Search bioRxivSearch

Biology subjects

Shaw, T.

Publications and source records attributed to Shaw, T..

2 recordsLinked to original sources

More Highly Myelinated White Matter Tracts are Associated with Faster Processing Speed in Healthy Adults

The objective of this study was to investigate whether the myelin content of white matter tracts is predictive of cogni-tive processing speed and whether such associations are modulated by age. Associations between myelin content and processing speed was assessed in 570 community-living individuals (277 middle-age, 293 older-age). Myelin content was measured using the mean T1w/T2w magnetic resonance ratio, in six white matter tracts (anterior corona radiata, superior corona radiata, pontine crossing tract, anterior limb of the internal capsule, genu of the corpus callosum, and splenium of the corpus callosum). Processing speed was estimated by extracting a principal component from 5 sep-arate tests of processing speed. It was found that myelin content of the bilateral anterior limb of the internal capsule and left splenium of the corpus callosum were significant predictors of processing speed, even after controlling for socio-demographic, health and genetic variables and correcting for multiple comparisons. A 1 SD increase in the myelin content of the anterior limb of the internal capsule was associated with 2.53% increase in processing speed and within the left splenium of the corpus callosum with a 2.20% increase in processing speed. In addition, significant differences in myelin content between middle-age and older participants were found in all six white matter tracts. The present results indicate that myelin content, estimated in vivo using a neuroimaging approach in healthy older adults is sufficiently precise to predict variability in processing speed in behavioural measures.

neuroscience

Metabolome Identification by Systematic Stable Isotope Labeling Experiments and False Discovery Analysis with a Target-Decoy Strategy

We introduce a formula-based strategy and algorithm (JUMPm) for global metabolite identification and false discovery analysis in untargeted mass spectrometry-based metabolomics. JUMPm determines the chemical formulas of metabolites from unlabeled and stable-isotope labeled metabolome data, and derives the most likely metabolite identity by searching structure databases. JUMPm also estimates the false discovery rate (FDR) with a target-decoy strategy based on the octet rule of chemistry. With systematic stable isotope labeling of yeast, we identified 2,085 chemical formulas (10% FDR), 892 of which were assigned with metabolite structures. We evaluated JUMPm with a library of synthetic standards, and found that 96% of the formulas were correctly identified. We extended the method to mammalian cells with direct isotope labeling and by heavy yeast spike-in. This strategy and algorithm provide a powerful a practical solution for global identification of metabolites with a critical measure of confidence.

biochemistry