Electrochemical Signal Substance for Multiplexed Immunosensing Interface Construction: A Mini Review

Appropriate labeling method of signal substance is necessary for the construction of multiplexed electrochemical immunosensing interface to enhance the specificity for the diagnosis of cancer. So far, various electrochemical substances, including organic molecules, metal ions, metal nanoparticles, Prussian blue, and other methods for an electrochemical signal generation have been successfully applied in multiplexed biosensor designing. However, few works have been reported on the summary of electrochemical signal substance applied in constructing multiplexed immunosensing interface. Herein, according to the classification of labeled electrochemical signal substance, this review has summarized the recent state-of-art development for the designing of electrochemical immunosensing interface for simultaneous detection of multiple tumor markers. After that, the conclusion and prospects for future applications of electrochemical signal substances in multiplexed immunosensors are also discussed. The current review can provide a comprehensive summary of signal substance selection for workers researched in electrochemical sensors, and further, make contributions for the designing of multiplexed electrochemical immunosensing interface with well signal.

A Mathematical Characterization for Patterns of a Keller-Segel Model with a Cubic Source Term

This paper deals with a Neumann boundary value problem for a Keller-Segel model with a cubic source term in ad-dimensional box(d=1,2,3), which describes the movement of cells in response to the presence of a chemical signal substance. It is proved that, given any general perturbation of magnitudeδ, its nonlinear evolution is dominated by the corresponding linear dynamics along a finite number of fixed fastest growing modes, over a time period of the order ln(1/δ). Each initial perturbation certainly can behave drastically differently from another, which gives rise to the richness of patterns. Our results provide a mathematical description for early pattern formation in the model.