Abstract

Dopaminergic agents are compounds that modulate dopamine-related activity in the brain and peripheral nerves within the pathways on both sides of the blood-brain barrier. Atypical levels of them can precipitate a multitude of neurological disorders, whose timely diagnosis signifies not only stopping the advancement of the illness but also surmounting it. A silver metallized gold nanorod (AuNRs) conditional sensor array, designed to detect dopaminergic agents for assessing nervous system disorders, yielded significant results in simultaneous detection and discrimination of Benserazide (Benz), Levodopa (L-DOPA), and Carbidopa (Carb). The array was composed of two different concentrations of silver ions as sensor elements (SEs), which generated unique signatures indicative of the presence of reductive target analytes, triggered by the incongruent formation of the Au@Ag core-shell, causing visual and fingerprint colorimetric patterns. Generating diverse responses is the key to the functionality of array-based sensing, which facilitated achieving spectral and color variation originating from the blue shift of AuNRs longitudinal localized surface plasmon resonance (LLSPR) in the extinction spectrum. Also, employing a smartphone camera enables clear visual discrimination across an extensive concentration span. Pattern recognition through linear discriminant analysis (LDA) underscored the robust discrimination accuracies of this sensor, along with quantification by means of partial least-squares regression (PLSR), affirming its potential for practical applications. Notably, the array demonstrated high sensitivity in detecting varied concentrations of target analytes, even in commercial drug samples. The sensor responses exhibited a linear correlation with the concentrations of Benz, L-DOPA, and Carb ranging from 1.59 to 100.0, 5.26 to 100.0, and 5.32 to 100.0 μmol L-1, respectively, and the minimum detectable concentrations for Benz, L-DOPA, and Carb were measured at 0.53, 1.75, and 1.77 μmol L-1, respectively. The implemented machine-learning-empowered array-based sensor represents advancements in dopaminergic agent tracing and naked eye detection.

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