Elina A. Tcherniavskaia

Optical micro resonance based sensor schemes for detection and identification of nano particles and biological agents in situ

A novel emerging technique for the label-free analysis of nano particles including biomolecules using optical micro cavity resonance is being developed. Various schemes based on a mechanically fixed microspheres as well as microspheres melted by laser on the tip of a standard single mode fiber have been investigated to make further development for microbial application. Water solutions of ethanol, HCl, glucose, vitamin C and biotin have been used to test refractive index changes by monitoring the magnitude of the whispering gallery modes spectral shift. Particular efforts were made for effective fixing of the micro spheres in the water flow, an optimal geometry for micro resonance observation and material of microsphere the most appropriate for microbial application. Optical resonance in free micro spheres from PMMA fixed in micro channels produced by photolithography has been observed under the laser power of less then 1 microwatt. Resonance shifts of C reactive protein water solutions as well as albumin solutions in pure water and with HCl modelling blood have been investigated. Introducing controlled amount of glass gel nano particles into sensor microsphere surrounding were accompanied by both correlative resonance shift (400 nm in diameter) and total reconstruct of resonance spectra (57 nm in diameter). Developed schemes have been demonstrated to be a promising technology platform for sensitive, lab-on-chip type sensor 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.

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

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.

Integrated fiber optical and thermal sensor for noninvasive monitoring of blood and human tissue

A novel concept of noninvasive monitoring of human tissue and blood based on optical diffuse reflective spectroscopy combined with metabolic heat measurements has been under development. A compact integrated fiber optical and thermal sensor has been developed. The idea of the method was to evaluate by optical spectroscopy haemoglobin and derivative concentrations and supplement with data associated with the oxidative metabolism of glucose. Body heat generated by glucose oxidation is based on the balance of capillary glucose and oxygen supply to the cells. The variation in glucose concentration is followed also by a difference from a distance (or depth) of scattered through the body radiation. So, blood glucose can be estimated by measuring the body heat and the oxygen supply. The sensor pickup contains of halogen lamp and LEDs combined with fiber optical bundle to deliver optical radiation inside and through the patient body, optical and thermal detectors. Fiber optical probe allows diffuse scattering measurement down to a depth of 2.5 mm in the skin including vascular system, which contributes to the control of the body temperature. The sensor pickup measures thermal generation, heat balance, blood flow rate, haemoglobin and derivative concentrations, environmental conditions. Multivariate statistical analysis was applied to convert various signals from the sensor pickup into physicochemical variables. By comparing the values from the noninvasive measurement with the venous plasma result, analytical functions for patient were obtained. Cluster analysis of patient groups was used to simplify a calibration procedure. Clinical testing of developed sensor is being performed.

Noninvasive Glucose Monitoring by Optical Reflective and Thermal Emission Spectroscopic Measurements

Noninvasive method for blood glucose monitoring in cutaneous tissue based on reflective spectrometry combined with a thermal emission spectroscopy has been developed. Regression analysis, neural network algorithms and cluster analysis are used for data processing.

Simultaneous real-time application and direct comparison of optical resonance sensing and fluorescence tagging techniques for biochemical component detection

New approach to perform a real-time biochemical component detection based on simultaneous analysis of spectral changes of whispering gallery modes (WGM) and fluorescence markers used for biochemical components tagging. Microcavity array sensor was chosen as detection unit. Experimental data on detection of bovine serum albumin protein solution using both techniques simultaneously is represented.

Quantification of whispering gallery mode spectrum variability in application to sensing nanobiophotonics

Abstract. An approach for the automated whispering gallery mode (WGM) signal decomposition and its parameter estimation is discussed. The algorithm is based on the peak picking and can be applied for the preprocessing of the raw signal acquired from the multiplied WGM-based biosensing chips. Quantitative estimations representing physically meaningful parameters of the external disturbing factors on the WGM spectral shape are the output values. Derived parameters can be directly applied to the further deep qualitative and quantitative interpretations of the sensed disturbing factors. The algorithm is tested on both simulated and experimental data taken from the bovine serum albumin biosensing task. The proposed solution is expected to be a useful contribution to the preprocessing phase of the complete data analysis engine and is expected to push the WGM technology toward the real-live sensing nanobiophotonics.

Plasmonic improvement of microcavity biomedical sensor spectroscopic characteristics

New opportunity to improve a sensetivity of a label-free biomolecule detection in sensing systems based on microcavity evanescent wave optical sensors has been recently found and is being under intensive development. Novel technique based on combination of optical resonance on microring structures with plasmon resonance. Recently developed tools based on neural network data processing can realize real-time identification of biological agents. So combining advantages of plasmon enhancing optical microcavity resonance with identification tools can give a new platform for ulta sensitive label-free biomedical sensor. Our developed technique used standard glass and polymer microspheres as sensetive elements. They are fixed in the solution flow by adhesive layer on the surface being in the field of evanescence wave. Sensitive layer have been treated by gold nanoparticel (GN) solution. Another technique used thin film gold layers deposited on the substrate below adhesive. The light from a tuneable diode laser is coupled into the microsphere through a prism and was sharply focussed on the single microsphere. Images were recorded by CMOS camera. Normalized by free spectral range resonance shift of whispering gallery mode (WGM) and a relative efficiency of their excitation were used as input data for biomolecule classification. Both biomolecules and NP injection was obtained caused WGM spectra modification. But after NP treatment spectral shift and intensity of WGM resonances in biomolecule solutions increased. WGM resonances in microspheres fixed on substrate with gold layer with optimized layer thickness in biomolecule solutions also had higher intensity and spectra modification then without gold layer.

Biochemical component identification by plasmonic improved whispering gallery mode optical resonance based sensor

Experimental data on detection and identification of variety of biochemical agents, such as proteins, microelements, antibiotic of different generation etc. in both single and multi component solutions under varied in wide range concentration analyzed on the light scattering parameters of whispering gallery mode optical resonance based sensor are represented. Multiplexing on parameters and components has been realized using developed fluidic sensor cell with fixed in adhesive layer dielectric microspheres and data processing. Biochemical component identification has been performed by developed network analysis techniques. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis. Novel technique based on optical resonance on microring structures, plasmon resonance and identification tools has been developed. To improve a sensitivity of microring structures microspheres fixed by adhesive had been treated previously by gold nanoparticle solution. Another technique used thin film gold layers deposited on the substrate below adhesive. Both biomolecule and nanoparticle injections caused considerable changes of optical resonance spectra. Plasmonic gold layers under optimized thickness also improve parameters of optical resonance spectra. Biochemical component identification has been also performed by developed network analysis techniques both for single and for multi component solution. So advantages of plasmon enhancing optical microcavity resonance with multiparameter identification tools is used for development of a new platform for ultra sensitive label-free biomedical sensor.

Biochemical component identification by light scattering techniques in whispering gallery mode optical resonance based sensor

Experimental data on detection and identification of variety of biochemical agents, such as proteins (albumin, interferon, C reactive protein), microelements (Na+, Ca+), antibiotic of different generations, in both single and multi component solutions under varied in wide range concentration are represented. Analysis has been performed on the light scattering parameters of whispering gallery mode (WGM) optical resonance based sensor with dielectric microspheres from glass and PMMA as sensitive elements fixed by spin - coating techniques in adhesive layer on the surface of substrate or directly on the coupling element. Sensitive layer was integrated into developed fluidic cell with a digital syringe. Light from tuneable laser strict focusing on and scattered by the single microsphere was detected by a CMOS camera. The image was filtered for noise reduction and integrated on two coordinates for evaluation of integrated energy of a measured signal. As the entrance data following signal parameters were used: relative (to a free spectral range) spectral shift of frequency of WGM optical resonance in microsphere and relative efficiency of WGM excitation obtained within a free spectral range which depended on both type and concentration of investigated agents. Multiplexing on parameters and components has been realized using spatial and spectral parameters of scattered by microsphere light with developed data processing. Biochemical component classification and identification of agents under investigation has been performed by network analysis techniques based on probabilistic network and multilayer perceptron. Developed approach is demonstrated to be applicable both for single agent and for multi component biochemical analysis.

Drag detection and identification by whispering gallery mode optical resonance based sensor

Experimental data on optical resonance spectra of whispering gallery modes of dielectric microspheres in antibiotic solutions under varied in wide range concentration are represented. Optical resonance was demonstrated could be detected at a laser power of less than 1 microwatt. Several antibiotics of different generations: Amoxicillin, Azithromycin, Cephazolin, Chloramphenicol, Levofloxacin, Lincomicin Benzylpenicillin, Riphampicon both in deionized water and physiological solution had been used for measurements. Both spectral shift and the structure of resonance spectra were of specific interest in this investigation. Drag identification has been performed by developed multilayer perceptron network. The network topology was designed included: a number of the hidden layers of multilayered perceptron, a number of neurons in each of layers, a method of training of a neural network, activation functions of layers, type and size of a deviation of the received values from required values. For a network training the method of the back propagation error in various modifications has been used. Input vectors correspond to 6 classes of biological substances under investigation. The result of classification was considered as positive when each of the region, representing a certain substance in a space: relative spectral shift of an optical resonance maxima - relative efficiency of excitation of WGM, was singly connected. It was demonstrated that the approach described in the paper can be a promising platform for the development of sensitive, lab-on-chip type sensors that can be used as an express diagnostic tools for different drugs and instrumentation for proteomics, genomics, drug discovery, and membrane studies.