Understanding sustainable diets: a descriptive analysis of the determinants and processes that influence diets and their impact on health, food security, and environmental sustainability

The confluence of population, economic development, and environmental pressures resulting from increased globalization and industrialization reveal an increasingly resource-constrained world in which predictions point to the need to do more with less and in a “better” way. The concept of sustainable diets presents an opportunity to successfully advance commitments to sustainable development and the elimination of poverty, food and nutrition insecurity, and poor health outcomes. This study examines the determinants of sustainable diets, offers a descriptive analysis of these areas, and presents a causal model and framework from which to build. The major determinants of sustainable diets fall into 5 categories: 1) agriculture, 2) health, 3) sociocultural, 4) environmental, and 5) socioeconomic. When factors or processes are changed in 1 determinant category, such changes affect other determinant categories and, in turn, the level of “sustainability” of a diet. The complex web of determinants of sustainable diets makes it challenging for policymakers to understand the benefits and considerations for promoting, processing, and consuming such diets. To advance this work, better measurements and indicators must be developed to assess the impact of the various determinants on the sustainability of a diet and the tradeoffs associated with any recommendations aimed at increasing the sustainability of our food system

Change management - practising what we teach: successfully engaging international students in the teaching, learning & assessment process

In this article we review processes of change in a module whose subject matter is change management. The module attracts mainly international students, and has suffered from uneven student engagement and performance. We will recount how a Teaching Enhancement and Student Success (TESS) project was used to inform our attempts to improve engagement and performance. Bearing in mind the origins of action research as part of Kurt Lewin‟s approach to planned change, we will use the four different elements of Lewin‟s work to reflect on the challenges we have been grappling with. The article will highlight different approaches to action research, which are linked to different aspirations as to the scope of change

Functional Analysis of Human Long Non-coding RNAs and Their Associations with Diseases

Within this study, we sought to leverage knowledge from well-characterized protein coding genes to characterize the lesser known long non-coding RNA (lncRNA) genes using computational methods to find functional annotations and disease associations. Functional genome annotation is an essential step to a systems-level view of the human genome. With this knowledge, we can gain a deeper understanding of how humans develop and function, and a better understanding of human disease. LncRNAs are transcripts greater than 200 nucleotides, which do not code for proteins. LncRNAs have been found to regulate development, tissue and cell differentiation, and organ formation. Their dysregulation has been linked to several diseases including autism spectrum disorder (ASD) and cancer. While a great deal of research has been dedicated to protein-coding genes, the relatively recently discovered lncRNA genes have yet to be characterized. LncRNA function is tied closely to when and where they are expressed. Co-expression network analysis offer a means of functional annotation of uncharacterized genes through a guilt by association approach. We have constructed two co-expression networks using known disease-associated protein-coding genes and lncRNA genes. Through clustering of the networks, gene set enrichment analysis, and centrality measures, we found enrichment for disease association and functions as well as identified high-confidence lncRNA disease gene targets. We present a novel approach to the identification of disease state associations by demonstrating genes that are associated with the same disease states share patterns that can be discerned from transcriptomes of healthy tissues. Using a machine learning algorithm, we built a model to classify ASD versus non-ASD genes using their expression profiles from healthy developing human brain tissues. Feature selection during the model-building process also identified critical temporospatial points for the determination of ASD genes. We constructed a webserver tool for the prioritization of genes for ASD association. The webserver tool has a database containing prioritization and co-expression information for nearly every gene in the human genome

An approach to the multidimensional assessment of food security and environmental sustainability: a vulnerability framework for the Mediterranean region

Poster presented at First International Conference on Global Food Security. Noordwijkerhout (The Netherlands), 29 Sep - 2 Oct 201

Multidimensional assessment of food security and environmental sustainability: a vulnerability framework for the Mediterranean Region [Poster]

Poster presented at Tropentag 2013. International Research on Food Security, Natural Resource Management and Rural Development. "Agricultural development within the rural-urban continuum". Stuttgart-Hohenheim (Germany), Sep 17-19 2013