler G, Bhushan S, Tchatalbachev S, Wübbeling F, Burger M, Chakraborty T, Mallidis C, Meinhardt A (2013) Structural and functional integrity of spermatozoa is compromised as a consequence of acute uropathogenic e.coli-associated epididymitis. Biol Reprod 89:1–10. https://doi.org/10.1095/biolreprod.113.110379 CrossRefGoogle Scholar
- Menkveld R, Rhemrev JP, Franken DR, Vermeiden JP, Kruger TF (1996) Acrosomal morphology as a novel criterion for male fertility diagnosis: relation with acrosin activity, morphology (strict criteria), and fertilization in vitro. Fertil Steril 65:637–644. https://doi.org/10.1016/S0015-0282(16)58167-9 CrossRefGoogle Scholar
- Nissen S (2003) Implementation of a Fast Artificial Neural Network Library (FANN). Department of Computer Science University of Copenhagen (DIKU). Software available at http://leenissen.dk/fann/
- Sanchez VB, Redmann K, Wistuba J, Wübbeling F, Burger M, Oldenhof H, Wolkers WF, Kliesch S, Schlatt S, Mallidis C (2012) Oxidative DNA damage in human sperm can be detected by Raman microspectroscopy. Fertil Steril 98:1124–1129. https://doi.org/10.1016/j.fertnstert.2012.07.1059. CrossRefGoogle Scholar
- Satapornvanit K, Baird DJ, Little DC, Tayloe GJ (2004) Risks of pesticide use in aquatic ecosystems adjacent to mixed vegetable and monocrop fruit growing areas in Thailand. Australas J 10:85–95Google Scholar
- Schölkopf B, Smola A (2002) Learning with Kernels. MIT Press, CambridgeGoogle Scholar
- Seed J, Chapin RE, Clegg ED, Dostal LA, Foote RH, Hurtt ME, Klinefelter GR, Makris SL, Perreault SD, Schrader S, Seyler D, Sprando R, Treinen KA, Veeramachaneni DN, Wise LD (1996) Methods for assessing sperm motility, morphology, and counts in the rat, rabbit, and dog: a consensus report. ILSI risk science institute expert working group on sperm evaluation. Reprod Toxicol 10(3):237–244. https://doi.org/10.1016/0890-6238(96)00028-7 CrossRefGoogle Scholar
- Teng M, Qi S, Zhu W, Wang Y, Wang D, Dong K, Wang C (2018) Effects of the bioconcentration and parental transfer of environmentally relevant concentrations of difenoconazole on endocrine disruption in zebrafish (Danio rerio). Environ Pollut 233:208–217. https://doi.org/10.1016/j.envpol.2017.10.063. CrossRefGoogle Scholar
- Tomiazzi J, Judai MA, Nai GA, Pereira DR, Antunes PA, Favareto APA (2018) Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms. Environ Sci Pollut Res Int 25(2):1259–1269. https://doi.org/10.1007/s11356-017-0496-y CrossRefGoogle Scholar
- Tully DB, Bao W, Goetz AK, Blystone CR, Ren H, Schmid JE, Strader LF, Wood CR, Best DS, Narotsky MG, Wolf DC, Rockett JC, Dix DJ (2006) Gene expression profiling in liver and testis of rats to characterize the toxicity of triazole fungicides. Toxicol Appl Pharmacol 215:260–273. https://doi.org/10.1016/j.taap.2006.02.015. CrossRefGoogle Scholar