USA As Represented by Secretary of the Navy

Jeff M Byers

Marc P Raphael

Joseph A Christodoulides

James B Delehanty

Brian H Houston

Peter Herdic

Alain Berdoz

Robert M Baden

Phillip A Frank

Josef A Christodoulides

Methods and systems for determining extracellular concentration data of an analyte are disclosed. A method for determining extracellular concentration data of an analyte includes receiving sensor data from one or more arrays of functionalized plasmonic nanostructures on a localized surface plasmon resonance imaging chip in contact with a fluid containing at least one living cell for a plurality of times, determining intensity data for the one or more arrays, determining fractional occupancy based on the intensity data, and determining extracellular concentration data based on the fractional occupancy data. A system for determining extracellular concentration data of an analyte includes a LSPRi chip, a sensor component, an intensity component, a fractional occupancy component, a concentration component, and a processor to implement the components.

Determining extracellular analyte concentration with nanoplasmonic sensors

A chip for localized surface plasmon resonance (LSPR) biosensing and imaging having a glass coverslip compatible for use in a standard microscope and at least one array of functionalized plasmonic nanostructures patterned onto the glass coverslip with electron beam nanolithography. The nanostructures can be regenerated allowing the chip to be used multiple times. Also disclosed is a method for determining the fractional occupancy values for surface-bound receptors as a function of time for LSPR biosensing from the spectroscopic response of the array and modeling the photon count in each spectrometer channel, allowing for a functional relationship to be determined between the acquired spectrum and the fractional occupancy of binding sites on the array. Additionally disclosed is a method for the spatiotemporal mapping of receptor-ligand binding kinetics in LSPR imaging using the chip and projecting a magnified image of the array to a CCD camera and monitoring the binding kinetics of the array.

Light microscopy chips and data analysis methodology for quantitative localzied surface plasmon resonance (LSPR) biosensing and imaging

A label-free method for the spatio-temporal mapping of protein secretions from individual cells in real time by using a chip for localized surface plasmon resonance (LSPR) imaging. The chip is a glass coverslip compatible for use in a standard microscope having at least one array of functionalized plasmonic nanostructures patterned onto it. After placing a cell on the chip, the secretions from the cell are spatially and temporally mapped using LSPR imaging. Transmitted light imaging and/or fluorescence imaging may be done simultaneously with the LSPR imaging.

Nanoplasmonic imaging technique for the spatio-temporal mapping of single cell secretions in real time

A method for calibrating multiple nanostructures in parallel for quantitative biosensing using a chip for localized surface plasmon resonance (LSPR) biosensing and imaging. The chip is a glass coverslip compatible for use in a standard microscope with at least one array of functionalized plasmonic nanostructures patterned onto it using electron beam nanolithography. The chip is used to collect CCD-based LSPR imagery data of each individual nanostructure and LSPR spectral data of the array. The spectral data is used to determine the fractional occupancy of the array. The imagery data is modeled as a function of fractional occupancy to determine the fractional occupancy of each individual nanostructure.

Calibrating single plasmonic nanostructures for quantitative biosening

Light microscopy chips and data analysis methodology for quantitative localized surface plasmon resonance (LSPR) biosensing and imaging

Nanosplasmonic imaging technique for the spatio-temporal mapping of single cell secretions in real time

A method and system for detecting and classifying intruders is provided. A noise threshold can be determined and set based on background noise. A seismic sensor can be configured to receive a plurality of seismic data signals. A microcontroller can be configured to count the number of times the noise threshold is exceeded over a defined time interval by the plurality of seismic data signals, and then detect and classify the presence of an intruder based on the count. Additionally, an amplitude evaluation module can be configured to determine a signal amplitude for the seismic data signals associated with the detected intruder and compare the detected intruder signal amplitude to known signal amplitudes in order to determine a sub-type of the intruder. Finally, a transmission source can be configured to transmit intruder detection and classification information to a remote location.

Growing community of inventors

Fairfax Station, VA, United States of America

Jeff M Byers