7 research outputs found

    The Brain Atlas Concordance Problem: Quantitative Comparison of Anatomical Parcellations

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    Many neuroscientific reports reference discrete macro-anatomical regions of the brain which were delineated according to a brain atlas or parcellation protocol. Currently, however, no widely accepted standards exist for partitioning the cortex and subcortical structures, or for assigning labels to the resulting regions, and many procedures are being actively used. Previous attempts to reconcile neuroanatomical nomenclatures have been largely qualitative, focusing on the development of thesauri or simple semantic mappings between terms. Here we take a fundamentally different approach, discounting the names of regions and instead comparing their definitions as spatial entities in an effort to provide more precise quantitative mappings between anatomical entities as defined by different atlases. We develop an analytical framework for studying this brain atlas concordance problem, and apply these methods in a comparison of eight diverse labeling methods used by the neuroimaging community. These analyses result in conditional probabilities that enable mapping between regions across atlases, which also form the input to graph-based methods for extracting higher-order relationships between sets of regions and to procedures for assessing the global similarity between different parcellations of the same brain. At a global scale, the overall results demonstrate a considerable lack of concordance between available parcellation schemes, falling within chance levels for some atlas pairs. At a finer level, this study reveals spatial relationships between sets of defined regions that are not obviously apparent; these are of high potential interest to researchers faced with the challenge of comparing results that were based on these different anatomical models, particularly when coordinate-based data are not available. The complexity of the spatial overlap patterns revealed points to problems for attempts to reconcile anatomical parcellations and nomenclatures using strictly qualitative and/or categorical methods. Detailed results from this study are made available via an interactive web site at http://obart.info

    Instantaneous Within-Patient Diversity of Pseudomonas aeruginosa Quorum-Sensing Populations from Cystic Fibrosis Lung Infections ▿ †

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    In the opportunistic pathogen Pseudomonas aeruginosa, acyl-homoserine lactone (acyl-HSL) quorum sensing (QS) regulates biofilm formation and expression of many extracellular virulence factors. Curiously, QS-deficient variants, often carrying mutations in the central QS regulator LasR, are frequently isolated from infections, particularly from cystic fibrosis (CF) lung infections. Very little is known about the proportion and diversity of these QS variants in individual infections. Such information is desirable to better understand the selective forces that drive the evolution of QS phenotypes, including social cheating and innate (nonsocial) benefits. To obtain insight into the instantaneous within-patient diversity of QS, we assayed a panel of 135 concurrent P. aeruginosa isolates from eight different adult CF patients (9 to 20 isolates per patient) for various QS-controlled phenotypes. Most patients contained complex mixtures of QS-proficient and -deficient isolates. Among all patients, deficiency in individual phenotypes ranged from 0 to about 90%. Acyl-HSL, sequencing, and complementation analyses of variants with global loss-of-function phenotypes revealed dependency upon the central QS circuitry genes lasR, lasI, and rhlI. Deficient and proficient isolates were clonally related, implying evolution from a common ancestor in vivo. Our results show that the diversity of QS types is high within and among patients, suggesting diverse selection pressures in the CF lung. A single selective mechanism, be it of a social or nonsocial nature, is unlikely to account for such heterogeneity. The observed diversity also shows that conclusions about the properties of P. aeruginosa QS populations in individual CF infections cannot be drawn from the characterization of one or a few selected isolates
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