SCIENTIFIC HUB

Follow the evidence.

SCIENTIFIC LITERATURE · MED

Adaptive preconditioning in neurological diseases - therapeutic insights from proteostatic perturbations.

Brain Res · 2016-03-02

DOI: 10.1016/j.brainres.2016.02.033PMID: 26923166

Open accessResearch Support, Non-U.S. Gov't; review-article; Review; Journal Article; Research Support, N.I.H., ExtramuralOriginal source ↗

Research overview

The text below is the source article’s original abstract under a verified reuse license. cc by

In neurological disorders, both acute and chronic neural stress can disrupt cellular proteostasis, resulting in the generation of pathological protein. However in most cases, neurons adapt to these proteostatic perturbations by activating a range of cellular protective and repair responses, thus maintaining cell function. These interconnected adaptive mechanisms comprise a 'proteostasis network' and include the unfolded protein response, the ubiquitin proteasome system and autophagy. Interestingly, several recent studies have shown that these adaptive responses can be stimulated by preconditioning treatments, which confer resistance to a subsequent toxic challenge - the phenomenon known as hormesis. In this review we discuss the impact of adaptive stress responses stimulated in diverse human neuropathologies including Parkinson׳s disease, Wolfram syndrome, brain ischemia, and brain cancer. Further, we examine how these responses and the molecular pathways they recruit might be exploited for therapeutic gain. This article is part of a Special Issue entitled SI:ER stress.

Scientific assessment

01

Research question

Assess the question within the original study’s scope.

02

Methods & sample

Check the source article for study design and sample details.

03

Key findings

An editorially approved findings summary is not yet published for this record.

04

Limitations

Generalizability, bias and clinical meaning require separate assessment.

Methods, samples and clinical conclusions are not inferred from bibliographic metadata.