A novel microfluidic/SERS platform has been developed for real time sensing of 2,4-DNT. The fundamental
research is being conducted at UCSB, commercialized by SpectraFluidics, and validated at ECBC. The system
leverages phenomena at multiple length scales, ranging from tens of micrometers to several nanometers. The key
enabling technology is a newly developed invention termed Free-Surface Fluidics (FSF), where one or more fluidic
surfaces are confined by surface tension forces, and exposed to the surrounding atmosphere. The free-surface fluidic
architecture is combined with surface-enhanced Raman spectroscopy (SERS) for detection of 2,4-DNT. Once 2,4-DNT
analyte molecules are absorbed into the flow, they can interact with gold or silver colloidal particles. This architecture
allows for analysis and deterministic control of SERS 'hot spot' aggregation, which can increase Raman scattering signal
strength by up to 10 orders in magnitude. We have successfully measured DNT vapor at concentrations as low as ~1
ppb. This sensitivity value is confirmed by orthogonal measurements using GC-mass spectroscopy at ECBC.
Fluorescent microarrays have the ability to detect and monitor multiple analytes simultaneously and noninvasively,
following initial placement. This versatility is advantageous for several biological applications including drug
discovery, biohazard detection, transplant organ preservation and cell culture monitoring. In this work, poly(ethylene
glycol) hydrogel microarrays are described that can be used to measure multiple analytes, including H+ and dissolved
oxygen. The array elements are created by filling micro-channels with a hydrogel precursor solution containing analyte
specific fluorescent sensors. A photomask is used to create the microarray through UV polymerization of the PEG
precursor solution. A compact imaging system composed of a CCD camera, high powered LED, and two optical filters
is used to measure the change in fluorescence emission corresponding to analyte concentration. The proposed system
was tested in aqueous solution by altering relevant analyte concentrations across their biological ranges.
A combined dissolved oxygen and pH sensitive poly(ethylene glycol) hydrogel microarray was fabricated for use in monitoring cell culture media. The sensor was prepared by filling micro-channels with a hydrogel precursor solution containing pH or oxygen sensitive fluorophores. This solution was then cured by passing UV light through a mask placed to the channels, creating array with 100 μm elements. An imaging system with a monochrome CCD camera and
appropriate interference filters was used to capture the fluorescence image induced by excitation of microstructure in transmission mode. The sensor performance was characterized in buffer solution (PBS) and cell culture media (MEM) across the biological range of pH (6-8) and dissolved oxygen (3-21%).
This study reports on current work involving the use of Surface Enhanced Raman Spectroscopy (SERS) for the intracellular detection of cell constituents in mouse fibroblast cells using gold nanoshells. Gold nanoshells were acquired from Nanospectra Biosciences that are based on a silica dielectric core and an outer gold shell layer. They
have the unique property of a tunable surface plasmon resonance wavelength from the visible through the near infrared which allows control of the electromagnetic field strength on its surface. Hence gold nanoshells can serve as SERS substrates with plasmonic properties that are not aggregation dependent and thus can be expected to overcome the reproducibility problem that is generally associated with aggregation based colloidal metal nanoparticles. These results represent the first steps in the development of a nanoshell-based SERS probe to detect cell organelles and/or intracellular biochemicals with the goal of ultimately improving the ability to monitor intracellular biological processes in real time.
A sensor has been developed that uses multiple source excitation to measure blood perfusion in transplanted organs. To better isolate the signal of interest, wavelet decomposition analysis was used and compared to Fast Fourier Transform analysis. Data was collected in vitro using an adjustable peristaltic perfusion system and compared to simulated data created using low frequency sine waves. Standard FFT analysis and wavelet decomposition, using the symlet-4 wavelet mother function, was performed on both sets of data. The results showed that wavelet analysis was more suitable than FFT to extract the semi-periodic perfusion signal. These results indicate the potential of wavelet analysis for blood perfusion monitoring.
KEYWORDS: Blood, Sensors, Data modeling, Monte Carlo methods, Tissues, Infrared radiation, In vitro testing, Liver, Optical diagnostics, Optical sensing
A Multi-Layer Monte Carlo (MLMC) model was developed to predict the results of in vivo blood perfusion and oxygenation measurement of transplanted organs as measured by an indwelling optical sensor. A sensor has been developed which uses three-source excitation in the red and infrared ranges (660, 810, 940 nm). In vitro data was taken using this sensor by changing the oxygenation state of whole blood and passing it through a single-tube pump system wrapped in bovine liver tissue. The collected data showed that the red signal increased as blood oxygenation increased and infrared signal decreased. The center wavelength of 810 nanometers was shown to be quite indifferent to blood oxygenation change. A model was developed using MLMC code that sampled the wavelength range from 600-1000 nanometers every 6 nanometers. Using scattering and absorption data for blood and liver tissue within this wavelength range, a five-layer model was developed (tissue, clear tubing, blood, clear tubing, tissue). The theoretical data generated from this model was compared to the in vitro data and showed good correlation with changing blood oxygenation.
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