An extracellular transglutaminase is required for apple pollen tube growth

An extracellular form of the calcium-dependent protein-cross-linking enzyme TGase (transglutaminase) was demonstrated to be involved in the apical growth of Malus domestica pollen tube. Apple pollen TGase and its substrates were co-localized within aggregates on the pollen tube surface, as determined by indirect immunofluorescence staining and the in situ cross-linking of fluorescently labelled substrates. TGase-specific inhibitors and an anti-TGase monoclonal antibody blocked pollen tube growth, whereas incorporation of a recombinant fluorescent mammalian TGase substrate (histidine-tagged green fluorescent protein: His6-Xpr-GFP) into the growing tube wall enhanced tube length and germination, consistent with a role of TGase as a modulator of cell wall building and strengthening. The secreted pollen TGase catalysed the cross-linking of both PAs (polyamines) into proteins (released by the pollen tube) and His6-Xpr-GFP into endogenous or exogenously added substrates. A similar distribution of TGase activity was observed in planta on pollen tubes germinating inside the style, consistent with a possible additional role for TGase in the interaction between the pollen tube and the style during fertilization.

The mosaic test:benchmarking colour-based image retrieval systems using image mosaics

Evaluation and benchmarking in content-based image retrieval has always been a somewhat neglected research area, making it difficult to judge the efficacy of many presented approaches. In this paper we investigate the issue of benchmarking for colour-based image retrieval systems, which enable users to retrieve images from a database based on lowlevel colour content alone. We argue that current image retrieval evaluation methods are not suited to benchmarking colour-based image retrieval systems, due in main to not allowing users to reflect upon the suitability of retrieved images within the context of a creative project and their reliance on highly subjective ground-truths. As a solution to these issues, the research presented here introduces the Mosaic Test for evaluating colour-based image retrieval systems, in which test-users are asked to create an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. We report on our findings from a user study which suggests that the Mosaic Test overcomes the major drawbacks associated with existing image retrieval evaluation methods, by enabling users to reflect upon image selections and automatically measuring image relevance in a way that correlates with the perception of many human assessors. We therefore propose that the Mosaic Test be adopted as a standardised benchmark for evaluating and comparing colour-based image retrieval systems.

The mosaic test:measuring the effectiveness of colour-based image retrieval

A variety of content-based image retrieval systems exist which enable users to perform image retrieval based on colour content - i.e., colour-based image retrieval. For the production of media for use in television and film, colour-based image retrieval is useful for retrieving specifically coloured animations, graphics or videos from large databases (by comparing user queries to the colour content of extracted key frames). It is also useful to graphic artists creating realistic computer-generated imagery (CGI). Unfortunately, current methods for evaluating colour-based image retrieval systems have 2 major drawbacks. Firstly, the relevance of images retrieved during the task cannot be measured reliably. Secondly, existing methods do not account for the creative design activity known as reflection-in-action. Consequently, the development and application of novel and potentially more effective colour-based image retrieval approaches, better supporting the large number of users creating media for use in television and film productions, is not possible as their efficacy cannot be reliably measured and compared to existing technologies. As a solution to the problem, this paper introduces the Mosaic Test. The Mosaic Test is a user-based evaluation approach in which participants complete an image mosaic of a predetermined target image, using the colour-based image retrieval system that is being evaluated. In this paper, we introduce the Mosaic Test and report on a user evaluation. The findings of the study reveal that the Mosaic Test overcomes the 2 major drawbacks associated with existing evaluation methods and does not require expert participants. © 2012 Springer Science+Business Media, LLC.