Fluorescence-based glucose sensors

Pickup, John C.; Hussain, Faeiza; Evans, Nicholas D.; Rolinski, Olaf J.; Birch, David J. S.

doi:10.1016/j.bios.2004.10.002

Cited by 560 publications

(336 citation statements)

References 63 publications

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“…lactate, ammonia, glutamate, oxygen, and carbon dioxide, are mostly determined by on-line and off-line methods using common probes, standard assay kits as well as chromatographic methods (HPLC, Ion Chromatography). Different glucose sensors (off-line and on-line) are available [Folly and B., 1996, Male et al, 1997, Pickup et al, 2005, but stability, calibration and validation of these probes remains an issue [Renneberg and Lisdat, 2008]. An example for a PAT-tool for glucose measurement is a continuous flow injection analysis based on chemiluminescence [Huang et al, 1991].…”

Section: Substrate and Metabolite Concentrationmentioning

confidence: 99%

Process control in cell culture technology using dielectric spectroscopy

Justice¹,

Brix

Freimark³

et al. 2011

Biotechnology Advances

106

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Section: Substrate and Metabolite Concentrationmentioning

confidence: 99%

Process control in cell culture technology using dielectric spectroscopy

Justice¹,

Brix

Freimark³

et al. 2011

Biotechnology Advances

106

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“…By inspecting the relative fluorescence intensities of the line scan data corresponding to the particle center and comparing those to the intensities at the surface, it is evident that solution pH determines whether GOx distribution is uniform (Figure 2, pH 3 and 4) or non-uniform (Figure 2, pH 5 and 6). To quantitatively compare the profiles, the following equation was introduced to calculate an associated distribution index, D r (1) where ν̄ is the average fluorescence intensity of the center 10% of the particle and ᾱ and β̄ are the average fluorescence intensities of the outer 10% of the distribution profile, located at the right and left boundaries of the particle surface, respectively. As the value of D r approaches unity, GOx is uniformly distributed throughout the particle, and as D r approaches 0, the distribution of GOx becomes inhomogeneous, with bias toward the surface boundaries.…”

Section: Sensor Component Immobilizationmentioning

confidence: 99%

Microscale Enzymatic Optical Biosensors Using Mass Transport Limiting Nanofilms. 1. Fabrication and Characterization Using Glucose as a Model Analyte

et al. 2007

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Abstract"Smart tattoo" sensors -fluorescent microspheres which can be implanted intradermally and interrogated noninvasively using light -are being developed as potential tools for in vivo biochemical monitoring. In this work, a platform for enzymatic tattoo-type sensors is described, and prototype devices evaluated using glucose as a model analyte. Sensor particles were prepared by immobilizing Pt(II) octaethylporphine (PtOEP), a phosphorescent dye readily quenched by molecular oxygen, into hybrid silicate microspheres, followed by loading and subsequent covalent immobilization of glucose oxidase (GOx). Rhodamine B (RITC)-doped multilayer nanofilms were subsequently assembled on the surfaces of the particles to provide a reference signal and provide critical control of glucose transport into the particle. The enzymatic oxidation of glucose within the sensor results in the glucose concentration-dependent depletion of local oxygen levels, enabling indirect monitoring of glucose by measuring relative changes in PtOEP emission. A custom testing apparatus was used to monitor the dynamic sensor response to varying bulk oxygen and glucose levels, respectively. For the prototypes tested, dynamic test results indicate that the sensors respond rapidly (t 95 = 84 sec) and reversibly to changes in bulk glucose levels, while demonstrating high baseline stability. The sensitivity (change in intensity ratio) of these devices was determined to be 4.16 ± 0.57 %/mg dL −1 . The analytical range for the prototypes was determined to be 2 to 120 mg/dl, though this can be extended to cover the physiologically relevant range by tailoring the nanofilm coatings. These findings confirm the potential for enzymatic microscale optical, and pave the way for extension of this initial demonstration with glucose to target other biochemical species relevant to metabolic monitoring.

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“…Additionally, this technology was not applicable to individuals with skin pigmentation, light scattering from the tissue, and was affected by epidermal thickness. [21] The stiff hydrogel fibers have been fabricated from PEG-diacrylate (PEGDA) (700 Da), which was not compatible with sensing mechanisms based on volumetric change-induced quantitative measurements in hydrogels. [20a] …”

mentioning

confidence: 99%

Glucose‐Sensitive Hydrogel Optical Fibers Functionalized with Phenylboronic Acid

et al. 2017

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Optical fibers are widely used in biomedical applications for sensing, imaging, and therapies. Unlike existing solid-state optical fibers, soft polymer and hydrogel fibers offer physical and chemical properties well suited for functionalization with biomolecules and long-term implantation in the body. Here, hydrogel optical fibers are fabricated with glucose-sensitive moieties and the swelling-induced sensing is demonstrated. The core of the fiber is made of poly(acrylamide-co-poly(ethylene glycol) diacrylate) (p(AM-co-PEGDA)) hydrogel functionalized with phenylboronic acid. The complexation of the phenylboronic acid and cis diols of glucose molecules lowers the apparent pKa of the hydrogel network and increases the concentration of the boronate anions that enhances the Donnan osmotic pressure to swell and change the physical size of the hydrogel optical fiber. This mechanism is reversible through ester group dynamic covalent binding of the phenylboronic acid with glucose molecules. Dynamic changes in the effective RI of the hydrogel optical fiber are measured through light propagation loss. The sensor sensitivity to glucose concentration is 1.2 mmol L−1 over a physiological range of 1–12 mmol L−1. The biocompatible hydrogel optical fibers may be subcutaneously implanted for continuous monitoring of interstitial glucose concentrations.

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Fluorescence-based glucose sensors

Cited by 560 publications

References 63 publications

Process control in cell culture technology using dielectric spectroscopy

Process control in cell culture technology using dielectric spectroscopy

Microscale Enzymatic Optical Biosensors Using Mass Transport Limiting Nanofilms. 1. Fabrication and Characterization Using Glucose as a Model Analyte

Glucose‐Sensitive Hydrogel Optical Fibers Functionalized with Phenylboronic Acid

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