Microfluidic surface-enhanced Raman scattering sensor with monolithically integrated nanoporous gold disk arrays for rapid and label-free biomolecular detection

Li, Ming; Zhao, Fei; Zeng, Jin; Qi, Ji; Lü, Jing; Shih, Wei-Chuan

doi:10.1117/1.jbo.19.11.111611

Cited by 81 publications

(46 citation statements)

References 58 publications

(61 reference statements)

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“…[4][5][6][7][8][9][10][11][12][13] The intensity of a Raman signal bears a linear relationship to the analyte concentrations, therefore, Raman spectroscopy can be used as a quantitative tool in concentration measurements as well. 1,4,5,[14][15][16][17] An ultimate goal in this field is to develop Raman spectroscopy-based techniques for biomedical applications through instrumentation, [18][19][20][21][22] plasmonic substrates, [23][24][25][26][27] devices, 28,29 assays, 30,31 and techniques. 32,33 Raman spectroscopic measurements, like other optical techniques, pose minimal danger from exposure to ionizing radiation due to the low-energy optical radiation exposure.…”

Section: Introductionmentioning

confidence: 99%

Noninvasive glucose sensing by transcutaneous Raman spectroscopy

2015

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Abstract. We present the development of a transcutaneous Raman spectroscopy system and analysis algorithm for noninvasive glucose sensing. The instrument and algorithm were tested in a preclinical study in which a dog model was used. To achieve a robust glucose test system, the blood levels were clamped for periods of up to 45 min. Glucose clamping and rise/fall patterns have been achieved by injecting glucose and insulin into the ear veins of the dog. Venous blood samples were drawn every 5 min and a plasma glucose concentration was obtained and used to maintain the clamps, to build the calibration model, and to evaluate the performance of the system. We evaluated the utility of the simultaneously acquired Raman spectra to be used to determine the plasma glucose values during the 8-h experiment. We obtained prediction errors in the range of ∼1.5 − 2 mM. These were in-line with a best-case theoretical estimate considering the limitations of the signal-to-noise ratio estimates. As expected, the transition regions of the clamp study produced larger predictive errors than the stable regions. This is related to the divergence of the interstitial fluid (ISF) and plasma glucose values during those periods. Two key contributors to error beside the ISF/plasma difference were photobleaching and detector drift. The study demonstrated the potential of Raman spectroscopy in noninvasive applications and provides areas where the technology can be improved in future studies.

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Section: Introductionmentioning

confidence: 99%

Noninvasive glucose sensing by transcutaneous Raman spectroscopy

2015

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“…[8][9][10][11][12] We demonstrated that CR provides improved performance using numerical models as well as experimental Raman spectra acquired from human subjects. We show that with CR both the standard error obtained using leave-one-out cross validation (SEV) and the standard error of prediction (SEP) improve compared to results obtained using PLS.…”

Section: Introductionmentioning

confidence: 99%

Constrained regularization for noninvasive glucose sensing using Raman spectroscopy

Shih

2015

J. Innov. Opt. Health Sci.

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Multivariate calibration is an important tool for spectroscopic measurement of analyte concentrations. We present a detailed study of a hybrid multivariate calibration technique, constrained regularization (CR), and demonstrate its utility in noninvasive glucose sensing using Raman spectroscopy. Similar to partial least squares (PLS) and principal component regression (PCR), CR builds an implicit model and requires knowledge only of the concentrations of the analyte of interest. Calibration is treated as an inverse problem in which an optimal balance between model complexity and noise rejection is achieved. Prior information is included in the form of a spectroscopic constraint that can be obtained conveniently. When used with an appropriate constraint, CR provides a better calibration model compared to PLS in both numerical and experimental studies.

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“…NPG arrays have been demonstrated in various plasmonic sensing mechanisms such as refractive index sensing via extinction spectroscopy, as well as spectroscopic fingerprinting by enhanced fluorescence, NIR absorption, and Raman spectroscopy [8][9][10][11]14]. A number of label-free biosensing applications have been developed in the past 4 years for nucleic acids, proteins, enzymes, metabolites, neurotransmitters, polycyclic aromatic hydrocarbons, carcinogenic environmental and food contaminants, and etc [11,[19][20][21][22][23].…”

Section: Nanoporous Gold Nanoparticles and Arraysmentioning

confidence: 99%

3D plasmonic nanoarchitecture as an emerging biosensing platform

Arnob

Shih

2017

Nanomedicine

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Propagating & localized surface plasmon resonanceRecent advances in plasmonics of coinage metals have attracted significant interest in the biosensing community [1,2]. Surface plasmon resonance refers to the oscillation of conduction band electrons excited by light. Often touted as a label-free sensing technique, surface plasmon resonance based sensing and imaging have become commercially available for quite some time, and are employed in applications such as studying protein-protein interactions, immunochemical procedures and drug-receptor binding. Traditional surface plasmon resonance sensors rely on the propagating surface plasmon resonance (PSPR), where light-electron coupling is obtained via total-internalreflection, a condition typically achieved by prism coupling [3][4][5]. Due to the unconventional nature of light coupling, PSPR sensors face challenges in instrument miniaturization and simplification. Another limiting factor for PSPR imaging is spatial resolution. Although, confined to the metal-dielectric interface, plasmon waves do propagate along the interface, therefore degrades spatial resolution.Localized surface plasmon resonance (LSPR) refers to nonpropagating plasmon modes identified in various nanostructures and colloidal nanoparticles [6]. In contrast to PSPR, LSPR provides the possibility of free-space light coupling and highly confined fields in all three dimensions, thanks to the nanostructures. These features can significantly reduce system complexity and measurement requirements [7]. In addition, since nanostructures are involved, the latitude of engineering design has substantially increased compared with PSPR where a thin film suffices. LSPR associated light concentration & field enhancementThe light concentrating property of LSPR is a focal point of modern plasmonic biosensing research. Typically understood as collective electron oscillation, LSPR produces highly localized electromagnetic field enhancement in plasmonic nanomaterials [6]. Plasmonic hot-spots refer to the locations, in close proximity of nanostructures, where electromagnetic fields are particularly enhanced relative to the incident field. LSPR associated local field concentration has been shown to enhance a variety of electronic as well as vibrational spectroscopic techniques. Among those, prominent examples can be drawn from Raman scattering, infrared and near-infrared (NIR) absorption and fluorescence [8][9][10][11].Traditional plasmonic nanomaterials are 1D (e.g., colloidal nanoparticles) or 2D (lithographically patterned nanostructure arrays) in nature, which typically result in sparse field concentration patterns. To improve efficiency and better utilization of hot-spots, the concept of 3D plasmonic nanoarchitecture, where abundant hot-spots are formed in a 3D volumetric fashion, have emerged [12]. Practically, there are several potential advantages of plasmonic sensing. First, many plasmonic sensing mechanisms can be implemented in a label-free fashion which requires no additional binding of fluorescent tag or radi...

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Microfluidic surface-enhanced Raman scattering sensor with monolithically integrated nanoporous gold disk arrays for rapid and label-free biomolecular detection

Cited by 81 publications

References 58 publications

Noninvasive glucose sensing by transcutaneous Raman spectroscopy

Noninvasive glucose sensing by transcutaneous Raman spectroscopy

Constrained regularization for noninvasive glucose sensing using Raman spectroscopy

3D plasmonic nanoarchitecture as an emerging biosensing platform

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