The progression of Alzheimer’s disease (AD) is positively correlated with the phosphorylation damage of Tau-441 protein, which is the marker with the most potential for the early detection of AD. The low content of Tau-441 in human serum is a major difficulty for the realization of content detection. Herein, we prepared an electrochemical immunosensor modified with Poly(3,4-ethylene-dioxythiophene)-poly (styrene sulfonate) (PEDOT: PSS)/Carboxylated multi-walled carbon nanotube (MWCNTs-COOH) nanocomposites based on electrochemical immunoassay technology for the low-concentration detection of Tau-441. The immunosensor based on the nanocomposite can take advantage of the characteristics of conductive polymers to achieve electrical signal amplification and use MWCNTs-COOH to increase the contact area of the active site and bond with the Tau-441 antibodies on the electrode. The physicochemical and electrical properties of PEDOT: PSS/MWCNTs-COOH were studied by in situ characterization techniques and electrochemical characterization methods, indicating that the immunosensor has high selectivity and sensitivity to the Tau-441 immune reaction. Under optimized optimal conditions, the electrochemical immunosensor detected a range of concentrations of Tau-441 to obtain a low detection of limit (0.0074 ng mL⁻¹) and demonstrated good detection performance through actual human serum sample testing experiments. Therefore, the study provides an effective reference value for the early diagnosis of AD.

This paper investigates the asynchronous non-fragile $H_{\infty }$ control problem for a class of Markovian jump singularly perturbed systems (MJSPSs) with time-varying delays. By applying a multi-layer structure method, a non-fragile controller with time delay is designed for the MJSPSs to adapt to disturbances caused by nonstationary quantization and DoS attacks. To model the asynchronous dynamics between the system and the controller mode, an independent Markov chain is employed to capture the asynchronous quantization and control behavior. By constructing mode-dependent Lyapunov–Krasovskii functions, sufficient conditions are derived to ensure stochastic finite-time exponential stability and $H_{\infty }$ performance under conditions of delay, singular disturbances, and quantization uncertainty. The effectiveness of the method is validated using an inverted pendulum system controlled by a DC motor, demonstrating its ability to achieve robust stability and performance in bandwidth-constrained network environments.