Biosecurity and biosafety are key concerns of modern society. Although nanomaterials are improving the capacities of point detectors, standoff detection still appears to be an open issue. Laser-induced fluorescence of biological agents (BAs) has proved to be one of the most promising optical techniques to achieve early standoff detection, but its strengths and weaknesses are still to be fully investigated. In particular, different BAs tend to have similar fluorescence spectra due to the ubiquity of biological endogenous fluorophores producing a signal in the UV range, making data analysis extremely challenging. The Universal Multi Event Locator (UMEL), a general method based on support vector regression, is commonly used to identify characteristic structures in arrays of data. In the first part of this work, we investigate fluorescence emission spectra of different simulants of BAs and apply UMEL for their automatic classification. In the second part of this work, we elaborate a strategy for the application of UMEL to the discrimination of different BAs’ simulants spectra. Through this strategy, it has been possible to discriminate between these BAs' simulants despite the high similarity of their fluorescence spectra. These preliminary results support the use of SVR methods to classify BAs’ spectral signatures

Carestia, M., Pizzoferrato, R., Gelfusa, M., Cenciarelli, O., Ludovici, G., Gabriele, J., et al. (2015). Development of a rapid method for the automatic classification of biological agents' fluorescence spectral signatures. OPTICAL ENGINEERING, 54(11), 114105 [10.1117/1.OE.54.11.114105].

Development of a rapid method for the automatic classification of biological agents' fluorescence spectral signatures

PIZZOFERRATO, ROBERTO;GELFUSA, MICHELA;CENCIARELLI, ORLANDO;MALIZIA, ANDREA;GAUDIO, PASQUALINO
2015

Abstract

Biosecurity and biosafety are key concerns of modern society. Although nanomaterials are improving the capacities of point detectors, standoff detection still appears to be an open issue. Laser-induced fluorescence of biological agents (BAs) has proved to be one of the most promising optical techniques to achieve early standoff detection, but its strengths and weaknesses are still to be fully investigated. In particular, different BAs tend to have similar fluorescence spectra due to the ubiquity of biological endogenous fluorophores producing a signal in the UV range, making data analysis extremely challenging. The Universal Multi Event Locator (UMEL), a general method based on support vector regression, is commonly used to identify characteristic structures in arrays of data. In the first part of this work, we investigate fluorescence emission spectra of different simulants of BAs and apply UMEL for their automatic classification. In the second part of this work, we elaborate a strategy for the application of UMEL to the discrimination of different BAs’ simulants spectra. Through this strategy, it has been possible to discriminate between these BAs' simulants despite the high similarity of their fluorescence spectra. These preliminary results support the use of SVR methods to classify BAs’ spectral signatures
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore FIS/01 - Fisica Sperimentale
Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)
English
Carestia, M., Pizzoferrato, R., Gelfusa, M., Cenciarelli, O., Ludovici, G., Gabriele, J., et al. (2015). Development of a rapid method for the automatic classification of biological agents' fluorescence spectral signatures. OPTICAL ENGINEERING, 54(11), 114105 [10.1117/1.OE.54.11.114105].
Carestia, M; Pizzoferrato, R; Gelfusa, M; Cenciarelli, O; Ludovici, G; Gabriele, J; Malizia, A; Murari, A; Vega, J; Gaudio, P
Articolo su rivista
File in questo prodotto:
File Dimensione Formato  
2015 OptEng-150911P_online.pdf

accesso solo dalla rete interna

Descrizione: Articolo principale
Licenza: Copyright dell'editore
Dimensione 2.07 MB
Formato Adobe PDF
2.07 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2108/127791
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 5
social impact