Phenotypic screening, transcriptional profiling, and comparative genomic analysis of an invasive and non-invasive strain of Candida albicans

<p>Abstract</p> <p>Background</p> <p>Invasion of host tissue by the human fungal pathogen <it>Candida albicans </it>is an important step during the development of candidosis. However, not all <it>C. albicans </it>strains possess the same invasive and virulence properties. For example, the two clinical isolates SC5314 and ATCC10231 differ in their ability to invade host tissue and cause experimental infections. Strain SC5314 is invasive whereas strain ATCC10231 is non-invasive and strongly attenuated in virulence compared to SC5314. In this study we compare the <it>in vitro </it>phenotypic, transcriptional and genomic profiles of these two widely used laboratory strains in order to determine the principal biological and genetic properties responsible for their differential virulence.</p> <p>Results</p> <p>In all media tested, the two strains showed the same metabolic flexibility, stress resistance, adhesion properties and hydrolytic enzyme secretion <it>in vitro</it>. However, differences were observed in response to cell-surface disturbing agents and alkaline pH. Furthermore, reduced hyphal formation in strain ATCC10231 under certain conditions correlated with reduced invasive properties in an <it>in vitro </it>invasion assay and a reduced ability to invade epithelial tissue. Despite these diverse phenotypic properties, no substantial genomic differences were detected by comparative genome hybridisation within the open reading frames. However, <it>in vitro </it>transcriptional profiling displayed major differences in the gene expression of these two strains, even under normal <it>in vitro </it>growth conditions.</p> <p>Conclusion</p> <p>Our data suggest that the reason for differential virulence of <it>C. albicans </it>strains is not due to the absence of specific genes, but rather due to differences in the expression, function or activity of common genes.</p

Context sensitive cardiac x-ray imaging: a machine vision approach to x-ray dose control

Modern cardiac x-ray imaging systems regulate their radiation output based on the thickness of the patient to maintain an acceptable signal at the input of the x-ray detector. This approach does not account for the context of the examination or the content of the image displayed. We have developed a machine vision algorithm that detects iodine-filled blood vessels and fits an idealized vessel model with the key parameters of contrast, diameter, and linear attenuation coefficient. The spatio-temporal distribution of the linear attenuation coefficient samples, when appropriately arranged, can be described by a simple linear relationship, despite the complexity of scene information. The algorithm was tested on static anthropomorphic chest phantom images under different radiographic factors and 60 dynamic clinical image sequences. It was found to be robust and sensitive to changes in vessel contrast resulting from variations in system parameters. The machine vision algorithm has the potential of extracting real-time context sensitive information that may be used for augmenting existing dose control strategies

Investigation into diagnostic accuracy of common strategies for automated perfusion motion correction

Respiratory motion is a significant obstacle to the use of quantitative perfusion in clinical practice. Increasingly complex motion correction algorithms are being developed to correct for respiratory motion. However, the impact of these improvements on the final diagnosis of ischemic heart disease has not been evaluated. The aim of this study was to compare the performance of four automated correction methods in terms of their impact on diagnostic accuracy. Three strategies for motion correction were used: (1) independent translation correction for all slices, (2) translation correction for the basal slice with transform propagation to the remaining two slices assuming identical motion in the remaining slices, and (3) rigid correction (translation and rotation) for the basal slice. There were no significant differences in diagnostic accuracy between the manual and automatic motion-corrected datasets (p=0.88). The area under the curve values for manual motion correction and automatic motion correction were 0.93 and 0.92, respectively. All of the automated motion correction methods achieved a comparable diagnostic accuracy to manual correction. This suggests that the simplest automated motion correction method (method 2 with translation transform for basal location and transform propagation to the remaining slices) is a sufficiently complex motion correction method for use in quantitative myocardial perfusion

Inductive learning spatial attention

This paper investigates the automatic induction of spatial attention from the visual observation of objects manipulated on a table top. In this work, space is represented in terms of a novel observer-object relative reference system, named Local Cardinal System, defined upon the local neighbourhood of objects on the table. We present results of applying the proposed methodology on five distinct scenarios involving the construction of spatial patterns of coloured blocks

Risk Factors for Urinary Complications After Renal Transplantation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73788/1/j.1600-6143.2007.01790.x.pd