ATP is an essential biological molecule, and abnormal levels are linked to various diseases. In this study, we developed an optical sensor array consisting of an anthracene-modified MCM-41 mesoporous nanoparticle-based hybrid organic–inorganic material to detect ATP in a TRIS-HCl buffer (pH 7). To create the sensor, we synthesized MCM-41 silica nanoparticles and functionalized them with aminoanthracene and imidazolium-anthracene groups. The fluorescence responses of the optical sensor array were recorded and analyzed by using a pattern recognition protocol, specifically linear discriminant analysis, to distinguish between ATP, ADP, AMP, and potential interferents. Quantitative regression analysis of ATP in TRIS-HCl was performed using artificial neural networks, which yielded an acceptable error rate of 7.8%. The sensor array was also evaluated for discrimination of Parkinson’s disease (PD) from healthy controls, based on pattern recognition of ATP-related analytes in saliva samples from 24 patients with PD and 23 healthy controls. The results showed that the MCM-41 mesoporous silica nanoparticle-based sensor array can discriminate PD by pattern recognition with 73.7% sensitivity and 83.3% specificity.
Ahi et al. (Fri,) studied this question.