journal article·2009-10Open access

The inhibition of neuronal calcium ion channels by trace levels of yttrium released from carbon nanotubes

Lorin M. Jakubek, Spiro Marangoudakis, Jesica Raingo, Xinyuan Liu, Diane Lipscombe, Robert H. Hurt

Biomaterials· Volume 30· Issue 31

Abstract

Carbon nanotubes (CNTs) are used with increasing frequency in neuroengineering applications. CNT scaffolds are used to transmit electrical stimulation to cultured neurons and to control outgrowth and branching patterns of neurites. CNTs have been reported to disrupt normal neuronal function including alterations in endocytotic capability and inhibition of ion channels. Calcium ion channels regulate numerous neuronal and cellular functions including endo and exocytosis, neurite outgrowth, and gene expression. Strong CNT interactions with neuronal calcium ion channels would have profound biological implications. Here we show that physiological solutions containing CNTs inhibit neuronal voltage-gated calcium ion channels in a dose-dependent and CNT sample-dependent manner with IC50 as low as 1.2 microg/ml. Importantly, we demonstrate that the inhibitory activity does not involve tubular graphene as previously reported, but rather very low concentrations of soluble yttrium released from the nanotube growth catalyst. Cationic yttrium potently inhibits calcium ion channel function with an inhibitory efficacy, IC50, of 0.07 ppm w/w. Because of this potency, unpurified and even some reportedly "purified" CNT samples contain sufficient bioavailable yttrium to inhibit channel function. Our results have important implications for emerging nano-neurotechnology and highlight the critical role that trace components can play in the biological response to complex nanomaterials.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Neuroscience and Neural Engineering · Carbon Nanotubes in Composites · Anesthesia and Neurotoxicity Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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