Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA)
Autor(a) principal: | |
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Data de Publicação: | 2024 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/273951 |
Resumo: | Paracoccidioidomycosis (PCM) is a systemic mycosis that is diagnosed by visualizing the fungus in clinical samples or by other methods, like serological techniques. However, all PCM diagnostic methods have limitations. The aim of this study was to develop a diagnostic tool for PCM based on Fourier transform infrared (FTIR) spectroscopy. A total of 224 serum samples were included: 132 from PCM patients and 92 constituting the control group (50 from healthy blood donors and 42 from patients with other systemic mycoses). Samples were analyzed by attenuated total reflection (ATR) and a t-test was performed to find differences in the spectra of the two groups. The wavenumbers that had p < 0.05 had their diagnostic potential evaluated using receiver operating characteristic (ROC) curves. The spectral region with the lowest p value was used for variable selection through principal component analysis (PCA). The selected variables were used in a linear discriminant analysis (LDA). In univariate analysis, the ROC curves with the best performance were obtained in the region 1551–1095 cm−1. The wavenumber that had the highest AUC value was 1264 cm−1, achieving a sensitivity of 97.73%, specificity of 76.01%, and accuracy of 94.22%. The total separation of groups was obtained in the PCA performed with a spectral range of 1551–1095 cm−1. LDA performed with the eight wavenumbers with the greatest weight from the group discrimination in the PCA obtained 100% accuracy. The methodology proposed here is simple, fast, and highly accurate, proving its potential to be applied in the diagnosis of PCM. The proposed method is more accurate than the currently known diagnostic methods, which is particularly relevant for a neglected tropical mycosis such as paracoccidioidomycosis. |
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Koehler, AlessandraScroferneker, Maria LuciaSouza, Nikolas Mateus Pereira deMoraes, Paulo Cezar dePereira, Beatriz Aparecida SoaresCavalcante, Ricardo de SouzaMendes, Rinaldo PôncioCorbellini, Valeriano Antonio2024-03-21T05:05:00Z20242309-608Xhttp://hdl.handle.net/10183/273951001197772Paracoccidioidomycosis (PCM) is a systemic mycosis that is diagnosed by visualizing the fungus in clinical samples or by other methods, like serological techniques. However, all PCM diagnostic methods have limitations. The aim of this study was to develop a diagnostic tool for PCM based on Fourier transform infrared (FTIR) spectroscopy. A total of 224 serum samples were included: 132 from PCM patients and 92 constituting the control group (50 from healthy blood donors and 42 from patients with other systemic mycoses). Samples were analyzed by attenuated total reflection (ATR) and a t-test was performed to find differences in the spectra of the two groups. The wavenumbers that had p < 0.05 had their diagnostic potential evaluated using receiver operating characteristic (ROC) curves. The spectral region with the lowest p value was used for variable selection through principal component analysis (PCA). The selected variables were used in a linear discriminant analysis (LDA). In univariate analysis, the ROC curves with the best performance were obtained in the region 1551–1095 cm−1. The wavenumber that had the highest AUC value was 1264 cm−1, achieving a sensitivity of 97.73%, specificity of 76.01%, and accuracy of 94.22%. The total separation of groups was obtained in the PCA performed with a spectral range of 1551–1095 cm−1. LDA performed with the eight wavenumbers with the greatest weight from the group discrimination in the PCA obtained 100% accuracy. The methodology proposed here is simple, fast, and highly accurate, proving its potential to be applied in the diagnosis of PCM. The proposed method is more accurate than the currently known diagnostic methods, which is particularly relevant for a neglected tropical mycosis such as paracoccidioidomycosis.application/pdfengJournal of fungi. Basel. Vol. 10, no. 2 (Feb. 2024), 147, 13 p.ParacoccidioidomicoseEspectroscopia de infravermelho com transformada de FourierMicosesParacoccidioidomycosisFourier transform infrared spectroscopyPhotodiagnosisROC curveLinear discriminant analysisSystemic mycosisRapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA)Estrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001197772.pdf.txt001197772.pdf.txtExtracted Texttext/plain39673http://www.lume.ufrgs.br/bitstream/10183/273951/2/001197772.pdf.txtb081fbf59af704fdc26e51789368d35eMD52ORIGINAL001197772.pdfTexto completo (inglês)application/pdf1868977http://www.lume.ufrgs.br/bitstream/10183/273951/1/001197772.pdf000348271e5480251b953d0a8730e726MD5110183/2739512024-03-22 05:03:56.384688oai:www.lume.ufrgs.br:10183/273951Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2024-03-22T08:03:56Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
title |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
spellingShingle |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) Koehler, Alessandra Paracoccidioidomicose Espectroscopia de infravermelho com transformada de Fourier Micoses Paracoccidioidomycosis Fourier transform infrared spectroscopy Photodiagnosis ROC curve Linear discriminant analysis Systemic mycosis |
title_short |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
title_full |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
title_fullStr |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
title_full_unstemmed |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
title_sort |
Rapid classification of serum from patients with Paracoccidioidomycosis using infrared spectroscopy, univariate statistics, and linear discriminant analysis (LDA) |
author |
Koehler, Alessandra |
author_facet |
Koehler, Alessandra Scroferneker, Maria Lucia Souza, Nikolas Mateus Pereira de Moraes, Paulo Cezar de Pereira, Beatriz Aparecida Soares Cavalcante, Ricardo de Souza Mendes, Rinaldo Pôncio Corbellini, Valeriano Antonio |
author_role |
author |
author2 |
Scroferneker, Maria Lucia Souza, Nikolas Mateus Pereira de Moraes, Paulo Cezar de Pereira, Beatriz Aparecida Soares Cavalcante, Ricardo de Souza Mendes, Rinaldo Pôncio Corbellini, Valeriano Antonio |
author2_role |
author author author author author author author |
dc.contributor.author.fl_str_mv |
Koehler, Alessandra Scroferneker, Maria Lucia Souza, Nikolas Mateus Pereira de Moraes, Paulo Cezar de Pereira, Beatriz Aparecida Soares Cavalcante, Ricardo de Souza Mendes, Rinaldo Pôncio Corbellini, Valeriano Antonio |
dc.subject.por.fl_str_mv |
Paracoccidioidomicose Espectroscopia de infravermelho com transformada de Fourier Micoses |
topic |
Paracoccidioidomicose Espectroscopia de infravermelho com transformada de Fourier Micoses Paracoccidioidomycosis Fourier transform infrared spectroscopy Photodiagnosis ROC curve Linear discriminant analysis Systemic mycosis |
dc.subject.eng.fl_str_mv |
Paracoccidioidomycosis Fourier transform infrared spectroscopy Photodiagnosis ROC curve Linear discriminant analysis Systemic mycosis |
description |
Paracoccidioidomycosis (PCM) is a systemic mycosis that is diagnosed by visualizing the fungus in clinical samples or by other methods, like serological techniques. However, all PCM diagnostic methods have limitations. The aim of this study was to develop a diagnostic tool for PCM based on Fourier transform infrared (FTIR) spectroscopy. A total of 224 serum samples were included: 132 from PCM patients and 92 constituting the control group (50 from healthy blood donors and 42 from patients with other systemic mycoses). Samples were analyzed by attenuated total reflection (ATR) and a t-test was performed to find differences in the spectra of the two groups. The wavenumbers that had p < 0.05 had their diagnostic potential evaluated using receiver operating characteristic (ROC) curves. The spectral region with the lowest p value was used for variable selection through principal component analysis (PCA). The selected variables were used in a linear discriminant analysis (LDA). In univariate analysis, the ROC curves with the best performance were obtained in the region 1551–1095 cm−1. The wavenumber that had the highest AUC value was 1264 cm−1, achieving a sensitivity of 97.73%, specificity of 76.01%, and accuracy of 94.22%. The total separation of groups was obtained in the PCA performed with a spectral range of 1551–1095 cm−1. LDA performed with the eight wavenumbers with the greatest weight from the group discrimination in the PCA obtained 100% accuracy. The methodology proposed here is simple, fast, and highly accurate, proving its potential to be applied in the diagnosis of PCM. The proposed method is more accurate than the currently known diagnostic methods, which is particularly relevant for a neglected tropical mycosis such as paracoccidioidomycosis. |
publishDate |
2024 |
dc.date.accessioned.fl_str_mv |
2024-03-21T05:05:00Z |
dc.date.issued.fl_str_mv |
2024 |
dc.type.driver.fl_str_mv |
Estrangeiro info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10183/273951 |
dc.identifier.issn.pt_BR.fl_str_mv |
2309-608X |
dc.identifier.nrb.pt_BR.fl_str_mv |
001197772 |
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2309-608X 001197772 |
url |
http://hdl.handle.net/10183/273951 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Journal of fungi. Basel. Vol. 10, no. 2 (Feb. 2024), 147, 13 p. |
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info:eu-repo/semantics/openAccess |
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openAccess |
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