TOWARDS GLOBAL E-AGRICULTURE: THE CHALLENGE OF WEB-BASED DECISION SUPPORT SYSTEMS FOR GROWERS

Globalization is influencing several agriculture aspects: market globalization has increased export from producing to consuming countries where different food safety or pesticide residue regulations apply, and has raised awareness of global problems linked to agriculture production (i.e., chemical pesticide pollution). Pests, diseases and weeds may cause significant damages to growers and the cost of pesticide increases. Environmental pollution and risk of unwanted residues on food forced researchers to find ways to optimize pesticide applications. However, extension services and research in pest management is often fragmented and efforts to develop support tools for pest management are often duplicated. Furthermore, sometimes the knowledge does not spread from research centers to growers due to difficulties in knowledge transfer. Decision support systems (DSS) are widely used for assisting with integrated pest management (IPM), crop nutrition, and other aspects of information transfer. Developing highly portable and especially web-based DSSs that can be easily adapted to new environments is therefore desirable in view of agriculture globalization. Web-based models and DSSs have the major advantage of reducing software development, maintenance, and distribution costs, while making the relevant knowledge easily accessible to growers world-wide. This paper presents two examples of web-based agricultural DSSs and demonstrates the potential use of these systems in a wide application range in order to adapt to the needs of globalization. Allowing the choice of different values for the parameters renders these DSSs very flexible. Their development process integrated agricultural expertise from two distinct research centers with information systems know-how from a third center, over two countries, demonstrating the need for a global software development that crosses country borders. The results show that it is possible to satisfy the prerequisites: reducing software development cost by enlarging the number of users and reaching growers among whom specific knowledge on diseases is not yet established

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. VIDEO ABSTRACT