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1.  Quantifying the Effects of Normal Ageing on White Matter Structure using Unsupervised Tract Shape Modelling 
NeuroImage  2010;51(1):1-10.
Quantitative tractography may provide insights into regional heterogeneity of changes in white matter structure in normal ageing. Here we examine how brain atrophy and white matter lesions affect correlations between tract shape, tract integrity and age in a range of frontal and non-frontal tracts in 90 non-demented subjects aged over 65 years using an enhanced version of probabilistic neighbourhood tractography. This novel method for automatic single seed point placement employs unsupervised learning and streamline selection to provide reliable and accurate tract segmentation, whilst also indicating how the shape of an individual tract compares to that of a predefined reference tract. There were significant negative correlations between tract shape similarity to reference tracts derived from a young brain white matter atlas and age in genu and splenium of corpus callosum. Controlling for intracranial and lateral ventricle volume, the latter of which increased significantly with age, attenuated these correlations by 40 and 84 % respectively, indicating that this age-related change in callosal tract topology is significantly mediated by global atrophy and ventricular enlargement. In accordance with the ‘frontal ageing’ hypothesis, there was a significant positive correlation between mean diffusivity (〈D〉) and age, and a significant negative correlation between fractional anisotropy (FA) and age in corpus callosum genu; correlations not seen in splenium. Significant positive correlations were also observed between 〈D〉 and age in bilateral cingulum cingulate gyri, uncinate fasciculi and right corticospinal tract. This pattern of correlations was not, however, reproduced when those subjects with significant white matter lesion load were analyzed separately from those without. These data therefore suggest that brain atrophy and white matter lesions play a significant role in driving regional patterns of age-related changes in white matter tract shape and integrity.
doi:10.1016/j.neuroimage.2010.02.036
PMCID: PMC3763188  PMID: 20171285
Ageing; white matter; magnetic resonance imaging; water diffusion tensor; tractography
2.  Visualization and Biochemical Analyses of the Emerging Mammalian 14-3-3-Phosphoproteome* 
Molecular & Cellular Proteomics : MCP  2011;10(10):M110.005751.
Hundreds of candidate 14-3-3-binding (phospho)proteins have been reported in publications that describe one interaction at a time, as well as high-throughput 14-3-3-affinity and mass spectrometry-based studies. Here, we transcribed these data into a common format, deposited the collated data from low-throughput studies in MINT (http://mint.bio.uniroma2.it/mint), and compared the low- and high-throughput data in VisANT graphs that are easy to analyze and extend. Exploring the graphs prompted questions about technical and biological specificity, which were addressed experimentally, resulting in identification of phosphorylated 14-3-3-binding sites in the mitochondrial import sequence of the iron-sulfur cluster assembly enzyme (ISCU), cytoplasmic domains of the mitochondrial fission factor (MFF), and endoplasmic reticulum-tethered receptor expression-enhancing protein 4 (REEP4), RNA regulator SMAUG2, and cytoskeletal regulatory proteins, namely debrin-like protein (DBNL) and kinesin light chain (KLC) isoforms. Therefore, 14-3-3s undergo physiological interactions with proteins that are destined for diverse subcellular locations. Graphing and validating interactions underpins efforts to use 14-3-3-phosphoproteomics to identify mechanisms and biomarkers for signaling pathways in health and disease.
doi:10.1074/mcp.M110.005751
PMCID: PMC3205853  PMID: 21725060
3.  Use of Cells Expressing γ Subunit Variants to Identify Diverse Mechanisms of AMPK Activation 
Cell Metabolism  2010;11(6):554-565.
Summary
A wide variety of agents activate AMPK, but in many cases the mechanisms remain unclear. We generated isogenic cell lines stably expressing AMPK complexes containing AMP-sensitive (wild-type, WT) or AMP-insensitive (R531G) γ2 variants. Mitochondrial poisons such as oligomycin and dinitrophenol only activated AMPK in WT cells, as did AICAR, 2-deoxyglucose, hydrogen peroxide, metformin, phenformin, galegine, troglitazone, phenobarbital, resveratrol, and berberine. Excluding AICAR, all of these also inhibited cellular energy metabolism, shown by increases in ADP:ATP ratio and/or by decreases in cellular oxygen uptake measured using an extracellular flux analyzer. By contrast, A769662, the Ca2+ ionophore, A23187, osmotic stress, and quercetin activated both variants to varying extents. A23187 and osmotic stress also increased cytoplasmic Ca2+, and their effects were inhibited by STO609, a CaMKK inhibitor. Our approaches distinguish at least six different mechanisms for AMPK activation and confirm that the widely used antidiabetic drug metformin activates AMPK by inhibiting mitochondrial respiration.
Graphical Abstract
Highlights
► AMPK is activated by a wide variety of different stresses, drugs, and xenobiotics ► We have developed a sensitive method to test which activators are AMP mediated ► Most, e.g., metformin and resveratrol, inhibit mitochondrial function and elevate AMP ► However, we can now distinguish six different mechanisms for AMPK activation
doi:10.1016/j.cmet.2010.04.001
PMCID: PMC2935965  PMID: 20519126
HUMDISEASE; SIGNALING

Results 1-3 (3)