scholarly journals Neurofilament Light (NF-L) Chain Protein from a Highly Polymerized Structural Component of the Neuronal Cytoskeleton to a Neurodegenerative Disease Biomarker in the Periphery

2021 ◽  
Vol 7 (2) ◽  
pp. 1-9
Author(s):  
Walter J Lukiw
2014 ◽  
Vol 54 (1) ◽  
pp. 457-481 ◽  
Author(s):  
Christopher Lausted ◽  
Inyoul Lee ◽  
Yong Zhou ◽  
Shizhen Qin ◽  
Jaeyun Sung ◽  
...  

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Thom S. Lysen ◽  
M. Arfan Ikram ◽  
Mohsen Ghanbari ◽  
Annemarie I. Luik

AbstractSleep and 24-h activity rhythm disturbances are associated with development of neurodegenerative diseases and related pathophysiological processes in the brain. We determined the cross-sectional relation of sleep and 24-h activity rhythm disturbances with plasma-based biomarkers that might signal neurodegenerative disease, in 4712 middle-aged and elderly non-demented persons. Sleep and activity rhythms were measured using the Pittsburgh Sleep Quality Index and actigraphy. Simoa assays were used to measure plasma levels of neurofilament light chain, and additionally β-amyloid 40, β-amyloid 42, and total-tau. We used linear regression, adjusting for relevant confounders, and corrected for multiple testing. We found no associations of self-rated sleep, actigraphy-estimated sleep and 24-h activity rhythms with neurofilament light chain after confounder adjustment and correction for multiple testing, except for a non-linear association of self-rated time in bed with neurofilament light chain (P = 2.5*10−4). Similarly, we observed no significant associations with β-amyloid 40, β-amyloid 42, and total-tau after multiple testing correction. We conclude that sleep and 24-h activity rhythm disturbances were not consistently associated with neuronal damage as indicated by plasma neurofilament light chain in this population-based sample middle-aged and elderly non-demented persons. Further studies are needed to determine the associations of sleep and 24-h activity rhythm disturbances with NfL-related neuronal damage.


2018 ◽  
Vol 307 ◽  
pp. 129-132 ◽  
Author(s):  
Cristina Meregalli ◽  
Giulia Fumagalli ◽  
Paola Alberti ◽  
Annalisa Canta ◽  
Valentina Alda Carozzi ◽  
...  

The Analyst ◽  
2014 ◽  
Vol 139 (11) ◽  
pp. 2823-2831 ◽  
Author(s):  
Jose O. Esteves-Villanueva ◽  
Hanna Trzeciakiewicz ◽  
Sanela Martic

Tau–tau binding induced electrostatic and conformational changes on the surface modulating the charge transfer resistance.


Author(s):  
P. Gambetti ◽  
G. Perry ◽  
L. Autillo-Gambetti

Neurofibrillary tangles (NFT) are one of the major pathologic lesions of Alzheimer's disease. These neuronal inclusions are predominantly composed of paired helical filaments (PHF), which consist of two 10 nm filaments winding around each other with an approximately 80 nm periodicity. Besides PHF, NFT comprise also 15 nm filaments, 10 nm filaments which are probably neurofilaments, microtubules and granular material. At variance with the neuronal cytoskeleton, PHF are insoluble in ionic detergent.Studies at the light microscope level have shown that NFT have unique antigenic determinants as well as determinants in common with elements of the normal neuronal cytoskeleton such as neurofilaments and microtubule-associated proteins. The present study uses immunocytochemistry and cytochemistry at the electron microscope level to assess which NFT component contains these determinants and whether these antigenic determinants are soluble in an ionic detergent.


2006 ◽  
Vol 11 (4) ◽  
pp. 304-311 ◽  
Author(s):  
Lars-Göran Nilsson

This paper presents four domains of markers that have been found to predict later cognitive impairment and neurodegenerative disease. These four domains are (1) data patterns of memory performance, (2) cardiovascular factors, (3) genetic markers, and (4) brain activity. The critical features of each domain are illustrated with data from the longitudinal Betula Study on memory, aging, and health ( Nilsson et al., 1997 ; Nilsson et al., 2004 ). Up to now, early signs regarding these domains have been examined one by one and it has been found that they are associated with later cognitive impairment and neurodegenerative disease. However, it was also found that each marker accounts for only a very small part of the total variance, implying that single markers should not be used as predictors for cognitive decline or neurodegenerative disease. It is discussed whether modeling and simulations should be used as tools to combine markers at different levels to increase the amount of explained variance.


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