The visual processing of motion-defined transparency

Our understanding of how the visual system processes motion transparency, the phenomenon by which multiple directions of motion are perceived to co-exist in the same spatial region, has grown considerably in the past decade. There is compelling evidence that the process is driven by global-motion mechanisms. Consequently, although transparently moving surfaces are readily segmented over an extended space, the visual system cannot separate two motion signals that co-exist in the same local region. A related issue is whether the visual system can detect transparently moving surfaces simultaneously, or whether the component signals encounter a serial â??bottleneckâ?? during their processing? Our initial results show that, at sufficiently short stimulus durations, observers cannot accurately detect two superimposed directions; yet they have no difficulty in detecting one pattern direction in noise, supporting the serial-bottleneck scenario. However, in a second experiment, the difference in performance between the two tasks disappears when the component patterns are segregated. This discrepancy between the processing of transparent and non-overlapping patterns may be a consequence of suppressed activity of global-motion mechanisms when the transparent surfaces are presented in the same depth plane. To test this explanation, we repeated our initial experiment while separating the motion components in depth. The marked improvement in performance leads us to conclude that transparent motion signals are represented simultaneously.

Conformational changes during proteolytic processing of a picornavirus capsid proteins

We have used synthetic peptide antibodies to probe conformational changes that occur during the cleavage cascade which generates the capsid proteins of a picornavirus. The initial translation product of 97 kDa, the precursor of all four structural proteins, is cleaved to form a 63 kDa fragment which, we show, has significantly different folding characteristics to both its larger parent and its products. We demonstrate that proteolytic cleavages as distant as 520 residues from epitopes confer sufficiently large conformational changes as to render them unrecognisable. To our knowledge, this is the first demonstration of this phenomenon in the picornavirus system.

Cell-specific processing of chromogranin A in endocrine cells of the rat stomach

The rat stomach is rich in endocrine cells. The acid-producing (oxyntic) mucosa contains ECL cells, A-like cells, and somatostatin (D) cells, and the antrum harbours gastrin (G) cells, enterochromaffin (EC) cells and D cells. Although chromogranin A (CgA) occurs in all these cells, its processing appears to differ from one cell type to another. Eleven antisera generated to different regions of rat CgA, two antisera generated to a human (h) CgA sequences, and one to a bovine Ib) CgA sequence, respectively, were employed together with antisera directed towards cell-specific markers such as gastrin (G cells), serotonin (EC cells), histidine decarboxylsae (ECL cells) and somatostatin (D cells) to characterize the expression of CgA and CgA-derived peptides in the various endocrine cell populations of the rat stomach. In the oxyntic mucosa, antisera raised against CgA(291-319) and CGA(316-321) immunostained D cells exclusively, whereas antisera raised against bCgA(82-91) and CgA(121-128) immunostained A-like cells and D cells. Antisera raised against CgA(318-349) and CgA(437-448) immunostained ECL cells and A-like cells, but not D cells. In the antrum, antisera against CgA(291-319) immunostained D cells, and antisera against CgA(351-356) immunostained G cells. Our observations suggest that each individual endocrine cell type in the rat stomach generates a unique mixture of CgA-derived peptides, probably reflecting cell-specific differences in the post-translational processing of CgA and its peptide products. A panel of antisera that recognize specific domains of CgA may help to identify individual endocrine cell populations.

Targeted 3' processing of antisense transcripts triggers Arabidopsis FLC chromatin silencing.

Noncoding RNA is emerging as an important regulator of gene expression in many organisms. We are characterizing RNA-mediated chromatin silencing of the Arabidopsis major floral repressor gene, FLC. Through suppressor mutagenesis, we identify a requirement for CstF64 and CstF77, two conserved RNA 3'-end-processing factors, in FLC silencing. However, FLC sense transcript 3' processing is not affected in the mutants. Instead, CstF64 and CstF77 are required for 3' processing of FLC antisense transcripts. A specific RNA-binding protein directs their activity to a proximal antisense polyadenylation site. This targeted processing triggers localized histone demethylase activity and results in reduced FLC sense transcription. Targeted 3' processing of antisense transcripts may be a common mechanism triggering transcriptional silencing of the corresponding sense gene.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.