Colour constancy is typically measured with techniques involving asymmetric matching by adjustment, in which the observer views two scenes under different illuminants and adjusts the colour of a reference patch in one to match a test patch in the other. This technique involves an unnatural task, requiring the observer to predict and adjust colour appearance under an illumination shift. Natural colour constancy is more a simple matter of determining whether a colour is the same as or different from that seen under different illumination conditions. There are also technical disadvantages to the method of matching by adjustment, particularly when used to measure colour constancy in complex scenes. Therefore, we have developed and tested a two-dimensional method of constant-stimuli, forced-choice matching paradigm for measuring colour constancy. Observers view test and reference scenes haploscopically and simultaneously, each eye maintaining separate adaptation throughout a session. On each trial, a pair of test and reference patches against multicoloured backgrounds are presented, the reference patch colours being selected from a two-dimensional grid of displayable colours around the point of perfect colour constancy. The observer's task is to respond "same" or "different". Fitting a two-dimensional Gaussian to the percentage of "different" responses yields (1) the subjective colour-constancy point, (2) the discrimination ellipse centred on this point, and (3) a map of changes in sensitivity to chromatic differences induced by the illuminant shift. The subjective colour-constancy point measured in this way shows smaller deviations from perfect colour constancy-under conditions of monocular adaptation-than previously reported; discrimination ellipses are several times larger than standard MacAdam ellipses; and chromatic sensitivity is independent of the direction of the illuminant shift, for broad distributions of background colours.
This work asserts that QC is essential to proteomics discovery experiments. Every experimenter must know the current capabilities of their measurement system and have an objective means for tracking and ensuring that performance. Proteomic analysis work-flows are complicated and multi-variate. QC is critical for clinical chemistry measurements and huge strides have been made in ensuring the quality and validity of results in clinical biochemistry labs. This work introduces some of these QC concepts and works to bridge their use from single analyte QC to applications in multi-analyte systems. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics.
One proposed mechanism for underpinning colour constancy is computation of the relative activity of cones within one class--cone ratios, or cone contrasts--between surfaces in a fixed scene undergoing a change in illuminant. Although there is evidence that cone ratios do determine colour appearance under many conditions, the site or sites of their computation is unknown. Here, we report that a cerebrally achromatopsic observer, MS, displayed evidence of colour constancy in asymmetric colour matching tasks and was able to discriminate changes in cone ratios for simple, but not complex scenes. We hypothesise that the site of local cone-ratio computation is therefore early in the visual system, probably retinal.
Proteomics is increasingly being applied to the human plasma proteome to identify biomarkers of disease for use in non-invasive assays. 2-D DIGE, simultaneously analysing thousands of protein spots quantitatively and maintaining protein isoform information, is one technique adopted. Sufficient numbers of samples must be analysed to achieve statistical power; however, few reported studies have analysed inherent variability in the plasma proteome by 2-D DIGE to allow power calculations. This study analysed plasma from 60 healthy volunteers by 2-D DIGE. Two samples were taken, 7 days apart, allowing estimation of sensitivity of detection of differences in spot intensity between two groups using either a longitudinal (paired) or non-paired design. Parameters for differences were: two-fold normalised volume change, α of 0.05 and power of 0.8. Using groups of 20 samples, alterations in 1742 spots could be detected with longitudinal sampling, and in 1206 between non-paired groups. Interbatch gel variability was small relative to the detection parameters, indicating robustness and reproducibility of 2-D DIGE for analysing large sample sets. In summary, 20 samples can allow detection of a large number of proteomic alterations by 2-D DIGE in human plasma, the sensitivity of detecting differences was greatly improved by longitudinal sampling and the technology was robust across batches.
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