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- Fachbereich Medizintechnik und Technomathematik (61) (remove)
Three amperometric biosensors have been developed for the detection of L-malic acid, fumaric acid, and L -aspartic acid, all based on the combination of a malate-specific dehydrogenase (MDH, EC 1.1.1.37) and diaphorase (DIA, EC 1.8.1.4). The stepwise expansion of the malate platform with the enzymes fumarate hydratase (FH, EC 4.2.1.2) and aspartate ammonia-lyase (ASPA, EC 4.3.1.1) resulted in multi-enzyme reaction cascades and, thus, augmentation of the substrate spectrum of the sensors. Electrochemical measurements were carried out in presence of the cofactor β-nicotinamide adenine dinucleotide (NAD+) and the redox mediator hexacyanoferrate (III) (HCFIII). The amperometric detection is mediated by oxidation of hexacyanoferrate (II) (HCFII) at an applied potential of + 0.3 V vs. Ag/AgCl. For each biosensor, optimum working conditions were defined by adjustment of cofactor concentrations, buffer pH, and immobilization procedure. Under these improved conditions, amperometric responses were linear up to 3.0 mM for L-malate and fumarate, respectively, with a corresponding sensitivity of 0.7 μA mM−1 (L-malate biosensor) and 0.4 μA mM−1 (fumarate biosensor). The L-aspartate detection system displayed a linear range of 1.0–10.0 mM with a sensitivity of 0.09 μA mM−1. The sensor characteristics suggest that the developed platform provides a promising method for the detection and differentiation of the three substrates.
The immobilization of NAD+-dependent dehydrogenases, in combination with a diaphorase, enables the facile development of multiparametric sensing devices. In this work, an amperometric biosensor array for simultaneous determination of ethanol, formate, d- and l-lactate is presented. Enzyme immobilization on platinum thin-film electrodes was realized by chemical cross-linking with glutaraldehyde. The optimization of the sensor performance was investigated with regard to enzyme loading, glutaraldehyde concentration, pH, cofactor concentration and temperature. Under optimal working conditions (potassium phosphate buffer with pH 7.5, 2.5 mmol L-1 NAD+, 2.0 mmol L-1 ferricyanide, 25 °C and 0.4% glutaraldehyde) the linear working range and sensitivity of the four sensor elements was improved. Simultaneous and cross-talk free measurements of four different metabolic parameters were performed successfully. The reliable analytical performance of the biosensor array was demonstrated by application in a clarified sample of inoculum sludge. Thereby, a promising approach for on-site monitoring of fermentation processes is provided.
Altered neurovascular coupling as measured by optical imaging: a biomarker for Alzheimer’s disease
(2017)
Field-effect EIS (electrolyte-insulator-semiconductor) sensors modified with a positively charged weak polyelectrolyte layer have been applied for the electrical detection of DNA (deoxyribonucleic acid) immobilization and hybridization by the intrinsic molecular charge. The EIS sensors are able to detect the existence of target DNA amplicons in PCR (polymerase chain reaction) samples and thus, can be used as tool for a quick verification of DNA amplification and the successful PCR process. Due to their miniaturized setup, compatibility with advanced micro- and nanotechnologies, and ability to detect biomolecules by their intrinsic molecular charge, those sensors can serve as possible platform for the development of label-free DNA chips. Possible application fields as well as challenges and limitations will be discussed.
In a special paired sample case, Hotelling’s T² test based on the differences of the paired random vectors is the likelihood ratio test for testing the hypothesis that the paired random vectors have the same mean; with respect to a special group of affine linear transformations it is the uniformly most powerful invariant test for the general alternative of a difference in mean. We present an elementary straightforward proof of this result. The likelihood ratio test for testing the hypothesis that the covariance structure is of the assumed special form is derived and discussed. Applications to real data are given.