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Estimating the modulatory effects of nanoparticles on neuronal circuits using computational upscaling

Authors Busse M, Stevens D, Kraegeloh A, Cavelius C, Vukelic M, Arzt E, Strauss DJ

Received 5 February 2013

Accepted for publication 1 March 2013

Published 19 September 2013 Volume 2013:8(1) Pages 3559—3572

DOI https://doi.org/10.2147/IJN.S43663

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Michael Busse,1 David Stevens,3 Annette Kraegeloh,2 Christian Cavelius,2 Mathias Vukelic,1 Eduard Arzt,2 Daniel J Strauss1,2

1Systems Neuroscience and Neurotechnology Unit, Saarland University, Faculty of Medicine, Neurocenter, and Saarland University of Applied Sciences, Homburg/Saarbruecken, Germany; 2Leibniz Institute for New Materials, Saarbruecken, Germany; 3Department of Physiology, Saarland University, Faculty of Medicine, Homburg/Saarbruecken, Germany

Background: Beside the promising application potential of nanotechnologies in engineering, the use of nanomaterials in medicine is growing. New therapies employing innovative nanocarrier systems to increase specificity and efficacy of drug delivery schemes are already in clinical trials. However the influence of the nanoparticles themselves is still unknown in medical applications, especially for complex interactions in neural systems. The aim of this study was to investigate in vitro effects of coated silver nanoparticles (cAgNP) on the excitability of single neuronal cells and to integrate those findings into an in silico model to predict possible effects on neuronal circuits.
Methods: We first performed patch clamp measurements to investigate the effects of nanosized silver particles, surrounded by an organic coating, on excitability of single cells. We then determined which parameters were altered by exposure to those nanoparticles using the Hodgkin–Huxley model of the sodium current. As a third step, we integrated those findings into a well-defined neuronal circuit of thalamocortical interactions to predict possible changes in network signaling due to the applied cAgNP, in silico.
Results: We observed rapid suppression of sodium currents after exposure to cAgNP in our in vitro recordings. In numerical simulations of sodium currents we identified the parameters likely affected by cAgNP. We then examined the effects of such changes on the activity of networks. In silico network modeling indicated effects of local cAgNP application on firing patterns in all neurons in the circuit.
Conclusion: Our sodium current simulation shows that suppression of sodium currents by cAgNP results primarily by a reduction in the amplitude of the current. The network simulation shows that locally cAgNP-induced changes result in changes in network activity in the entire network, indicating that local application of cAgNP may influence the activity throughout the network.

Keywords: coated silver nanoparticles, modeling, patch clamp recordings, neuronal circuit model, neuromodulatory effect, nanocarriers, nonviral vectors, Llinás model

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