Preclinical and clinical study on type 3 metabotropic glutamate receptors in Parkinson's disease.

Metabotropic glutamate (mGlu) receptors are candidate drug targets for therapeutic intervention in Parkinson's disease (PD). Here we focused on mGlu3, a receptor subtype involved in synaptic regulation and neuroinflammation. mGlu3 mice showed an enhanced nigro-striatal damage and microglial activation in response to 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP).

Association of Early fMRI Connectivity Alterations With Different Cognitive Phenotypes in Patients With Newly Diagnosed Parkinson Disease.

Background And Objectives: According to the dual syndrome hypothesis, patients with Parkinson disease (PD) with visuospatial deficits are more likely to progress to dementia, compared with patients with a prevalent dysexecutive syndrome. In this study, we aimed to investigate whether early connectivity changes in the dorsolateral prefrontal cortex (DLPFC) and the precuneus (PCun)-which are critical to fronto-executive and visuospatial functions, respectively-can identify distinct cognitive phenotypes in cognitively intact newly diagnosed patients with PD.

Methods: Newly diagnosed, drug-naïve patients with PD (≤2 years from clinical onset) with normal Montreal Cognitive Assessment (MoCA), were consecutively enrolled from our Movement Disorders Clinics in Italy.

Neurophysiological Features of Tremor during Walking in Parkinson's Disease.

Background: In Parkinson's Disease (PD), upper limb tremor during walking (TW) is observed and clinical observations suggest it may represent a variant of rest tremor. However, its neurophysiological characteristics remain unexplored.

Objectives: This study compared the neurophysiological features of TW with other PD tremors and tested whether TW arises from reduced ipsilateral arm swing.

Computational framework for the generation of one-dimensional vascular models accounting for uncertainty in networks extracted from medical images.

One-dimensional (1D) cardiovascular models offer a non-invasive method to answer medical questions, including predictions of wave-reflection, shear stress, functional flow reserve, vascular resistance and compliance. This model type can predict patient-specific outcomes by solving 1D fluid dynamics equations in geometric networks extracted from medical images. However, the inherent uncertainty in in vivo imaging introduces variability in network size and vessel dimensions, affecting haemodynamic predictions.