Post-Prandial Glucose and Insulin Responses of Hummus Alone or Combined with a Carbohydrate Food: A Dose-Response Study

OBJECTIVES: Pulses are low glycemic index (GI) foods and have been associated with reduced risk of heart disease, diabetes and some cancers. However the blood glucose and insulin responses of hummus, a food containing chickpea, have not been thoroughly tested. METHODS: Ten healthy subjects each consumed 11 breakfast study meals in randomized order over a period of 15 weeks. Hummus was consumed alone at three doses (2.7 g, 10.8 g and 25 g available carbohydrate [avCHO] portions) and with 50 g avCHO from white bread at three doses (2.7 g, 5.4 g and 10.8 g avCHO portions). The responses elicited by hummus alone were compared with 25 g avCHO portions of white bread, while those after hummus plus white bread were compared with 50 g avCHO from white bread. Plasma glucose and serum insulin responses were monitored over two hours and the GI and insulin index (II) calculated using standard methodology. RESULTS: The GI and II of hummus were 15 ± 3 and 52 ± 13, respectively, and were significantly lower than white bread (P \u3c 0.05). The glucose and insulin incremental area under the curve (IAUC) for hummus alone were significantly lower than white bread except for insulin IAUC of hummus 25 g avCHO. The peak rise of blood glucose and insulin after hummus were significantly lower than after white bread. Glucose and insulin IAUC after adding hummus to bread did not differ significantly from white bread alone. However the blood glucose 45 min after adding 25 g avCHO from hummus to white bread was significantly lower while at 120 min it was significantly higher than after white bread alone. CONCLUSIONS: This study demonstrated that, similar to chickpeas, hummus has a very low GI and II. Postprandial glucose responses were 4 times less than that of white bread and did not compromise insulin levels

Combined effect of obesity and diabetes on early breast cancer outcome: A prospective observational study

Background: Previous studies suggested that obesity and diabetes were correlated with breast cancer outcome. The aim of the present study was to investigate the prognostic effect of obesity and diabetes on the outcome of early breast cancer patients. Materials and Methods: Overall, 841 early breast cancer patients were prospectively enrolled between January 2009 and December 2013. Study population was divided into four groups: (1) patients without obesity or diabetes; (2) patients with only diabetes; (3) patients with only obesity; and (4) patients with both diabetes and obesity. Categorical variables were analyzed by the chi-square test and survival data by the log-rank test. Results: At diagnosis, obese and diabetic patients were more likely to be older (p < 0.0001) and post-menopausal (p < 0.0001) and to have a tumor larger than 2 cm (p < 0.0001) than patients in groups 1–3. At univariate analyses, obese and diabetic patients had a worse disease-free survival (p = 0.01) and overall survival (p = 0.001) than did patients without obesity and diabetes. At multivariate analyses, the co-presence of obesity and diabetes was an independent prognostic factor for diseasefree survival (hazard ratio=2.62, 95% CI 1.23–5.60) but not for overall survival. Conclusions: At diagnosis, patients with obesity and diabetes were older, had larger tumors and a worse outcome compared to patients without obesity or diabetes. These data suggest that metabolic health influences the prognosis of patients affected by early breast cance

Dietary glycemic index and load and the risk of type 2 diabetes: A systematic review and updated meta‐analyses of prospective cohort studies

Published meta-analyses indicate significant but inconsistent incident type-2 diabetes (T2D)-dietary glycemic index (GI) and glycemic load (GL) risk ratios or risk relations (RR). It is now over a decade ago that a published meta-analysis used a predefined standard to identify valid studies. Considering valid studies only, and using random effects dose-response meta-analysis (DRM) while withdrawing spurious results (p &lt; 0.05), we ascertained whether these relations would support nutrition guidance, specifically for an RR &gt; 1.20 with a lower 95% confidence limit &gt;1.10 across typical intakes (approximately 10th to 90th percentiles of population intakes). The combined T2D-GI RR was 1.27 (1.15-1.40) (p &lt; 0.001, n = 10 studies) per 10 units GI, while that for the T2D-GL RR was 1.26 (1.15-1.37) (p &lt; 0.001, n = 15) per 80 g/d GL in a 2000 kcal (8400 kJ) diet. The corresponding global DRM using restricted cubic splines were 1.87 (1.56-2.25) (p &lt; 0.001, n = 10) and 1.89 (1.66-2.16) (p &lt; 0.001, n = 15) from 47.6 to 76.1 units GI and 73 to 257 g/d GL in a 2000 kcal diet, respectively. In conclusion, among adults initially in good health, diets higher in GI or GL were robustly associated with incident T2D. Together with mechanistic and other data, this supports that consideration should be given to these dietary risk factors in nutrition advice. Concerning the public health relevance at the global level, our evidence indicates that GI and GL are substantial food markers predicting the development of T2D worldwide, for persons of European ancestry and of East Asian ancestry

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.Peer Reviewe

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies

The effect of wheat bran particle size and wheat protein on serum lipids and colonic health

grantor: University of TorontoBackground. Wheat bran is the major source of dietary fiber yet the optimum particle size is not clearly defined. Objective. To determine the effect of wheat bran particle size and wheat protein on serum lipids and colonic health. Design. In one-month metabolic (n = 24) and two-week ad-libitum diets (n = 24) subjects took 19g/d dietary fiber as fine or coarse-wheat bran in randomized crossover studies with low-fiber controls. In the metabolic study 10% of energy was provided as wheat gluten. Results. Wheat bran had no effect on serum lipids but gluten reduced triglycerides (P = 0.005). Wheat bran particle size did not affect fecal bulking. However, fine bran increased fecal butyrate concentrations (P $<$ 0.007) and breath CH\sb4 levels (P = 0.025) suggesting increased bacterial fermentation. Conclusions. Wheat bran regardless of particle size does not lower serum lipids although gluten may reduce serum triglycerides. Fine bran is an effective fecal bulking agent and may promote colonic mucosal health.M.Sc