Results 151 to 160 of about 928,578 (204)

Altered Cerebrospinal Fluid Tryptophan–Kynurenine Pathway Metabolism in Multiple System Atrophy

open access: yesMovement Disorders, EarlyView.
Abstract Background Alterations in tryptophan–kynurenine (TRP‐KYN) metabolism, which is associated with neuroinflammation, remain unclear in multiple system atrophy (MSA). Objective The aim was to investigate cerebrospinal fluid (CSF) TRP metabolites in MSA and their associations with other biomarkers.
Ryunosuke Nagao   +8 more
wiley   +1 more source

Plasma p‐tau217 Versus p‐tau181 in Parkinson's Disease: Differential Associations with Alzheimer's Disease‐Related Neurostructural Changes and Cognitive Function

open access: yesMovement Disorders, EarlyView.
Abstract Background Plasma phosphorylated‐tau at threonine‐217 (p‐tau217) and threonine‐181 (p‐tau181) are scalable, minimally invasive biomarkers of Alzheimer's disease (AD) pathology. In Parkinson's disease (PD), AD co‐pathology may contribute to its clinical heterogeneity.
Eleonora Fiorenzato   +16 more
wiley   +1 more source

Melanopsin‐Mediated Post‐Illumination Pupillary Response in Idiopathic Rapid Eye Movement (REM) Sleep Behavior Disorder and Parkinson's Disease

open access: yesMovement Disorders, EarlyView.
Abstract Aims To conduct a case–control study to investigate melanopsin‐mediated post‐illumination pupillary response (PIPR) in patients with Parkinson's disease (PD), video‐polysomnography‐confirmed isolated/idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD), and age‐matched healthy controls (HC). Methods PIPR was measured at 6 s after
Joey W.Y. Chan   +16 more
wiley   +1 more source

High‐Fat Diet Exacerbates Neuropathology in a Transgenic Mouse Model of Multiple System Atrophy

open access: yesMovement Disorders, EarlyView.
Abstract Background Multiple system atrophy (MSA) is a rare and devastating neurodegenerative disorder. Accumulating clinical and preclinical evidence suggests that diabetes and insulin resistance may adversely influence MSA pathophysiology. Objective We investigated the potential association between diabetes, impaired glucose homeostasis, and MSA ...
Marie‐Laure Arotcarena   +7 more
wiley   +1 more source

Neuropsychiatric‐Led Presentation of Late‐Onset Parkin‐Related Parkinson's Disease

open access: yes
Movement Disorders Clinical Practice, EarlyView.
Sarah Fullam   +4 more
wiley   +1 more source

COVID‐19 Amplifies Sex‐Specific Dopamine and Glial Responses in a Parkinson's Disease Mouse Model

open access: yesMovement Disorders, EarlyView.
Abstract Background Exposure to environmental agents, including viral infections, may increase Parkinson's disease (PD) susceptibility, especially in males, but the neurodegenerative risk extent of COVID‐19 remains uncertain. Objectives We investigated the plausible link between severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection and
Ifeoluwa Awogbindin   +10 more
wiley   +1 more source

Early‐Onset Parkinson's Disease with 22q11.2 Microdeletion and Pathogenic GBA1 Variant

open access: yes
Movement Disorders Clinical Practice, EarlyView.
Nikolai Gil D. Reyes   +8 more
wiley   +1 more source

Apathy in Lewy Body Disorders: A Position Paper

open access: yesMovement Disorders, EarlyView.
Abstract Apathy is one of the most prevalent and disabling non‐motor symptoms in Parkinson's disease (PD) and dementia with Lewy bodies (DLB), collectively referred to as Lewy body disorders (LBDs). It is associated with reduced quality of life, accelerated cognitive decline, increased caregiver burden, and poorer functional outcomes, yet remains ...
Jaime Kulisevsky   +12 more
wiley   +1 more source

Levodopa and Melanoma: Practical Recommendations for Parkinson's Disease—International Parkinson and Movement Disorder Society Scientific Issues Committee Viewpoint

open access: yes
Movement Disorders Clinical Practice, EarlyView.
Giorgia Sciacca   +27 more
wiley   +1 more source

Parkinson's Disease and Retinal Age Gap: A Cross‐Sectional Analysis

open access: yesMovement Disorders, EarlyView.
Abstract Background Deep‐learning models are capable of predicting age from retinal scans and the difference between this and chronological age, retinal age gap, has been shown to be significantly associated with risk of mortality, cardiovascular diseases, and kidney failure.
Akshay Narayan   +9 more
wiley   +1 more source

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