BACKGROUND/AIMS: Alpha synuclein (αSN) is a widely distributed protein in vertebrates whose physiological significance in many tissues remains unclear, being a key protein present in neurodegenerative disease such as Parkinson's Disease, Lewy Body Dementia, and in Sporadic-Inclusion Body Myositis. We search for αSN in skeletal muscle (SM) and neuronal plasma membrane isolated from brain (BR) from young and old rats. METHODS: In isolated Sarcolemma from SM and from myelin-free neuronal plasma membrane isolated from BR, we determine by Western blot with anti-αSN (2B2D1) and anti-P-αSN (EP1536Y) the αSN membrane distribution, and the SM αSN intra and extracellular localization. RESULTS: In SM and BR, αSN is present in cytosol (CYT) as monomer and oligomer structures mainly tetramers (TM) and in plasma membranes as oligomers (TM and PM). All αSN oligomers were localized in non-lipid rafts and their distribution was unaffected by cholesterol-depletion with Methyl-β-Cyclodextrin. Membranes with natively high cholesterol content such as Transverse Tubules in SM and myelin in BR, reduce the presence of αSN. Under the same experimental conditions, aged SM and BR plasma membranes show ≈2 folds more αSN. In SM, αSN is extruded without cell damage in young and old rats. CONCLUSION: We conclude that oligomeric αSN are regularly present in SM and BR plasma membranes of healthy young and old rats. Interestingly, low-cholesterol content membranes promote αSN interaction. SM, the largest tissue in vertebrate body is a source of αSN and may contribute to the presence of αSN in extracellular fluids.
Covariance analysis from wavelet data in electroencephalographic records (EEG) was, for the first time, applied in this study to unravel information contained in the standard EEG, which was previously not taken into consideration due to the mathematical models used. The methodology discussed here could be applied to any neurological condition, including the important early stages of neurodegenerative diseases. In this study, we analyzed EEG from control (CL) participants and participants with diagnosed Parkinson’s disease (PD), who were age-matched women in an eyes-closed resting state, to test the model. PD is predicted to rise over the next decades as the population ages. Furthermore, women are more likely to undergo PD-related complications and worse disability than men. Two groups based on age were considered: under and over 60 years (PD patients <60 and >60; CL <60 and >60). Continuous Wavelet Transform and Cross Wavelet Transform were applied to determine patterns of global wavelet curves, main frequencies, and power analyses. Our results indicate that both CL age groups and PD patients <60 share a main a brainwave and PD patients >60 showed a main δ brainwave. Interestingly, power anomalies analyses show a decreasing anteroposterior gradient in CL, whereas it is increasing in PD patients, which was not previously observed. The brainwave power in PD patients <60 was higher in θ, α and β waves and in >60 group, the δ, θ and β brainwaves were predominant. This methodology offers a tool to reveal abnormal electrical brain activity unseen by a regular EEG analysis. The advent of new models that process EEG, such as the model proposed in this study, promotes renewed interest in electrophysiology of the brain to study the early stages of PD and improve understanding of the origin and progress of the disease.
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