Optimization of Subsecond Estradiol Detection through Analysis of Surface-Analyte Interactions.

Subsecond neurochemical signaling is the fastest and one of the most diverse forms of intercellular communication employed along the neuro-immune-endocrine axis; consequently, spatiotemporally resolved approaches with high sensitivity and selectivity tailored to specific analytes are required for adequate monitoring. However, many existing electrochemical approaches are optimized solely towards catecholamine and indolamine detection, leaving a wide array of structurally diverse neuroregulators at a disadvantage with limited detection capability. Here, we use estradiola fast-signaling neurosteroid vital for neuroprotection that has proven difficult to detect with existing methodsas a model target analyte for optimizing direct electrochemical detection at carbon surfaces. We take a two-pronged approach to optimizing estradiol detection by examining the electrode-analyte interface from the perspective of both the carbon surface and the target molecule. We first establish the surface characteristics of diverse carbon fibers, then examine estradiol's electrochemical behavior at each surface. Finally, we determine the contributions of estradiol's structure to specific adsorption, elucidating subtle structural considerations to analyte-specific tailoring of carbon electrodes. By taking this multi-perspective approach, we develop a thorough understanding of the interactions between carbon sensing surfaces and estradiol for improved sensitivity and selectivity. Moreover, our approach is applicable to other neglected neurochemicals that have proven challenging to detect. This work creates a potentially broadly applicable roadmap for customizing direct monitoring at carbon surfaces through a tailored approach to optimizing the electrode-analyte interface.