Amperometric Biosensor Based on Glutamate Oxidase to Determine Ast Activity.

This work presents the development of an amperometric biosensor for detecting aspartate aminotransferase (AST) activity in biological fluids using a platinum disk electrode as the working transducer. Optimal concentrations of substrates (aspartate, α-ketoglutarate) and the coenzyme (pyridoxal phosphate) were determined to ensure efficient biosensor operation. A semi-permeable poly-m-phenylenediamine membrane was applied to enhance selectivity against electroactive interferents.

Operational stability study of lactate biosensors: modeling, parameter identification, and stability analysis.

Introduction: This paper investigates the operational stability of lactate biosensors, crucial devices in various biomedical and biotechnological applications. We detail the construction of an amperometric transducer tailored for lactate measurement and outline the experimental setup used for empirical validation.

Methods: The modeling framework incorporates Brown and Michaelis-Menten kinetics, integrating both distributed and discrete delays to capture the intricate dynamics of lactate sensing.

Stability in biosensors derived from domain map analysis of bibliometric data.

In the presented work, advanced methods of analysis and visualization were used to compile trends and patterns in the scientific literature. The most relevant information for the stability of biosensors was selected on the basis of clusters constructed on the basis of keywords. The most significant publications in the clusters appearing over time were analyzed.

On Model of Recurrent Neural Network on a Time Scale: Exponential Convergence and Stability Research.

The majority of the results on modeling recurrent neural networks (RNNs) are obtained using delayed differential equations, which imply continuous time representation. On the other hand, these models must be discrete in time, given their practical implementation in computer systems, requiring their versatile utilization across arbitrary time scales. Hence, the goal of this research is to model and investigate the architecture design of a delayed RNN using delayed differential equations on a time scale.

Nonlinear Analytics for Electrochemical Biosensor Design Using Enzyme Aggregates and Delayed Mass Action.

The paper is devoted to the extension of Brown's model of enzyme kinetics to the case with distributed delays. Firstly, we construct a multi-substrate multi-inhibitor model using discrete and distributed delays. Furthermore, we consider simplified models including one substrate and one inhibitor, for which an experimental study has been performed.

A meta-analysis of the influence of the external conditions on the biosensor receptor layer component stability.

The manuscript presented here contains meta-analysis of the influence of the external conditions on the biosensor receptor layer component stability. The novelty of this paper is due to compilation and comparison of studies, based on proposed collective analyses. The presented meta-analysis allows to increase the precision and accuracy of the results by combining and co-analyzing data from five smaller experiments.

On qualitative analysis of the nonstationary delayed model of coexistence of two-strain virus: Stability, bifurcation, and transition to chaos.

The model of interaction of two strains of the virus is considered in the paper. The model is based on a nonstationary system of differential equations with delays and takes into account populations of susceptible, first-time and re-infected individuals across two strains. For small values of the delays, the conditions of global asymptotic stability are obtained with the help of Lyapunov functionals technique.