Network dynamical stability analysis reveals key 'mallostatic' natural variables that erode homeostasis and drive age-related decline of health

Autor: Glen Pridham, Andrew D. Rutenberg

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023)

Abstract Using longitudinal study data, we dynamically model how aging affects homeostasis in both mice and humans. We operationalize homeostasis as a multivariate mean-reverting stochastic process. We hypothesize that biomarkers have stable equilibr

Externí odkaz: https://doaj.org/article/4a27806a9efb4236b17654a8243f8850

A metric learning method for estimating myelin content based on T2-weighted MRI from a de- and re-myelination model of multiple sclerosis.

Autor: Glen Pridham, Shahnewaz Hossain, Khalil S Rawji, Yunyan Zhang

Publikováno v: PLoS ONE, Vol 16, Iss 4, p e0249460 (2021)

Myelin plays a critical role in the pathogenesis of neurological disorders but is difficult to characterize in vivo using standard analysis methods. Our goal was to develop a novel analytical framework for estimating myelin content using T2-weighted

Externí odkaz: https://doaj.org/article/8838c8bbfa5e4312b207cd747997c5f6

Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis

Autor: Zahra Hosseinpour, Laura Jonkman, Olayinka Oladosu, Glen Pridham, G. Bruce Pike, Matilde Inglese, Jeroen J. Geurts, Yunyan Zhang

Publikováno v: Journal of Neuroscience Methods, 379:109671. Elsevier
Hosseinpour, Z, Jonkman, L, Oladosu, O, Pridham, G, Pike, G B, Inglese, M, Geurts, J J & Zhang, Y 2022, ' Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis ', Journal of Neuroscience Methods, vol. 379, 109671 . https://doi.org/10.1016/j.jneumeth.2022.109671
Hosseinpour, Z, Jonkman, L, Oladosu, O, Pridham, G, Pike, G B, Inglese, M, Geurts, J J & Zhang, Y 2022, ' Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis ', Journal of Neuroscience Methods, vol. 379, 109671, pp. 1-11 . https://doi.org/10.1016/j.jneumeth.2022.109671
Journal of Neuroscience Methods, 379:109671, 1-11. Elsevier

© 2022 Elsevier B.V.Background: Multiple sclerosis (MS) is a complex disease of the central nervous system involving several types of brain pathology that are difficult to characterize using conventional imaging methods. New method: We originated no

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b3b5c12aa1aa2fdcc7aeebc86ee1d4c
https://research.vumc.nl/en/publications/1ddafaed-5cfc-4f77-a591-9e08b26355da

Strategies for handling missing data that improve Frailty Index estimation and predictive power: lessons from the NHANES dataset

Autor: Glen Pridham, Kenneth Rockwood, Andrew Rutenberg

Publikováno v: GeroScience

Missing data are ubiquitous in aging studies. Combining the National Health and Nutrition Examination Survey (NHANES) 2003/2004 and 2005/2006 cross-sectional aging studies (N = 9307), we investigated the effects of both real and simulated missing dat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::964072ae026a145a06e0e620d0b5b63d
https://pubmed.ncbi.nlm.nih.gov/35103915

Characterizing Structural Changes With Evolving Remyelination Following Experimental Demyelination Using High Angular Resolution Diffusion MRI and Texture Analysis

Autor: Olayinka Oladosu, Glen Pridham, Tim Luo, Khalil S. Rawji, Yunyan Zhang, Peng Zhai, Shahnewaz Hossain

Publikováno v: Journal of Magnetic Resonance Imaging. 49:1750-1759

Changes in myelin integrity are associated with the pathophysiology of many neurological diseases, including multiple sclerosis. However, noninvasive measurement of myelin injury and repair remains challenging. Advanced MRI techniques including diffu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::78f4472cacb9fc17286842d18a568000
https://doi.org/10.1002/jmri.26328