Monash University

About: Monash University is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 35920 authors who have published 100681 publications receiving 3027002 citations.

Diets that differ in their FODMAP content alter the colonic luminal microenvironment

Abstract: Objective A low FODMAP (Fermentable Oligosaccharides, Disaccharides, Monosaccharides And Polyols) diet reduces symptoms of IBS, but reduction of potential prebiotic and fermentative effects might adversely affect the colonic microenvironment. The effects of a low FODMAP diet with a typical Australian diet on biomarkers of colonic health were compared in a single-blinded, randomised, cross-over trial. Design Twenty-seven IBS and six healthy subjects were randomly allocated one of two 21-day provided diets, differing only in FODMAP content (mean (95% CI) low 3.05 (1.86 to 4.25) g/day vs Australian 23.7 (16.9 to 30.6) g/day), and then crossed over to the other diet with ≥21-day washout period. Faeces passed over a 5-day run-in on their habitual diet and from day 17 to day 21 of the interventional diets were pooled, and pH, short-chain fatty acid concentrations and bacterial abundance and diversity were assessed. Results Faecal indices were similar in IBS and healthy subjects during habitual diets. The low FODMAP diet was associated with higher faecal pH (7.37 (7.23 to 7.51) vs 7.16 (7.02 to 7.30); p=0.001), similar short-chain fatty acid concentrations, greater microbial diversity and reduced total bacterial abundance (9.63 (9.53 to 9.73) vs 9.83 (9.72 to 9.93) log 10 copies/g; p Clostridium cluster XIVa (median ratio 6.62; p Akkermansia muciniphila (19.3; p Ruminococcus torques . Conclusions Diets differing in FODMAP content have marked effects on gut microbiota composition. The implications of long-term reduction of intake of FODMAPs require elucidation. Trial registration number ACTRN12612001185853.

Graph WaveNet for Deep Spatial-Temporal Graph Modeling

Abstract: Spatial-temporal graph modeling is an important task to analyze the spatial relations and temporal trends of components in a system. Existing approaches mostly capture the spatial dependency on a fixed graph structure, assuming that the underlying relation between entities is pre-determined. However, the explicit graph structure (relation) does not necessarily reflect the true dependency and genuine relation may be missing due to the incomplete connections in the data. Furthermore, existing methods are ineffective to capture the temporal trends as the RNNs or CNNs employed in these methods cannot capture long-range temporal sequences. To overcome these limitations, we propose in this paper a novel graph neural network architecture, Graph WaveNet, for spatial-temporal graph modeling. By developing a novel adaptive dependency matrix and learn it through node embedding, our model can precisely capture the hidden spatial dependency in the data. With a stacked dilated 1D convolution component whose receptive field grows exponentially as the number of layers increases, Graph WaveNet is able to handle very long sequences. These two components are integrated seamlessly in a unified framework and the whole framework is learned in an end-to-end manner. Experimental results on two public traffic network datasets, METR-LA and PEMS-BAY, demonstrate the superior performance of our algorithm.

Framework Analysis: A Qualitative Methodology for Applied Policy Research

Abstract: Policies and procedures govern organizations whether they are private or public, for-profit or not-forprofit. Review of such policies and procedures are done periodically to ensure optimum efficiency within the organization. Framework analysis is a qualitative method that is aptly suited for applied policy research. Framework analysis is better adapted to research that has specific questions, a limited time frame, a pre-designed sample and a priori issues. In the analysis, data is sifted, charted and sorted in accordance with key issues and themes using five steps: familiarization; identifying a thematic framework; indexing; charting; and mapping and interpretation. Framework analysis provides an excellent tool to assess policies and procedures from the very people that they affect.