The authors developed an anthracene-functionalized MCM-41 nanoparticle fluorescence sensor array to detect ATP and used pattern-recognition (LDA, ANN) on saliva samples to discriminate Parkinson's disease patients from controls (n=24 vs 23) with 73.7% sensitivity and 83.3% specificity.

Offers a noninvasive, ATP-focused salivary biomarker assay reflecting metabolic/mitochondrial perturbations relevant to PD that could support patient stratification or monitoring, but it has limited immediate therapeutic discovery impact and requires larger clinical validation.

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.