摘要
We recognize the stochastic collisions of dopamine contained phospholipid vesicle on carbon fiber nanoelectrode, extending the observation of discrete collision events on nanoelectrode to biologically relevant analytes. To decrease noise interference to the technique, the dimensions of nanoelectrode was systematically investigated and optimized. Scanning electron microscopy(SEM) further supported the comparable sizes of nanoelectrode and vesicles(~100 nm in diameter). Vesicles collision and rupture on the surface of nanoelectrode led to the dopamine release from vesicles, which could be electrochemically oxidized to dopamine-o-quinone and detected via voltammetry. The comparable size of the nanoelectrode with vesicles and fast voltammetry allowed differentiation of single collision events from the current magnitudes and peak widths in the electrochemical collision experiments, which shows the efficacy of the method to characterize vesicle samples. This work provides a foundation upon which quantitative sensor technology might be built for the detection of dopamine contained vesicles with high spatial and temporal resolution.
We recognize the stochastic collisions of dopamine contained phospholipid vesicle on carbon fiber nanoelectrode, extending the observation of discrete collision events on nanoelectrode to biologically relevant analytes. To decrease noise interference to the technique, the dimensions of nanoelectrode was systematically investigated and optimized. Scanning electron microscopy （SEM） further supported the comparable sizes of nanoelectrode and vesicles （-100 nm in diameter）. Vesicles collision and rupture on the surface of nanoelectrode led to the dopamine release from vesicles, which could be electrochemically oxidized to dopamine-o-quinone and detected via voltammetry. The comparable size of the nanoelectrode with vesicles and fast voltammetry allowed differentiation of single collision events from the current magnitudes and peak widths in the electrochemical collision experiments, which shows the efficacy of the method to characterize vesicle samples. This work provides a foundation upon which quantitative sensor technology might be built for the detection of dopamine contained vesicles with high spatial and temporal resolution.
基金
supported by the National Natural Science Foundation of China(21422508,31470960)
Chinese Academy of Sciences
support by the Deanship of Scientific Research,College of Science Research Center at King Saud University
