Minimal Effective Dose of Beans Required to Elicit a Significantly Lower Glycemic Response Than Commonly Consumed Starchy Foods: Predictions Based on In Vitro Digestion and Carbohydrate Analysis.

Beans elicit lower glycemic responses (GRs) than other starchy foods, but the minimum effective dose (MED) to reduce GR is unknown. We sought to determine the MED of beans compared to common starchy foods. Overnight-fasted healthy volunteers consumed »c (phase 1, n = 24) or ½c (phase 2, n = 18) of black, cranberry, great northern, kidney, navy and pinto beans and corn, rice, pasta and potato (controls), with blood glucose measured before and for 2 h after eating. GRs (incremental areas under the curves, iAUCs) after beans were consumed were compared to those of controls by ANOVA followed by Dunnett's test. To qualify for MED, beans had to elicit an effective reduction in GR, defined as a statistically significant reduction in iAUC of ≥20% (i.e., a relative glycemic response, RGR, ≤80). Outcomes from in vitro digestion were compared with in vivo RGR. Both doses of all six beans effectively reduced GR versus all four starchy controls, except for »c and ½c cranberry and pinto vs. corn, »c great northern and navy vs. corn and »c navy and pinto vs. potato. MED criteria were met for 18 comparisons of the »c servings, with four of the remaining six met by the ½c servings. The overall mean ± SEM RGR vs. controls was similar for the »c and ½c servings: 53 ± 4% and 56 ± 3%, respectively. By multiple regression analysis, RGR = 23.3 × RDS + 8.3 × SDS - 20.1 × RS + 39.5 × AS - 108.2 (rapidly digested starch, p < 0.001; slowly digested starch, p = 0.054; resistant starch, p = 0.18; available sugars, p = 0.005; model r = 0.98, p = 0.001). RGR correlated with in vitro glucose release (r = 0.92, p < 0.001). The MED of beans is » cup. For n = 30 comparisons (n = 24 beans vs. controls, n = 6 controls vs. each other), an effective reduction in GR was predicted from in vitro carbohydrate analysis with 86% sensitivity and 100% specificity.

Effects of High-Fat Diet Induced Obesity and Fructooligosaccharide Supplementation on Cardiac Protein Expression.

The mechanism by which high fat-diet induced obesity affects cardiac protein expression is unclear, and the extent to which this is modulated by prebiotic treatment is not known. These outcomes were assessed in rats initially fed a high-fat diet, then the top 40% weight gain group were randomly allocated to control (CON), high-fat (HF) and HF supplemented with fructooligosaccharide (32 g; HF-FOS) treatments for 12 weeks (n = 10/group). At sacrifice, left ventricles were either frozen or preserved in formalin. Serum was stored for glucose and insulin measurements. Protein spectra was obtained using an Orbitrap analyzer, processed with Sequest and fold changes assessed with Scaffold Q +. Treatment effects for body weights, glucose and insulin were assessed using one-way ANOVA, and the differential protein expression was assessed by a Mann-Whitney U test. The Database for Annotation, Visualization and Integrated Discovery and the Kyoto Encyclopedia of Genes and Genomes identified pathways containing overrepresented proteins. Hematoxylin and eosin sections were graded for hypertrophy and also quantified; differences were identified using Chi-square analyses and Mann-Whitney U tests. HF diet fed rats were significantly (p < 0.05) heavier than CON, and 23 proteins involved in mitochondrial function and lipid metabolism were differentially expressed between HF and CON. Between HF-FOS and HF, 117 proteins involved in contractility, lipid and carbohydrate metabolism were differentially expressed. HF cardiomyocytes were significantly (p < 0.05) more hypertrophic than CON. We conclude that high-fat feeding and FOS are associated with subcellular deviations in cardiac metabolism and contractility, which may influence myocardial function and alter the risk of cardiovascular disease.

Proximate Analysis and Nutritional Evaluation of Twenty Canadian Lentils by Principal Component and Cluster Analyses.

Proximate composition and starch nutritional properties of twenty cooked lentils were assessed to identify unique varieties that could be used in value added foods. Significant variations exist among the lentil varieties (p < 0.05) with respect to their energy, fat, protein, carbohydrate, and dietary fiber content, and these are related to lentil type and seed size. Dazil and Greenstar were unique for their high resistant starch content (RS) and lower area under the starch hydrolysis curve (SHAUC) while Proclaim was opposite. SHAUC was positively correlated (p < 0.001) with rapidly digestible starch (RDS) content (r = 0.626) but negatively correlated with RS content (r = -0.635). Principal component analysis showed that the first three principal components accounted for 62.8% of the total variance and the contribution of SHAUC was 33.2%. These results confirm that in vitro SHAUC and a combination of RDS and RS may be predictive of the digestibility profile of cooked lentils.

Food Type and Lentil Variety Affect Satiety Responses but Not Food Intake in Healthy Adults When Lentils Are Substituted for Commonly Consumed Carbohydrates.

BACKGROUND: Lentils have potential to increase satiety and may contribute to a body weight management strategy; however, the effects on satiety of replacing common food ingredients with lentils within food products remain largely unknown. OBJECTIVE: The aim of this study was to determine the effects of replacing wheat and rice with 2 lentil varieties within muffins and chilies on satiety, test-meal food intake, and 24-h energy intake. METHODS: Healthy adults consumed muffins or chilies in which wheat or rice was substituted with green (61.8 g) or red (54 g) lentils in 2 randomized crossover studies (muffin study: n = 24, mean ± SE age: 25.4 ± 0.9 y, BMI (in kg/m2): 23.2 ± 0.5; chili study: n = 24, age: 25.7 ± 1.0 y, BMI: 23.2 ± 0.5), with ≥1-wk washout periods between study visits and studies. Subjective appetite sensations measured over 180 min were summarized with total area under the curve (AUC), food intake was measured at an ad libitum test meal, and 24-h energy intake was measured using weighed food records. Treatment effects were compared within each study using repeated-measures ANCOVA (subjective appetite sensations) and ANOVA (food intake, 24-h energy intake). RESULTS: Green, but not red, lentil chili significantly increased fullness AUC (17.5%, P = 0.02) and decreased desire to eat AUC (20.1%, P = 0.02) and prospective food consumption AUC (16.7%, P = 0.04) compared with rice chili, with no significant differences between chili treatments for test-meal food intake or 24-h energy intake. Muffin treatments did not significantly differ for any outcomes. CONCLUSIONS: Replacing rice with green, but not red lentils within chili increases satiety but does not decrease food intake, whereas replacing wheat with lentils within muffins does not increase satiety or decrease food intake in healthy adults. Further study of the role of lentil replacement in food products in body weight management is warranted. This trial was registered at clinicaltrials.gov as NCT03128684.

Effect of Processing on Postprandial Glycemic Response and Consumer Acceptability of Lentil-Containing Food Items.

The consumption of pulses is associated with many health benefits. This study assessed post-prandial blood glucose response (PPBG) and the acceptability of food items containing green lentils. In human trials we: (i) defined processing methods (boiling, pureeing, freezing, roasting, spray-drying) that preserve the PPBG-lowering feature of lentils; (ii) used an appropriate processing method to prepare lentil food items, and compared the PPBG and relative glycemic responses (RGR) of lentil and control foods; and (iii) conducted consumer acceptability of the lentil foods. Eight food items were formulated from either whole lentil puree (test) or instant potato (control). In separate PPBG studies, participants consumed fixed amounts of available carbohydrates from test foods, control foods, or a white bread standard. Finger prick blood samples were obtained at 0, 15, 30, 45, 60, 90, and 120 min after the first bite, analyzed for glucose, and used to calculate incremental area under the blood glucose response curve and RGR; glycemic index (GI) was measured only for processed lentils. Mean GI (± standard error of the mean) of processed lentils ranged from 25 ± 3 (boiled) to 66 ± 6 (spray-dried); the GI of spray-dried lentils was significantly (p < 0.05) higher than boiled, pureed, or roasted lentil. Overall, lentil-based food items all elicited significantly lower RGR compared to potato-based items (40 ± 3 vs. 73 ± 3%; p < 0.001). Apricot chicken, chicken pot pie, and lemony parsley soup had the highest overall acceptability corresponding to "like slightly" to "like moderately". Processing influenced the PPBG of lentils, but food items formulated from lentil puree significantly attenuated PPBG. Formulation was associated with significant differences in sensory attributes.

Carbohydrate Replacement of Rice or Potato with Lentils Reduces the Postprandial Glycemic Response in Healthy Adults in an Acute, Randomized, Crossover Trial.

Background: The postprandial blood glucose response (PBGR) following carbohydrate replacement of high-glycemic index (GI) foods with pulses, in a mixed meal, has not been accurately defined. Objective: We aimed to determine the extent to which PBGR and relative glycemic response (RGR) are lowered when half of the available carbohydrate (AC) from rice or potato is replaced with cooked lentils. Methods: Using a crossover design, 2 groups of 24 healthy adults randomly consumed 50 g AC from control white rice alone [mean ± SD body mass index (BMI, in kg/m2): 24.3 ± 0.5; mean ± SD age: 27.7 ± 1.2 y], instant potato alone (BMI: 24.0 ± 0.5; age: 27.4 ± 1.2 y), or the same starch source in a 50:50 AC combination with each of 3 types of commercially available lentils (large green, small green, split red). Fasting and postprandial blood samples were analyzed for glucose and insulin, and used to derive incremental area under the curve (iAUC), RGR, and maximum concentration (Cmax). Treatment effects were assessed with the use of repeated-measures ANOVA within the rice and potato treatments. Results: In comparison to rice alone, blood glucose iAUC and Cmax (P < 0.001) were lowered after consumption of rice with large green (P = 0.057), small green (P = 0.002), and split red (P = 0.006) lentils. Blood glucose iAUC and Cmax were also significantly lowered (P < 0.0001) after consumption of potato combined with each lentil, compared to potato alone. Plasma insulin iAUC and Cmax were significantly (P < 0.001) decreased when lentils were combined with potato, but not with rice. The RGRs of rice and potato were lowered by ∼20% and 35%, respectively, when half of their AC was replaced with lentils. Conclusions: Replacing half of the AC from high-GI foods with lentils significantly attenuates PBGR in healthy adults; this can contribute to defining a health claim for pulses and blood glucose lowering. This trial was registered at clinicaltrials.gov as NCT02426606.

Investigating the relationship between lentil carbohydrate fractions and in vivo postprandial blood glucose response by use of the natural variation in starch fractions among 20 lentil varieties.

Consumption of pulses is associated with many health benefits by mechanisms that are not fully understood. This study sought to identify the starch component(s) in cooked lentils responsible for lowering postprandial glycemic response (PPGR). Rapidly digestible (RDS), slowly digestible (SDS) and resistant starch (RS) content of 20 varieties of cooked lentil were determined by in vitro methods and 8 varieties, representing a linear range of SDS, were chosen for a human trial with 10 participants to determine PPGR and glycemic index (GI). Among the 20 lentil varieties, RS accounted for 35% of the variation of in vitro area under the starch hydrolysis curve (SHAUC) (r = -0.587; p < 0.01), but RDS (r = 0.401; p = 0.080) and SDS (r = -0.022; p = 0.927) were not significantly related to SHAUC. Multiple linear regression of in vitro data resulted in an equation [SHAUCest = 30.9RDS - 63.6RS + 9680] that accounted for 70% of the variance in SHAUC, with SDS excluded due to collinearity. In the human trial all 8 lentils had low GI values (10 to 23). Neither GI nor area under the glucose response curve (AUC) was significantly related to RDS, SDS or RS (minimum p = 0.24). However, SHAUC and SHAUCest, respectively, were related to both GI (r = 0.704, p = 0.051; r = 0.773, p = 0.024) and AUC (r = 0.765, p = 0.027; r = 0.822, p = 0.012). These results confirm that lentils have low GI values, which is not reliably predicted by their RDS, SDS and RS contents when considered individually. However, in vitro SHAUC and a combination of RDS and RS may be predictive of the PPGR of lentils.

Whole Soy Flour Incorporated into a Muffin and Consumed at 2 Doses of Soy Protein Does Not Lower LDL Cholesterol in a Randomized, Double-Blind Controlled Trial of Hypercholesterolemic Adults.

BACKGROUND: Soy protein may reduce coronary heart disease (CHD) risk by lowering LDL cholesterol, but few studies have assessed whether whole soy flour displays a similar effect. OBJECTIVE: The aim of this study was to assess the dose effect of whole soy flour incorporated into muffins on plasma LDL cholesterol in hypercholesterolemic adults. METHODS: Adults aged 30-70 y (n = 243) with elevated LDL cholesterol (≥3.0 and ≤5.0 mmol/L) were stratified by LDL cholesterol and randomly assigned to consume 2 soy muffins containing 25 g soy protein [high-dose soy (HDS)], 1 soy and 1 wheat muffin containing 12.5 g soy protein and 12.5 g whey protein [low-dose soy (LDS)], or 2 wheat muffins containing 25 g whey protein (control) daily for 6 wk while consuming a self-selected diet. Fasting blood samples were collected at weeks 0, 3, and 6 for analysis of plasma lipids [total, LDL, and HDL cholesterol and triglycerides (TGs)], glucose, insulin, C-reactive protein (CRP), and isoflavones. Blood pressures also were measured. Dietary intake was assessed at weeks 0 and 4 with the use of 3 d food records. Treatment effects were assessed with the use of intention-to-treat analysis with multiple imputation and LDL cholesterol as the primary outcome. RESULTS: In total, 213 (87.6%) participants completed the trial. Participants were primarily Caucasian (83%) and mostly female (63%), with a mean ± SD body mass index (in kg/m2) of 28.0 ± 4.6 and systolic and diastolic blood pressures of 122 ± 16 and 77 ± 11 mm Hg, respectively. Despite a dose-dependent increase in plasma isoflavones (P < 0.001), neither HDS nor LDS had a significant effect on LDL cholesterol compared with control (mean ± SEM changes: control, -0.04 ± 0.05 mmol/L; HDS, 0.01 ± 0.05 mmol/L; and LDS, -0.04 ± 0.06 mmol/L). There were no significant treatment effects on total or HDL cholesterol, TGs, CRP, homeostatic model assessment of insulin resistance, blood pressure, or the Framingham 10-y CHD risk score. CONCLUSION: Consuming 12.5 or 25 g protein from defatted soy flour incorporated into muffins does not reduce LDL cholesterol or other CHD risk factors in hypercholesterolemic adults. This trial was registered at clinicaltrials.gov as NCT01547585.

The glycemic index of pigmented potatoes is related to their polyphenol content.

Polyphenol extracts from coloured fruits and vegetables inhibit α-glucosidase in vitro, however it is not known whether this translates into an attenuation of blood glucose response in vivo. We examined this relationship in a GI study by feeding coloured potatoes to 9 healthy volunteers. We also examined the in vitro inhibitory activity of potato anthocyanin extracts on rat intestinal α-glucosidase. Potatoes (Purple Majesty; Red-Y38; Yukon Gold and Snowden) were fed with skin after cooking in a convection oven, using a random block design and 50 g available carbohydrate. Glucose was used as the standard and venous blood collected at 0, 15, 30, 45, 60, 90, 120 min. Areas under the curve (AUC) for glucose and insulin were calculated, and GI and Insulin Index derived. Neither AUC for blood glucose response nor insulin was significantly different among the various potatoes studied. Although the mean GI (±SE) values for the potato types varied (purple = 77.0 ± 9.0; red = 78.0 ± 14.0; yellow = 81.0 ± 16.0; and white = 93.0 ± 17.0), these differences were not significantly different. The mean (±SE) polyphenol content (mg GAE/100 g DW) was 234 ± 28; 190 ± 15; 108 ± 39; 82 ± 1 for purple, red, yellow and white potatoes, respectively. There was a significant inverse correlation between polyphenol content and GI of the potatoes (r = -0.825; p < 0.05; n = 4). In vitro, polyphenol extracts of red and purple potatoes inhibited α-glucosidase by 37.4 ± 2.2% and 28.7 ± 3.2%, respectively. The GI of coloured potatoes is significantly related to their polyphenol content, possibly mediated through an inhibitory effect of anthocyanins on intestinal α-glucosidase.

Assessment of distributions for fitting lag times of individual cells in bacterial populations.

To develop mathematical models describing lag times of individual bacterial cells (tau), experimental tau data were fitted to a variety of continuous distributions using BestFit. Six strains of Escherichia coli O157:H7 were used, and serial dilutions were made in Bioscreen multi-well plates to get single cells per well. Detection times (td) for individual wells were converted to tau using the maximum specific growth rate (mu) for each strain. All strains were subject to 25 trials, with up to 100 replicate wells per trial. Some strains had significantly longer t(d), and lower mu, but the tau values were not significantly different. Distributions were best fit in the order Pearson V>Pearson VI>Extreme Value>Lognormal>Lognormal2>Inverse Gaussian based on the Anderson-Darling statistic. The Lognormal distribution was selected because there was less variability in the parameter values, and parameters have specific biological meanings. Distributions could be fit to sample populations as low as six, with fittings and parameter values comparable to those obtained with larger samples (up to 89). Extreme Value, Pearson V, and Pearson VI distributions were more suitable for fitting tau values generated from a Lognormal distribution when the numbers of sample points were few, which suggested that there are similarities between the distributions. The results suggest that a Lognormal distribution can be used successfully to characterize tau.