An electrochemical sensing platform based on gold nanostars for the detection of Alzheimer's disease marker Aβ oligomers (Aβo)

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid-beta (Aβ) peptides in the brain. Among the different forms of Aβ, oligomers (Aβo) are considered the most toxic and have been implicated in AD pathology. However, the accurate detection of Aβo remains challenging due to their low abundance and structural complexity. In this study, we propose an electrochemical sensing platform based on gold nanostars (AuS) for the detection of Aβo in AD. The AuS were functionalized with a peptide probe (PrPc) that specifically interacts with Aβo. The PrPc-AuS sensing platform exhibited high sensitivity and selectivity for Aβo detection. The electrochemical impedance spectroscopy (EIS) analysis showed significant changes in impedance upon binding of Aβo to the PrPc-AuS surface, providing quantitative information about the Aβo concentration. The platform demonstrated a linear detection range of 5–200 pM with a detection limit of 2 pM, meeting the requirements for clinical detection. This electrochemical sensing platform offers a promising approach for the early diagnosis and monitoring of AD, contributing to the development of point-of-care diagnostics for neurodegenerative diseases

Comparative Analysis of Theoretical, Observational, and Modeled Deformation of Ground Subsidence: The Case of the Alhada Pb-Zn Mine

In this study, the probability integral method, Synthetic Aperture Radar Interferometry (InSAR), and the Okada dislocation model were collaboratively used to analyze deformation in the Alhada Pb-Zn mine. The predicted deformation values of the subsidence centers in three subsidence areas were 107 mm, 120 mm, and 83 mm, respectively, as predicted using the probability integral method. The coherent scatterer InSAR technique was used to analyze the time-series deformation of the mining area, and the same subsidence center locations and similar deformation values were observed. The Okada dislocation model was used to invert the optimal parameters of the underground-mining ore body causing the surface subsidence, indicating that the surface subsidence is mainly caused by the mining of ore bodies in the 888 and 848 middle sections. We further simulated ground deformation using the multi-source Okada model. The results showed that the predicted and modeled deformations are highly correlated with the observed deformation. Through the analysis and comparison of the InSAR results, it was concluded that the three subsidence areas do not threaten the stability of the main buildings in the mining area. Using theoretical, observational, and modeling methods, the development and evolution of the subsidence area in mines can be established, which could provide basic data for subsidence control work and guarantee mine production safety