47 research outputs found
The Maltase Involved in Starch Metabolism in Barley Endosperm Is Encoded by a Single Gene
During germination and early seedling growth of barley (Hordeum vulgare), maltase is responsible for the conversion of maltose produced by starch degradation in the endosperm to glucose for seedling growth. Despite the potential relevance of this enzyme for malting and the production of alcoholic beverages, neither the nature nor the role of maltase is fully understood. Although only one gene encoding maltase has been identified with certainty, there is evidence for the existence of other genes and for multiple forms of the enzyme. It has been proposed that maltase may be involved directly in starch granule degradation as well as in maltose hydrolysis. The aim of our work was to discover the nature of maltase in barley endosperm. We used ion exchange chromatography to fractionate maltase activity from endosperm of young seedlings, and we partially purified activity for protein identification. We compared maltase activity in wild-type barley and transgenic lines with reduced expression of the previously-characterised maltase gene Agl97, and we used genomic and transcriptomic information to search for further maltase genes. We show that all of the maltase activity in the barley endosperm can be accounted for by a single gene, Agl97. Multiple forms of the enzyme most likely arise from proteolysis and other post-translational modifications
Recruitment and retention of students–an integrated and holistic vision of mathematics support
Microbiology of the phyllosphere: a playground for testing ecological concepts
Many concepts and theories in ecology are highly debated, because it is often difficult to design decisive tests with sufficient replicates. Examples include biodiversity theories, succession concepts, invasion theories, coexistence theories, and concepts of life history strategies. Microbiological tests of ecological concepts are rapidly accumulating, but have yet to tap into their full potential to complement traditional macroecological theories. Taking the example of microbial communities on leaf surfaces (i.e. the phyllosphere), we show that most explorations of ecological concepts in this field of microbiology focus on autecology and population ecology, while community ecology remains understudied. Notable exceptions are first tests of the island biogeography theory and of biodiversity theories. Here, the phyllosphere provides the unique opportunity to set up replicated experiments, potentially moving fields such as biogeography, macroecology, and landscape ecology beyond theoretical and observational evidence. Future approaches should take advantage of the great range of spatial scales offered by the leaf surface by iteratively linking laboratory experiments with spatial simulation models
Understanding evaluation of learning support in mathematics and statistics
With rapid and continuing growth of learning support initiatives in mathematics and statistics found in many parts of the world, and with the likelihood that this trend will continue, there is a need to ensure that robust and coherent measures are in place to evaluate the effectiveness of these initiatives. The nature of learning support brings challenges for measurement and analysis of its effects. After briefly reviewing the purpose, rationale for, and extent of current provision, this article provides a framework for those working in learning support to think about how their efforts can be evaluated. It provides references and specific examples of how workers in this field are collecting, analysing and reporting their findings. The framework is used to structure evaluation in terms of usage of facilities, resources and services provided, and also in terms of improvements in performance of the students and staff who engage with them. Very recent developments have started to address the effects of learning support on the development of deeper approaches to learning, the affective domain and the development of communities of practice of both learners and teachers. This article intends to be a stimulus to those who work in mathematics and statistics support to gather even richer, more valuable, forms of data. It provides a 'toolkit' for those interested in evaluation of learning support and closes by referring to an on-line resource being developed to archive the growing body of evidence. © 2011 Taylor & Francis
