2022
DOI: 10.1101/2022.08.03.502650
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Neuronal Maturation-dependent Nano-Neuro Interaction and Modulation

Abstract: Nanotechnology-enabled neuromodulation, a rapidly growing technique, is a promising minimally-invasive tool in neuroscience and engineering for both fundamental studies as well as clinical applications. However, the nano-neuro interactions at different stages of maturation of a neural network and its implications on the nano-neuromodulation remain unclear. Here, we report heterogeneous to homogenous transformation of neuromodulation in a progressively maturing neural network. Utilizing plasmonic fluors as ultr… Show more

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Cited by 1 publication
(3 citation statements)
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“…In this study, we harnessed negatively charged plasmonicfluors comprised of IR-650 (called PF-650 henceforth) to demonstrate plasmon-enhanced expansion microscopy. 24 It has been previously reported that negatively charged nanostructures, irrespective of their size, shape, and composition, specifically bind to neurons. 25 Plasmonic-fluor-650 is realized using Au@Ag nanocuboids with an LSPR wavelength at ∼650 nm as a plasmonic nanoantenna (Figure 1B).…”
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“…In this study, we harnessed negatively charged plasmonicfluors comprised of IR-650 (called PF-650 henceforth) to demonstrate plasmon-enhanced expansion microscopy. 24 It has been previously reported that negatively charged nanostructures, irrespective of their size, shape, and composition, specifically bind to neurons. 25 Plasmonic-fluor-650 is realized using Au@Ag nanocuboids with an LSPR wavelength at ∼650 nm as a plasmonic nanoantenna (Figure 1B).…”
mentioning
confidence: 99%
“…24,25 SEM imaging revealed random orientations of PFs on the soma and higher alignment along the length of neurites (Figure 3A). 24 As expected, we observed a bright fluorescence signal from PFs adsorbed on the neuronal cell body and neurites with minimal background, indicating the specific binding of PFs to neurons (Figure 3B). Following the ExM procedure, confocal microscopy images revealed excellent retention of the structural details across a large sample size (∼400 × 200 μm 2 in pre-ExM scale) (Figure 3C,E).…”
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confidence: 99%
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