Identification of Water-Soluble Polymers through Machine Learning of Fluorescence Signals from Multiple Peptide Sensors.

Journal: ACS applied bio materials
PMID: 37889623

Abstract

Recently, there has been growing concern about the discharge of water-soluble polymers (especially synthetic polymers) into the environment. Therefore, the identification of water-soluble polymers in water samples is becoming increasingly crucial. In this study, a chemical tongue system to simply and precisely identify water-soluble polymers using multiple fluorescently responsive peptide sensors was demonstrated. Fluorescence spectra obtained from the mixture of each peptide sensor and water-soluble polymer were changed depending on the combination of the polymer species and peptide sensors. Water-soluble polymers were successfully identified through the supervised or unsupervised machine learning of multidimensional fluorescence signals from the peptide sensors.

Authors

  • Shion Hasegawa
    Department of Chemical Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, 2-12-1-H121 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
  • Toshiki Sawada
    Department of Chemical Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, 2-12-1-H121 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.
  • Takeshi Serizawa
    Department of Chemical Science and Engineering, School of Materials and Chemical Technology, Tokyo Institute of Technology, 2-12-1-H121 Ookayama, Meguro-ku, Tokyo 152-8550, Japan.

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