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Discrimination of phthalate species using a simple phage-based colorimetric sensor in conjunction with hierarchical support vector machine.
Seol, Daun; Jang, Daeil; Oh, Jin-Woo; Cha, Kyungjoon; Chung, Hoeil.
Afiliação
  • Seol D; Department of Chemistry and Research Institute for Convergence of Basic Science, Hanyang University, Seoul 04763, Republic of Korea.
  • Jang D; Department of Mathematics, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea.
  • Oh JW; BK21 Plus Division of Nano Convergence Technology, Pusan National University, Busan 46241, Republic of Korea; Department of Nano Fusion Technology, Pusan National University, Busan 46241, Republic of Korea; Department of Nanoenergy Engineering, Pusan National University, Busan 46241, Republic of Kor
  • Cha K; Department of Mathematics, College of Natural Sciences, Hanyang University, Seoul 04763, Republic of Korea. Electronic address: kjcha@hanyang.ac.kr.
  • Chung H; Department of Chemistry and Research Institute for Convergence of Basic Science, Hanyang University, Seoul 04763, Republic of Korea. Electronic address: hoeil@hanyang.ac.kr.
Environ Res ; 170: 238-242, 2019 03.
Article em En | MEDLINE | ID: mdl-30594695
ABSTRACT
Here, the analytical potential of an M13 bacteriophage-based color sensor for discrimination of 4 phthalates with similar molecular structures (bis-(2-ethylhexyl)-phthalate (BEHP), dibutyl phthalate (DBP), diethyl phthalate (DEP), and benzyl-butyl-phthalate (BBP)) was investigated. The pattern and magnitude of the RGB color changes were different depending on the functional groups present in the phthalate structures. For example, BEHP possessing a long alkyl chain resulted in a minute color change, while the variation of color was substantially large when BBP containing an additional benzene ring was measured. Since a tryptophan-histidine-tryptophan residue possessing indole and imidazole was present on the self-assembled phages, the π-π interaction of benzene in BBP with the sensor surface produced a considerably greater color change. To evaluate the multi-modally varying color signals due to diverse interactions of the phthalates with the sensor and to discriminate them, support vector machine (SVM), which can construct a boundary hyperplane among complexly scattered sample groups, was used. In addition, hierarchical SVM (H-SVM) was adopted to deal with multi-class discrimination. The use of H-SVM improved the discrimination accuracy up to 90.1%, compared to 87.1% using SVM. The demonstrated color sensor is versatile and can be potentially adopted as an on-site screening tool. Strategies to improve the accuracy further for real applications are also discussed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ácidos Ftálicos / Bacteriófagos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ácidos Ftálicos / Bacteriófagos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article