Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
DOI: | 10.1007/s11356-019-06407-0 |
Texto Completo: | http://dx.doi.org/10.1007/s11356-019-06407-0 http://hdl.handle.net/11449/199641 |
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−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. |
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Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methodsArtificial intelligenceFungicideRaman spectroscopyRatReproductionSpermatozoaDifenoconazole 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.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Graduate Program in Environment and Regional Development University of Western São Paulo – UNOESTECollege of Science Letters and Education from Presidente Prudente – FACLEPP University of Western São Paulo – UNOESTESchool of Technology and Applied Sciences São Paulo State University (UNESP) Campus Presidente PrudenteSchool of Technology and Applied Sciences São Paulo State University (UNESP) Campus Presidente PrudenteFAPESP: 2013/14262-7FAPESP: 2014/11410-8University of Western São Paulo – UNOESTEUniversidade Estadual Paulista (Unesp)Pereira, Viviane RibasPereira, Danillo Robertode Melo Tavares Vieira, Kátia CristinaRibas, Vitor PereiraConstantino, Carlos José Leopoldo [UNESP]Antunes, Patrícia AlexandraFavareto, Ana Paula Alves2020-12-12T01:45:24Z2020-12-12T01:45:24Z2019-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article35253-35265http://dx.doi.org/10.1007/s11356-019-06407-0Environmental Science and Pollution Research, v. 26, n. 34, p. 35253-35265, 2019.1614-74990944-1344http://hdl.handle.net/11449/19964110.1007/s11356-019-06407-02-s2.0-85074833298Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnvironmental Science and Pollution Researchinfo:eu-repo/semantics/openAccess2024-06-18T18:18:15Zoai:repositorio.unesp.br:11449/199641Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:32:10.630929Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
title |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
spellingShingle |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods Pereira, Viviane Ribas Artificial intelligence Fungicide Raman spectroscopy Rat Reproduction Spermatozoa Pereira, Viviane Ribas Artificial intelligence Fungicide Raman spectroscopy Rat Reproduction Spermatozoa |
title_short |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
title_full |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
title_fullStr |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
title_full_unstemmed |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
title_sort |
Sperm quality of rats exposed to difenoconazole using classical parameters and surface-enhanced Raman scattering: classification performance by machine learning methods |
author |
Pereira, Viviane Ribas |
author_facet |
Pereira, Viviane Ribas Pereira, Viviane Ribas Pereira, Danillo Roberto de Melo Tavares Vieira, Kátia Cristina Ribas, Vitor Pereira Constantino, Carlos José Leopoldo [UNESP] Antunes, Patrícia Alexandra Favareto, Ana Paula Alves Pereira, Danillo Roberto de Melo Tavares Vieira, Kátia Cristina Ribas, Vitor Pereira Constantino, Carlos José Leopoldo [UNESP] Antunes, Patrícia Alexandra Favareto, Ana Paula Alves |
author_role |
author |
author2 |
Pereira, Danillo Roberto de Melo Tavares Vieira, Kátia Cristina Ribas, Vitor Pereira Constantino, Carlos José Leopoldo [UNESP] Antunes, Patrícia Alexandra Favareto, Ana Paula Alves |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
University of Western São Paulo – UNOESTE Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Pereira, Viviane Ribas Pereira, Danillo Roberto de Melo Tavares Vieira, Kátia Cristina Ribas, Vitor Pereira Constantino, Carlos José Leopoldo [UNESP] Antunes, Patrícia Alexandra Favareto, Ana Paula Alves |
dc.subject.por.fl_str_mv |
Artificial intelligence Fungicide Raman spectroscopy Rat Reproduction Spermatozoa |
topic |
Artificial intelligence Fungicide Raman spectroscopy Rat Reproduction Spermatozoa |
description |
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. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 2020-12-12T01:45:24Z 2020-12-12T01:45:24Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1007/s11356-019-06407-0 Environmental Science and Pollution Research, v. 26, n. 34, p. 35253-35265, 2019. 1614-7499 0944-1344 http://hdl.handle.net/11449/199641 10.1007/s11356-019-06407-0 2-s2.0-85074833298 |
url |
http://dx.doi.org/10.1007/s11356-019-06407-0 http://hdl.handle.net/11449/199641 |
identifier_str_mv |
Environmental Science and Pollution Research, v. 26, n. 34, p. 35253-35265, 2019. 1614-7499 0944-1344 10.1007/s11356-019-06407-0 2-s2.0-85074833298 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Environmental Science and Pollution Research |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
35253-35265 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1822182306817769472 |
dc.identifier.doi.none.fl_str_mv |
10.1007/s11356-019-06407-0 |