Oxytocin imprinted polymer based surface plasmon resonance sensor and its application to milk sample


Yola M. L. , Atar N., Erdem A.

SENSORS AND ACTUATORS B-CHEMICAL, vol.221, pp.842-848, 2015 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 221
  • Publication Date: 2015
  • Doi Number: 10.1016/j.snb.2015.07.004
  • Title of Journal : SENSORS AND ACTUATORS B-CHEMICAL
  • Page Numbers: pp.842-848
  • Keywords: Oxytocin, Surface plasmon resonance, Molecular imprinting, Validation, GRAPHENE-MODIFIED ELECTRODES, QUARTZ-CRYSTAL MICROBALANCE, RED YEAST RICE, CAPILLARY-ELECTROPHORESIS, CARBON NANOTUBES, SENSITIVE DETERMINATION, SELECTIVE DETERMINATION, GRAPHITE ELECTRODE, WASTE-WATER, NANOSENSOR

Abstract

In present study, a novel and sensitive molecular imprinted surface plasmon resonance sensor was prepared by fabricating a self-assembling monolayer formation of allylmercaptane on gold chip surface for selective determination of oxytocin in milk. Then, oxytocin-imprinted poly (2-hydroxyethyl methacrylate-methacryloylamidoglutamic acid) nanofilm was performed onto the allyl mercaptane modified chip. The unmodified and modified surfaces were characterized by using Fourier transform infrared spectroscopy, atomic force microscopy, ellipsometry, scanning electron microscope and contact angle measurements. The imprinted surface plasmon resonance sensor was found to be sensitive, selective, linear and proper. The linearity range in the concentration range of oxytocin was obtained as 0.01-1.0 ng/mL and the detection limit of the prepared sensor was calculated as 0.0030 ng/mL. The molecular imprinted sensor based on surface plasmon resonance was also applied successfully to milk sample for the determination of oxytocin. Furthermore, the repeatability of the prepared molecular imprinted sensor was studied. The good repeatability of the prepared oxytocin-imprinted surface plasmon resonance sensors makes them attractive in sensor studies. In addition, isotherm models were applied to data to explain adsorption process. (C) 2015 Elsevier B.V. All rights reserved.