Understanding the potential of nanomaterials (NMs) to cross the blood-brain barrier (BBB), as a function of their physicochemical properties and subsequent behavior, fate, and adverse effect beyond that point, is vital for evaluating the neurological effects arising from their unintentional entry into the brain, which is yet to be fully explored. This is not only due to the complex nature of the brain but also the existing analytical limitations for characterization and quantification of NMs in the complex brain environment. By using a fit-for-purpose analytical workflow and an in vitro BBB model, we show that the physiochemical properties of metallic NMs influence their biotransformation in biological matrices, which in turn modulates the transport form, efficiency, amounts, and pathways of NMs through the BBB and, consequently, their neurotoxicity. The data presented here will support in silico modeling and prediction of the neurotoxicity of NMs and facilitate the tailored design of safe NMs.

Biotransformation modulates the penetration of metallic nanomaterials across an artificial blood-brain barrier model

Abdolahpur Monikh, Fazel;
2021

Abstract

Understanding the potential of nanomaterials (NMs) to cross the blood-brain barrier (BBB), as a function of their physicochemical properties and subsequent behavior, fate, and adverse effect beyond that point, is vital for evaluating the neurological effects arising from their unintentional entry into the brain, which is yet to be fully explored. This is not only due to the complex nature of the brain but also the existing analytical limitations for characterization and quantification of NMs in the complex brain environment. By using a fit-for-purpose analytical workflow and an in vitro BBB model, we show that the physiochemical properties of metallic NMs influence their biotransformation in biological matrices, which in turn modulates the transport form, efficiency, amounts, and pathways of NMs through the BBB and, consequently, their neurotoxicity. The data presented here will support in silico modeling and prediction of the neurotoxicity of NMs and facilitate the tailored design of safe NMs.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3467421
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