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Surface-enhanced Raman scattering (SERS) has started to attract attention in vapor sensing; however, practical applications require shorter response time and better sensitivity. Herein, we report a...

When myocardial walls experience stress due to cardiovascular diseases, like heart failure, hormone N-terminal pro-B-type natriuretic peptide (NT-proBNP) is secreted into the blood. Early detection of NT-proBNP can assist diagnosis of heart failure and enable early medical intervention. A simple, cost-effective detection technique such as the widely used fluorescence imaging immunoassay is yet to be developed to detect clinically relevant levels of NT-proBNP. In this work, we demonstrate photonic crystal-enhanced fluorescence imaging immunoassay using diatom biosilica, which is capable of detecting low levels of NT-proBNP in solution with the concentration range of 0˜100 pg/mL. By analyzing the fluorescence images in the spatial and spatial frequency domain with principle component analysis (PCA) and partial least squares regression (PLSR) algorithms, we create a predictive model that achieves great linearity with a validation R2 value of 0.86 and a predictive root mean square error of 14.47, allowing for good analyte quantification. To demonstrate the potential of the fluorescence immunoassay biosensor for clinical usage, we conducted qualitative screening of high and low concentrations of NT-proBNP in human plasma. A more advanced machine learning algorithm, the support vector machine classification, was paired with the PCA and trained by 160 fluorescence images. In the 40 testing images, we achieved excellent specificity of 93%, as well as decent accuracy and sensitivity of 78% and 65% respectively. Therefore, the photonic crystal-enhanced fluorescence imaging immunoassay reported in this article is feasible to screen clinically relevant levels of NT-proBNP in body fluid and evaluate the risk of heart failure.

Tetrahydrocannabinol (THC) is the main active component in marijuana and the rapid detection of THC in human body fluid plays a critical role in forensic analysis and public health. Surface-enhanced Raman scattering (SERS) sensing has been increasingly used to detect illicit drugs; however, only limited SERS sensing results of THC in methanol solution have been reported, while its presence in body fluids, such as saliva or plasma, has yet to be investigated. In this article, we demonstrate the trace detection of THC in human plasma and saliva solution using a SERS-active substrate formed by in situ growth of silver nanoparticles (Ag NPs) on diatom frustules. THC at extremely low concentration of 1 pM in plasma and purified saliva solutions were adequately distinguished with good reproducibility. The SERS peak at 1603 cm-1 with standard deviation of 3.4 cm-1 was used for the evaluation of THC concentration in a methanol solution. Our SERS measurement also shows that this signature peak experiences a noticeable wavenumber shift and a slightly wider variation in the plasma and saliva solution. Additionally, we observed that THC in plasma or saliva samples produces a strong SERS peak at 1621 cm-1 due to the stretching mode of O-C═O, which is related to the metabolic change of THC structures in body fluid. To conduct a quantitative analysis, principal component analysis (PCA) was applied to analyze the SERS spectra of 1 pM THC in methanol solution, plasma, and purified saliva samples. The maximum variability of the first three principal components was achieved at 71%, which clearly denotes the impact of different biological background signals. Similarly, the SERS spectra of THC in raw saliva solution under various metabolic times were studied using PCA and 98% of the variability is accounted for in the first three principal components. The clear separation of samples measured at different THC resident times can provide time-dependent information on the THC metabolic process in body fluids. A linear regression model was used to estimate the metabolic rate of THC in raw saliva and the predicted metabolic time in the testing data set matched well with the training data set. In summary, the hybrid plasmonic-biosilica SERS substrate can achieve ultrasensitive, near-quantitative detection of trace levels of THC in complex body fluids, which can potentially transform forensic sensing techniques to detect marijuana abuse.

Surface-enhanced Raman scattering (SERS) sensing in microfluidic devices, namely optofluidic-SERS, suffers an intrinsic trade-off between mass transport and hot spot density, both of which are required for ultra-sensitive detection. To overcome this compromise, photonic crystal-enhanced plasmonic mesocapsules are synthesized, utilizing diatom biosilica decorated with in-situ growth silver nanoparticles (Ag NPs). In our optofluidic-SERS testing, 100× higher enhancement factors and greater than 1,000× better detection limit were achieved compared with traditional colloidal Ag NPs, the improvement of which is attributed to unique properties of the mesocapsules. First, the porous diatom biosilica frustules serve as carrier capsules for high density Ag NPs that form high density plasmonic hot-spots. Second, the submicron-pores embedded in the frustule walls not only create a large surface-to-volume ratio allowing for effective analyte capture, but also enhance the local optical field through the photonic crystal effect. Last, the mesocapsules provide effective mixing with analytes as they are flowing inside the microfluidic channel. The reported mesocapsules achieved single molecule detection of Rhodamine 6G in microfluidic devices and were further utilized to detect 1 nM of benzene and chlorobenzene compounds in tap water with near real-time response, which successfully overcomes the constraint of traditional optofluidic sensing.

The precise control of both the size and shape of Ag nanoparticles strongly influences their optical properties. Although the synthesis of Ag nanocubes with sharp corners and edges has been demonstrated, the ability to scale these approaches with high selectivity remains elusive. In this study, a continuous flow microwave-assisted reactor was used to separate nucleation from growth events, which provides a method to synthesize very uniform single crystalline Ag nanocubes. Nucleation in the microwave zone was enhanced through seed-mediated processes by sulfide formation, and a chemical regulator was used in the growth zone to further improve the sharpness of the edges of the nanocubes. Transmission electron microscopy and optical properties were used to optimize the reaction conditions and Ag nanocubes with edge lengths of 28 and 45 nm were readily synthesized with narrow particle size distributions and high selectivities (>70%). Nanocubes with 28 nm edge lengths were used to prepare films to demonstrate t...

Scombroid fish poisoning caused by histamine intoxication is one of the most prevalent allergies associated with seafood consumption in the United States. Typical symptoms range from mild itching up to fatal cardiovascular collapse seen in anaphylaxis. In this paper, we demonstrate rapid, sensitive, and quantitative detection of histamine in both artificially spoiled tuna solution and real spoiled tuna samples using thin layer chromatography in tandem with surface-enhanced Raman scattering (TLC-SERS) sensing methods, enabled by machine learning analysis based on support vector regression (SVR) after feature extraction with principal component analysis (PCA). The TLC plates used herein, which were made from commercial food-grade diatomaceous earth, served simultaneously as the stationary phase to separate histamine from the blended tuna meat and as ultra-sensitive SERS substrates to enhance the detection limit. Using a simple drop cast method to dispense gold colloidal nanoparticles onto the diatomaceous earth plate, we were able to directly detect histamine concentration in artificially spoiled tuna solution down to 10 ppm. Based on the TLC-SERS spectral data of real tuna samples spoiled at room temperature for 0 to 48 hours, we used the PCA-SVR quantitative model to achieve superior predictive performance exceling traditional partial least squares regression (PLSR) method. This work proves that diatomaceous earth based TLC-SERS technique combined with machine-learning analysis is a cost-effective, reliable, and accurate approach for on-site detection and quantification of seafood allergen to enhance food safety.

Fluorescence biosensing is one of the most established biosensing methods, particularly fluorescence spectroscopy and microscopy. These are two highly sensitive techniques but require high-grade electronics and optics to achieve the desired sensitivity. Efforts have been made to implement these methods using consumer grade electronics and simple optical setups for applications such as point-of-care diagnostics, but the sensitivity inherently suffers. Sensing substrates, capable of enhancing fluorescence are thus needed to achieve high sensitivity for such applications. In this paper, we demonstrate a photonic crystal-enhanced fluorescence immunoassay biosensor using diatom biosilica, which consists of silica frustules with sub-100 nm periodic pores. Utilizing the enhanced local optical field, the Purcell effect and increased surface area from the diatom photonic crystals, we create ultrasensitive immunoassay biosensors that can significantly enhance fluorescence spectroscopy as well as fluorescence imaging. Using standard antibody-antigen-labeled antibody immunoassay protocol, we experimentally achieved 100× and 10× better detection limit with fluorescence spectroscopy and fluorescence imaging respectively. The limit of detection of the mouse IgG goes down to 10-16 M (14 fg/mL) and 10-15 M (140 fg/mL) for the two respective detection modalities, virtually sensing a single mouse IgG molecule on each diatom frustule. The effectively enhanced fluorescence imaging in conjunction with the simple hot-spot counting analysis method used in this paper proves the great potential of diatom fluorescence immunoassay for point-of-care biosensing.

We report an ultra-compact, cost-effective on-chip near-infrared spectroscopy system for CO2 sensing using narrow-band optical filter array based on plasmonic gratings with a waveguide layer. By varying the periodicity of the gratings, the transmission spectra of the filters can be continuously tuned to cover the 2.0 μm sensing window with high spectral resolution around 10 nm. Our experimental results show that the on-chip spectroscopy system can resolve the two symmetric vibrational bands of CO2 at 2.0 μm wavelength, which proves its potential to replace the expensive commercial IR spectroscopy system for on-site gas sensing.

By coupling surface-enhanced Raman spectroscopy (SERS) with thin-layer chromatography, hybrid photonic crystal- plasmonic devices provide lab-on-a-chip functionalities for separating and detecting multiple chemical targets in a complex solution.