A novel colorimetric biosensor based on non-aggregated Au@Ag core–shell nanoparticles for methamphetamine and cocaine detection

We report a novel colorimetric biosensor based on non-aggregation Au@Ag core-shell nanoparticles to detect methamphetamine and cocaine. The biosensor consisted of a reporter probe (RP) that is a specific single-stranded DNA (ssDNA) sequence coated on Au@Ag nanoparticles, a capture probe (CP) conjugated with magnetic beads, and an illicit drug-binding DNA aptamer (Apt). Au@Ag nanoparticles were synthesized by seed growth and characterized by scanning electron microscope (SEM), high-resolution transmission electron microscopy (HR-TEM), and UV–vis spectra. Methamphetamine (METH) was used as an example to evaluate the feasibility of the biosensor and to optimize the detection conditions. We demonstrated that this sensing platform was able to detect as low as 0.1 nM (14.9 ng L−1) METH with a negligible interference from other common illicit drugs. Various concentrations of METH were spiked into urines, and the biosensor yielded recoveries more than 83.1%. In addition, the biosensor also showed a high sensitivity to detect cocaine. These results demonstrated that our colorimetric sensor holds promise to be implemented as a visual sensing platform to detect multiple illicit drugs in biological samples and environmental matrices

Multi-channel SPR biosensor based on PCF for multi-analyte sensing applications

This paper presents a theoretical investigation of a novel holey fiber (Photonic Crystal Fiber (PCF)) multi-channel biosensor based on surface plasmon resonance (SPR). The large gold coated micro fluidic channels and elliptical air hole design of our proposed biosensor aided by a high refractive index over layer in two channels enables operation in two modes; multi analyte sensing and self-referencing mode. Loss spectra, dispersion and detection capability of our proposed biosensor for the two fundamental modes (HE x 11 and HE y 11 ) have been elucidated using a Finite Element Method (FEM) and Perfectly Matching Layers (PML)

Silicon-based nanochannel glucose sensor

Silicon nanochannel biological field effect transistors have been developed for glucose detection. The device is nanofabricated from a silicon-on-insulator wafer with a top-down approach and surface functionalized with glucose oxidase. The differential conductance of silicon nanowires, tuned with source-drain bias voltage, is demonstrated to be sensitive to the biocatalyzed oxidation of glucose. The glucose biosensor response is linear in the 0.5-8 mM concentration range with 3-5 min response time. This silicon nanochannel-based glucose biosensor technology offers the possibility of high density, high quality glucose biosensor integration with silicon-based circuitry.Comment: 3 pages, 3 figures, two-column format. Related papers can be found at http://nano.bu.ed

Inhibition-based first-generation electrochemical biosensors: theoretical aspects and application to 2,4-dichlorophenoxy acetic acid detection

In this work, several theoretical aspects involved in the first-generation inhibition-based electrochemical biosensor measurements have been discussed. In particular, we have developed a theoretical-methodological approach for the characterization of the kinetic interaction between alkaline phosphatase (AlP) and 2,4- dichlorophenoxy acetic acid (2,4-D) as representative inhibitor studied by means of cyclic voltammetry and amperometry. Based on these findings, a biosensor for the fast, simple, and inexpensive determination of 2,4-D has been developed. The enzyme has been immobilized on screen-printed electrodes (SPEs). To optimize the biosensor performances, several carbon-based SPEs, namely graphite (G), graphene (GP), and multiwalled carbon nanotubes (MWCNTs), have been evaluated. AlP was immobilized on the electrode surface by means of polyvinyl alcohol with styryl-pyridinium groups (PVA-SbQ) as cross-linking agent. In the presence of ascorbate 2-phosphate (A2P) as substrate, the herbicide has been determined, thanks to its inhibition activity towards the enzyme catalyzing the oxidation of A2P to ascorbic acid (AA). Under optimum experimental conditions, the best performance in terms of catalytic efficiency has been demonstrated by MWCNTs SPE-based biosensor. The inhibition biosensor shows a linearity range towards 2,4-D within 2.1–110 ppb, a LOD of 1 ppb, and acceptable repeatability and stability. This analysis method was applied to fortified lake water samples with recoveries above 90 %. The low cost of this device and its good analytical performances suggest its application for the screening and monitoring of 2,4-D in real matrices

On noise processes and limits of performance in biosensors

In this paper, we present a comprehensive stochastic model describing the measurement uncertainty, output signal, and limits of detection of affinity-based biosensors. The biochemical events within the biosensor platform are modeled by a Markov stochastic process, describing both the probabilistic mass transfer and the interactions of analytes with the capturing probes. To generalize this model and incorporate the detection process, we add noisy signal transduction and amplification stages to the Markov model. Using this approach, we are able to evaluate not only the output signal and the statistics of its fluctuation but also the noise contributions of each stage within the biosensor platform. Furthermore, we apply our formulations to define the signal-to-noise ratio, noise figure, and detection dynamic range of affinity-based biosensors. Motivated by the platforms encountered in practice, we construct the noise model of a number of widely used systems. The results of this study show that our formulations predict the behavioral characteristics of affinity-based biosensors which indicate the validity of the model