Automated procedure to detect subtle motor alterations in the balance beam test in a mouse model of early Parkinson's disease.

Parkinson's disease (PD) is the most common motor neurodegenerative disorder, characterised by aggregated α-synuclein (α-syn) constituting Lewy bodies. We aimed to investigate temporal changes in motor impairments in a PD mouse model induced by overexpression of α-syn with the conventional manual analysis of the balance beam test and a novel approach using machine learning algorithms to automate behavioural analysis. We combined automated animal tracking using markerless pose estimation in DeepLabCut, with automated behavioural classification in Simple Behavior Analysis. Our automated procedure was able to detect subtle motor deficits in mouse performances in the balance beam test that the manual analysis approach could not assess. The automated model revealed time-course significant differences for the "walking" behaviour in the mean interval between each behavioural bout, the median event bout duration and the classifier probability of occurrence in male PD mice, even though no statistically significant loss of tyrosine hydroxylase in the nigrostriatal system was found in either sex. These findings are valuable for early detection of motor impairment in early PD animal models. We provide a user-friendly, step-by-step guide for automated assessment of mouse performances in the balance beam test, which aims to be replicable without any significant computational and programming knowledge.

Efficacy of invasive and non-invasive methods for the treatment of Parkinson's disease: Nanodelivery and enriched environment.

Parkinson's disease (PD) is the second most common neurodegenerative disorder characterised by the loss of dopaminergic neurons in the substantia nigra pars compacta and the subsequent motor disability. The most frequently used treatments in clinics, such as L-DOPA, restore dopaminergic neurotransmission in the brain. However, these treatments are only symptomatic, have temporary efficacy, and produce side effects. Part of the side effects are related to the route of administration as the consumption of oral tablets leads to unspecific pulsatile activation of dopaminergic receptors. For this reason, it is necessary to not only find alternative treatments, but also to develop new administration systems with better security profiles. Nanoparticle delivery systems are new administration forms designed to reach the pharmacological target in a highly specific way, leading to better drug bioavailability, efficacy and safety. Some of these delivery systems have shown promising results in animal models of PD not only when dopaminergic drugs are administered, but even more when neurotrophic factors are released. These latter compounds promote maturation and survival of dopaminergic neurons and can be exogenously administered in the form of pharmacological therapy or endogenously generated by non-pharmacological methods. In this sense, experimental exposure to enriched environments, a non-invasive strategy based on the combination of social and inanimate stimuli, enhances the production of neurotrophic factors and produces a neuroprotective effect in parkinsonian animals. In this review, we will discuss new nanodelivery systems in PD with a special focus on therapies that increase the release of neurotrophic factors.