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Microprofiling real time nitric oxide flux for field studies using a stratified nanohybrid carbon-metal electrode

Abstract

Nitric oxide (NO) is an important signaling molecule that is involved in stress response, homeostasis, host defense, and cell development. In most cells, NO levels are in the femtomolar to micromolar range, with extracellular concentrations being much lower. Thus, real time measurement of spatiotemporal NO dynamics near the surface of living cells/tissues is a major challenge. Here, we report the development, application, and validation of a self referencing (i.e., oscillating) NO microelectrode based on a hybrid nanomaterial composed of nanoceria, reduced graphene oxide and nanoplatinum. The sensitivity (0.95 ± 0.03 pA nM-1), response time (1.1 ± 0.1 sec), operating potential (+720 mV), and selectivity of the nanomaterial-modified microelectrode are improvements over previous microelectrode designs, enabling studies of NO flux using the self referencing (SR) microelectrode modality. NO efflux was first measured from chitosan and alginate polymers in abiotic studies, and a deterministic model used to determine the effective diffusion coefficient for each polymer composite. Next, NO flux was quantified in three model organisms with known NO pathways, including: bacteria, plant, and an invertebrate animal. For each organism, an established hypothesis was validated based on NO flux measurement and the results confirm data collected using standard analytical techniques. The sensor can be used to expand our fundamental knowledge of NO transport by facilitating field experiments which are not possible with standard techniques.

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Supplementary files

Publication details

The article was received on 14 Aug 2017, accepted on 11 Oct 2017 and first published on 12 Oct 2017


Article type: Paper
DOI: 10.1039/C7AY01964E
Citation: Anal. Methods, 2017, Accepted Manuscript
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    Microprofiling real time nitric oxide flux for field studies using a stratified nanohybrid carbon-metal electrode

    P. Chaturvedi, D. C. Vanegas, B. A. Hauser, J. S. Foster, M. S. Sepulveda and E. S. McLamore, Anal. Methods, 2017, Accepted Manuscript , DOI: 10.1039/C7AY01964E

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