The construction of UiO-66(Ce)/Cu oxidase for multivariate identification of acetylcholinesterase, organophosphorus pesticides and tannic acid supported by machine learning.

The widespread abuse of organophosphorus pesticides (OPs) threatens human health and ecological sustainability. The development of a portable, intelligent, and prompt detection strategy poses a key priority in both environment and human health, but remains a significant challenge. Here, visual detection of OPs was achieved based on its inhibition of acetylcholinesterase (AChE), using the constructed metal-organic framework (MOF) composite UiO-66(Ce)/Cu as a catalyst in the 3,3',5,5'-tetramethylbenzidine (TMB) oxidation process. The coexistence of Cu2 +/Cu+ and Ce4+/Ce3+ redox pairs synergistically promoted electron transfer and oxidase-mimicking (OXD-mimicking) catalysis. Based on the oxidation capability of UiO-66(Ce)/Cu and reversible colorimetric response, the AChE, OPs, and tannic acid (TA) can be detected assisted by the smartphone integrating with the machine learning algorithm. The limits of detection for TA, AChE, and OPs were determined to be 0.344 μM, 0.102 mU mL⁻¹ , and 0.0891 μg mL⁻¹ , respectively. In addition, satisfactory recoveries of 91.95-106.04% were obtained from real water and food samples, further corroborating the applicability of the intelligent and visual readout system for the portable analysis of OPs and TA. This work presented a practical strategy for constructing MOF-based OXD-mimicking nanozyme toward cascade biosensing and food safety applications.