Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods

Autor(es)

Pereira, Viviane Ribas ^[1] ; Pereira, Danillo Roberto ^[1] ; de Melo Tavares Vieira, Katia Cristina ^[1] ; Ribas, Vitor Pereira ^[2] ; Leopoldo Constantino, Carlos Jose ^[3] ; Antunes, Patricia Alexandra ^[2] ; Alves Favareto, Ana Paula ^[1]

Afiliação do(s) autor(es)

^[1] Univ Western Sao Paulo UNOESTE, Grad Program Environm & Reg Dev, BR-19067175 Presidente Prudente, SP - Brazil

^[2] Univ Western Sao Paulo UNOESTE, Coll Sci Letters & Educ Presidente Prudente FACLE, BR-19067175 Presidente Prudente, SP - Brazil

^[3] Sao Paulo State Univ UNESP, Sch Technol & Appl Sci, Campus Presidente Prudente, Presidente Prudente, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: Environmental Science and Pollution Research; v. 26, n. 34, p. 35253-35265, DEC 2019.
• Citações Web of Science: 0

Resumo

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(-1) day (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. (AU)

• Processo FAPESP: 13/14262-7 - Filmes nanoestruturados de materiais de interesse biológico
• Beneficiário: Osvaldo Novais de Oliveira Junior
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 14/11410-8 - EMU concedido no processo 2013/14262-7: Streamline Renishaw
• Beneficiário: Osvaldo Novais de Oliveira Junior
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários