journal article·2020-08-02Open access

Subretinally injected semiconducting polymer nanoparticles rescue vision in a rat model of retinal dystrophy

José Fernando Maya-Vetencourt, Giovanni Manfredi, Maurizio Mete, Elisabetta Colombo, Mattia Bramini, Stefano Di Marco, Dmytro Shmal, Giulia Mantero, Michele Dipalo, Anna Rocchi, Mattia L. DiFrancesco, Ermanno D. Papaleo, Angela Russo, Jonathan Barsotti, Cyril Eleftheriou, Francesca Di Maria, Vanessa Cossu, Fabio Piazza, Laura Emionite, Flavia Ticconi, Cecilia Marini, Gianmario Sambuceti, Grazia Pertile, Guglielmo Lanzani, Fabio Benfenati

Nature Nanotechnology· Volume 15· Issue 8

Abstract

Inherited retinal dystrophies and late-stage age-related macular degeneration, for which treatments remain limited, are among the most prevalent causes of legal blindness. Retinal prostheses have been developed to stimulate the inner retinal network; however, lack of sensitivity and resolution, and the need for wiring or external cameras, have limited their application. Here we show that conjugated polymer nanoparticles (P3HT NPs) mediate light-evoked stimulation of retinal neurons and persistently rescue visual functions when subretinally injected in a rat model of retinitis pigmentosa. P3HT NPs spread out over the entire subretinal space and promote light-dependent activation of spared inner retinal neurons, recovering subcortical, cortical and behavioural visual responses in the absence of trophic effects or retinal inflammation. By conferring sustained light sensitivity to degenerate retinas after a single injection, and with the potential for high spatial resolution, P3HT NPs provide a new avenue in retinal prosthetics with potential applications not only in retinitis pigmentosa, but also in age-related macular degeneration.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Retinal Development and Disorders · Neuroscience and Neural Engineering · Photoreceptor and optogenetics research

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

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