Objective:To cross-sectionally compare the regional white matter fractional anisotropy (FA) of cognitively normal (CN) older individuals and patients with mild cognitive impairment (MCI) and Alzheimer disease (AD), separately focusing on the normal-appearing white matter (NAWM) and white matter hyperintensities (WMH), and to test the independent effects of presumed degenerative and vascular process on FA differences. Methods:Forty-seven patients with AD, 73 patients with MCI, and 95 CN subjects received diffusion tensor imaging and vascular risk evaluation. To properly control normal regional variability of FA, we divided cerebral white matter into 4 strata as measured from a series of young healthy individuals (H1 ϭ highest; H2 ϭ intermediate high; H3 ϭ intermediate low; H4 ϭ lowest anisotropy stratum). Results:For overall cerebral white matter, patients with AD had significantly lower FA than CN individuals or patients with MCI in the regions with higher baseline anisotropy (H1, H2, and H3), corresponding to long corticocortical association fibers, but not in H4, which mostly includes heterogeneously oriented fibers. Vascular risk showed significant independent effects on FA in all strata except H1, which corresponds to the genu and splenium of the corpus callosum. Similar results were found within NAWM. FA in WMH was significantly lower than NAWM across all strata but was not associated with diagnosis or vascular risk. Conclusions:Both vascular and Alzheimer disease degenerative process contribute to microstructural injury of cerebral white matter across the spectrum of cognitive ability and have different region-specific injury patterns. Neurology ® 2009;73:1722-1728 GLOSSARY AD ϭ Alzheimer disease; ANCOVA ϭ analysis of covariance; ANOVA ϭ analysis of variance; CC ϭ corpus callosum; CN ϭ cognitively normal; DTI ϭ diffusion tensor imaging; FA ϭ fractional anisotropy; MCI ϭ mild cognitive impairment; MDT ϭ minimal deformation template; MMSE ϭ Mini-Mental State Examination; NAWM ϭ normal-appearing white matter; ROI ϭ region of interest; SLF ϭ superior longitudinal fasciculus; UCD ϭ University of California, Davis; WMH ϭ white matter hyperintensities.Fractional anisotropy (FA), a quantitative measure derived from diffusion tensor imaging (DTI), sensitively reflects the microstructural integrity of white matter fibers.1 Decrease in FA of cerebral white matter is known to occur with mild cognitive impairment (MCI) and Alzheimer disease (AD), 2 as well as cognitively normal aging 3 and cerebrovascular vascular disease. 4Little is known, however, about the FA changes within white matter hyperintensities (WMH) occurring in patients with AD or MCI, even though WMH are commonly associated with MCI 5,6 and AD. 5,7 Most previous DTI studies 8-14 of patients with AD and MCI typically compared their white matter with that of cognitively normal (CN) older individuals, without proper consideration of WMH, or focused solely on normal-appearing white matter (NAWM).Moreover, the separate and independent contributions o...

The accuracy of phylogenetic inference was examined in simulated data sets up to nearly 10,000 taxa, the size of the largest set of homologous genes in existing molecular sequence databases. Even with a simple search algorithm (maximum parsimony without branch swapping), the number of characters needed to estimate 80% of a tree correctly can scale remarkably well at optimal substitution rates (on the order of log N, where N is the number of taxa). In other words, the number of taxa in an analysis can be doubled and only an arithmetic increase in the number of characters is required to maintain the same level of accuracy. Even substitution rates that are much higher than normally used in phylogenetic studies did not affect the scaling too adversely. However, scaling is usually worse than log N for more stringent levels of accuracy. Moreover, errors are not distributed randomly throughout the tree. Shallow nodes are remarkably easy to reconstruct and display favourable log-linear scaling. The deepest nodes are extremely difficult to reconstruct accurately, even with branch swapping, and the scaling is poor. Therefore, the strategy of sequencing large numbers of homologous genes may not always provide global solutions to extreme phylogenetic problems and alternative strategies may be required.

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