Here, we have synthesized and characterized graphene-fiber microelectrodes (GFME's) for subsecond detection of neurochemicals with fast-scan cyclic voltammetry (FSCV) for the first time. GFME's exhibited extraordinary properties including faster electron transfer kinetics, significantly improved sensitivity, and ease of tunability that we anticipate will have major impacts on neurochemical detection for years to come. GF's have been used in the literature for various applications; however, scaling their size down to microelectrodes and implementing them as neurochemical microsensors is significantly less developed. The GF's developed in this paper were on average 20−30 μm in diameter and both graphene oxide (GO) and reduced graphene oxide (rGO) fibers were characterized with FSCV. Neat GF's were synthesized using a one-step dimension-confined hydrothermal strategy. FSCV detection has traditionally used carbon-fiber microelectrodes (CFME's) and more recently carbon nanotube fiber electrodes; however, uniform functionalization and direct control of the 3D surface structure of these materials remain limited. The expansion to GFME's will certainly open new avenues for fine-tuning the electrode surface for specific electrochemical detection. When comparing to traditional CFME's, our GFME's exhibited significant increases in electron transfer, redox cycling, fouling resistance, higher sensitivity, and frequency independent behavior which demonstrates their incredible utility as biological sensors.

We have developed a sensitive and stable electrochemical method for 17β‐estradiol (E2) detection using fast‐scan cyclic voltammetry (FSCV). Recently, E2 was proposed to function as a rapid synaptocrine signaling molecule in the brain; however, methods to directly monitor subsecond fluctuations in E2 are currently unavailable, limiting our understanding of the dynamics and mechanism of rapid E2 release. FSCV at carbon‐fiber microelectrodes enables subsecond detection of electroactive neurochemicals directly in tissues like the brain. Here, we have electrochemically characterized E2 using FSCV for use in a tissue matrix. The limit of detection of E2 is 31.2±2.5 nM with FSCV, which will enable low nanomolar fluctuations in extracellular E2 to be monitored with hundred millisecond temporal resolution. We also identify specific parameters for waveform modification to improve future detection. This method will significantly improve E2 sensing capabilities and will have far‐reaching impacts on improving our understanding of dynamic E2 signaling in the brain.

Small molecules and signaling peptides are extensively involved in controlling basic brain function. While classical neurotransmitters can be detected with a variety of techniques, methods for measurement of rapidly-released neuropeptides remain underdeveloped. Fast-scan cyclic voltammetry (FSCV) is an electrochemical technique often used for subsecond detection of small molecule neurotransmitters, in vivo. A few peptides have been detected with FSCV; however, a detailed analysis of the electrochemical signature of all electroactive amino acids with FSCV has not been fully investigated. Because the mechanisms, locations, and timescales for signaling peptide release in the brain are relatively unexplored, developing sensitive and selective tools capable of quantitating neuropeptide signaling is essential. To bridge this gap, we used FSCV to characterize the electroactive amino acids: cysteine, methionine, histidine, tryptophan, and tyrosine. We show that tyrosine, tryptophan, and histidine are easily oxidized on carbon fiber surfaces with FSCV, while detection of the sulfur-containing amino acids is more difficult. This study provides critical information for electrochemical waveform design and optimization for detection of peptides containing these amino acids.

Guanosine acts in both neuroprotective and neurosignaling pathways in the central nervous system; in this paper, we present the first fast voltammetric measurements of endogenous guanosine release during pre-and post-ischemic conditions. We discuss the metric of our measurements via analysis of event concentration, duration, and interevent time of rapid guanosine release. We observe changes across all three metrics from our normoxic to ischemic conditions. Pharmacological studies were performed to confirm that guanosine release is a calcium-dependent process and that the signaling observed is purinergic. Finally, we show the validity of our ischemic model via staining and fluorescent imaging. Overall, this paper sets the tone for rapid monitoring of guanosine and provides a platform to investigate the extent to which guanosine accumulates at the site of brain injury, i.e., ischemia.