Classification of the micro and nanoparticles and biological agents by neural network analysis of the parameters of optical resonance of whispering gallery mode in dielectric microspheres

Vladimir A. Saetchnikov; Elina A. Tcherniavskaia; Gustav Schweiger; Andreas Ostendorf

doi:10.1117/12.889574

14 June 2011 Classification of the micro and nanoparticles and biological agents by neural network analysis of the parameters of optical resonance of whispering gallery mode in dielectric microspheres

Vladimir A. Saetchnikov, Elina A. Tcherniavskaia, Gustav Schweiger, Andreas Ostendorf

Author Affiliations +

Proceedings Volume 8090, Novel Biophotonic Techniques and Applications; 80900R (2011) https://doi.org/10.1117/12.889574
Event: European Conferences on Biomedical Optics, 2011, Munich, Germany

Abstract

A novel technique for the label-free analysis of micro and nanoparticles including biomolecules using optical micro cavity resonance of whispering-gallery-type modes is being developed. Various schemes of the method using both standard and specially produced microspheres have been investigated to make further development for microbial application. It was demonstrated that optical resonance under optimal geometry could be detected under the laser power of less 1 microwatt. The sensitivity of developed schemes has been tested by monitoring the spectral shift of the whispering gallery modes. Water solutions of ethanol, ascorbic acid, blood phantoms including albumin and HCl, glucose, biotin, biomarker like C reactive protein so as bacteria and virus phantoms (gels of silica micro and nanoparticles) have been used. Structure of resonance spectra of the solutions was a specific subject of investigation. Probabilistic neural network classifier for biological agents and micro/nano particles classification has been developed. Several parameters of resonance spectra as spectral shift, broadening, diffuseness and others have been used as input parameters to develop a network classifier for micro and nanoparticles and biological agents in solution. Classification probability of approximately 98% for probes under investigation have been achieved. Developed approach have been demonstrated to be a promising technology platform for sensitive, lab-on-chip type sensor which can be used for development of diagnostic tools for different biological molecules, e.g. proteins, oligonucleotides, oligosaccharides, lipids, small molecules, viral particles, cells as well as in different experimental contexts e.g. proteomics, genomics, drug discovery, and membrane studies.

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Vladimir A. Saetchnikov, Elina A. Tcherniavskaia, Gustav Schweiger, and Andreas Ostendorf "Classification of the micro and nanoparticles and biological agents by neural network analysis of the parameters of optical resonance of whispering gallery mode in dielectric microspheres", Proc. SPIE 8090, Novel Biophotonic Techniques and Applications, 80900R (14 June 2011); https://doi.org/10.1117/12.889574

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