Twenty diabetic outpatients (12 non-insulin-treated and 8 insulin-treated) were given guar granulate in a dose of 10 g daily for two months in order to study the effect on glycaemic control and lipid levels. Mean glycosylated haemoglobin levels (HbAlc%) fell from 11.1±2.0% pre-guar to 10.5 ± 2.2% (P< 0.001) after one month on guar and to 10.1±2.3% ( P<0.0001) after two months. Following discontinuation of guar, HbAlc% rose to 11.1±2.5% ( P<0.002). However, there were no significant changes in fasting blood glucose, 1 h postprandial blood glucose following a test meal, 24 h urinary glucose excretion or in lipid levels. Gastrointestinal side effects occurred in 4 patients during treatment with guar. Four patients reduced their dose of insulin and 2 patients reduced their dose of sulphonylurea therapy during this time because of symptoms suggestive of hypoglycaemia. We suggest that the low dose of guar used in this study may help improve glycaemic control in diabetic patients and that this may be achieved with a low incidence of gastrointestinal side effects.

Background PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers. Methods Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging. Results A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis (‘GLYC-GLUC’) which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance. Conclusions In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.