The
ultimate detection limit of optical biosensors is often limited
by various noise sources, including those introduced by the optical
measurement setup. While sophisticated modifications to instrumentation
may reduce noise, a simpler approach that can benefit all sensor platforms
is the application of signal processing to minimize the deleterious
effects of noise. In this work, we show that applying complex Morlet
wavelet convolution to Fabry–Pérot interference fringes
characteristic of thin film reflectometric biosensors effectively
filters out white noise and low-frequency reflectance variations.
Subsequent calculation of the average difference in extracted phase
between the filtered analyte and reference signals enables a significant
reduction in the limit of detection (LOD). This method is applied
on experimental data sets of thin film porous silicon sensors (PSi)
in buffered solution and complex media obtained from two different
laboratories. The demonstrated improvement in the LOD achieved using
wavelet convolution and average phase difference paves the way for
PSi optical biosensors to operate with clinically relevant detection
limits for medical diagnostics, environmental monitoring, and food
safety.
The anterior gradient
homologue-2 (AGR2) protein is an attractive
biomarker for various types of cancer. In pancreatic cancer, it is
secreted to the pancreatic juice by premalignant lesions, which would
be an ideal stage for diagnosis. Thus, designing assays for the sensitive
detection of AGR2 would be highly valuable for the potential early
diagnosis of pancreatic and other types of cancer. Herein, we present
a biosensor for label-free AGR2 detection and investigate approaches
for enhancing the aptasensor sensitivity by accelerating the target
mass transfer rate and reducing the system noise. The biosensor is
based on a nanostructured porous silicon thin film that is decorated
with anti-AGR2 aptamers, where real-time monitoring of the reflectance
changes enables the detection and quantification of AGR2, as well
as the study of the diffusion and target-aptamer binding kinetics.
The aptasensor is highly selective for AGR2 and can detect the protein
in simulated pancreatic juice, where its concentration is outnumbered
by orders of magnitude by numerous proteins. The aptasensor’s
analytical performance is characterized with a linear detection range
of 0.05–2 mg mL–1, an apparent dissociation
constant of 21 ± 1 μM, and a limit of detection of 9.2
μg mL–1 (0.2 μM), which is attributed
to mass transfer limitations. To improve the latter, we applied different
strategies to increase the diffusion flux to and within the nanostructure,
such as the application of isotachophoresis for the preconcentration
of AGR2 on the aptasensor, mixing, or integration with microchannels.
By combining these approaches with a new signal processing technique
that employs Morlet wavelet filtering and phase analysis, we achieve
a limit of detection of 15 nM without compromising the biosensor’s
selectivity and specificity.
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