Characterization of an automated method to segment the human locus coeruleus.

Following the development of magnetic resonance imaging (MRI) methods to assay the integrity of catecholamine nuclei, including the locus coeruleus (LC), there has been an effort to develop automated methods that can accurately segment this small structure in an automated manner to promote its widespread use and overcome limitations of manual segmentation. Here we characterize an automated LC segmentation approach (referred to as the funnel-tip [FT] method) in healthy individuals and individuals with LC degeneration in the context of Alzheimer's disease (AD, confirmed with tau-PET imaging using [18F]MK6240). The first sample included n = 190 individuals across the AD spectrum from cognitively normal to moderate AD.

Glycomic and Glycoproteomic Techniques in Neurodegenerative Disorders and Neurotrauma: Towards Personalized Markers.

The proteome represents all the proteins expressed by a genome, a cell, a tissue, or an organism at any given time under defined physiological or pathological circumstances. Proteomic analysis has provided unparalleled opportunities for the discovery of expression patterns of proteins in a biological system, yielding precise and inclusive data about the system. Advances in the proteomics field opened the door to wider knowledge of the mechanisms underlying various post-translational modifications (PTMs) of proteins, including glycosylation.

A Probabilistic Programming Approach to Protein Structure Superposition.

Optimal superposition of protein structures or other biological molecules is crucial for understanding their structure, function, dynamics and evolution. Here, we investigate the use of probabilistic programming to superimpose protein structures guided by a Bayesian model. Our model THESEUS-PP is based on the THESEUS model, a probabilistic model of protein superposition based on rotation, translation and perturbation of an underlying, latent mean structure.