scispace - formally typeset
I

Ines Trigo-Damas

Researcher at CEU San Pablo University

Publications -  18
Citations -  952

Ines Trigo-Damas is an academic researcher from CEU San Pablo University. The author has contributed to research in topics: Parkinson's disease & Medicine. The author has an hindex of 6, co-authored 13 publications receiving 674 citations. Previous affiliations of Ines Trigo-Damas include University of Navarra & Carlos III Health Institute.

Papers
More filters
Journal ArticleDOI

Oxidative stress and Parkinson’s disease

TL;DR: A mini review of the classical pathways involving these mechanisms of neurodegeneration, the biochemical and molecular events that mediate or regulate DA neuronal vulnerability, and the role of PD-related gene products in modulating cellular responses to oxidative stress in the course of the Neurodegenerative process are given.
Journal ArticleDOI

Compensatory mechanisms in Parkinson's disease: Circuits adaptations and role in disease modification

TL;DR: The evidence for the role of the best known and other possible compensatory mechanisms in PD are reviewed and the possibility that, although beneficial in practical terms, compensation could also play a deleterious role in disease progression is discussed.
Journal ArticleDOI

Advances in Parkinson's Disease: 200 Years Later.

TL;DR: Some of the key advances in the field over the past two centuries are highlighted and the current challenges focusing on exciting new research developments likely to come in the next few years are discussed.
Journal ArticleDOI

The use of nonhuman primate models to understand processes in Parkinson's disease.

TL;DR: How the findings from nonhuman primate research contribute to the understanding of idiopathic Parkinson’s disease is discussed and highlighted.
Journal ArticleDOI

Novel models for Parkinson's disease and their impact on future drug discovery.

TL;DR: The authors provide an outline of the various traditional models of Parkinson's disease and address those that have been recently generated, and discuss the utility of these models for the identification of drugs of potential therapeutic value for Parkinson´s Disease patients.