The Glycemic Potential of White and Red Rice Affected by Oil Type and Time of Addition.

UNLABELLED: Limited research exists on how different oil types and time of addition affect starch digestibility of rice. This study aimed to assess the starch digestibility of white and red rice prepared with 2 oil types: vegetable oil (unsaturated fat) and ghee (clarified butter, saturated fat) added at 3 different time points during the cooking process ("before": frying raw rice in oil before boiling, "during": adding oil during boiling, and "after": stir-frying cooked rice in oil). Red rice produced a slower digestion rate than white rice. White rice digestibility was not affected by oil type, but was affected by addition time of oil. Adding oil "after" (stir-frying) to white or red rice resulted in higher slowly digestible starch. Red rice cooked using ghee showed the lowest amount of glucose release during in vitro digestion. The addition of ghee "during" (that is boiling with ghee) or "before" (that is frying rice raw with ghee then boiling) cooking showed potential for attenuating the postprandial glycemic response and increasing resistant starch content. This is the first report to show healthier ways of preparing rice. White rice with oil added "after" (stir-fried) may provide a source of sustained glucose and stabilize blood glucose levels. Boiling red rice with ghee or cooking red rice with ghee pilaf-style may provide beneficial effects on postprandial blood glucose and insulin concentrations, and improve colonic health. The encouraging results of the present study justify extending it to an in vivo investigation to conclusively determine the effect of time of addition of fat when rice is cooked on blood glucose homeostasis. PRACTICAL APPLICATION: Rice is a predominant source of energy in most of Asia with excessive consumption of rice being implicated in the rise of type 2 diabetes. Stir-frying white rice can be a source of sustained glucose and provide a stabilizing effect on blood glucose levels. Boiling red rice with ghee or cooking red rice with ghee pilaf-style may provide beneficial effects on postprandial blood glucose and insulin concentrations. This suggests how a single technique of adding fat in the cooking of rice at certain time points may be a useful method in providing taste and lowering glycemia.

The impact of a low glycemic index (GI) breakfast and snack on daily blood glucose profiles and food intake in young Chinese adult males.

OBJECTIVE: Low glycemic index (GI) foods have been suggested to minimize large fluctuations in blood glucose levels and reduce food intake. However, the majority of studies have been conducted on Caucasian populations with limited data on Asians. The objective of this study was to investigate how the provision of a low GI breakfast and afternoon snack affected daily blood glucose profiles and food intake. MATERIALS AND METHODS: In a randomized, controlled crossover non blind design, 11 healthy Chinese male adults (body mass index 22.4 ± 1.3 kg m-2) attended two sessions where they consumed either a high or low GI breakfast and afternoon snack, and a standardized buffet lunch. Daily changes in glycemic response (GR) were measured using the Medtronic MiniMed (Northridge, CA) iPro™2 continuous glucose monitoring system (CGMS). The GR was further calculated to obtain the incremental area under the curve (IAUC). Glycemic variability was calculated as mean amplitude of glycemic excursion (MAGE) and energy intake (kcal) was measured quantitatively at the buffet lunch. RESULTS: Compared to the high GI intervention, the low GI intervention significantly reduced the GR following breakfast (p = 0.02), lunch (p = 0.02) and dinner (p = 0.05). The low GI treatment showed a reduction in daily AUC (p = 0.03). There was a significant reduction in IAUC after a low GI breakfast compared to the high GI breakfast (p = 0.03). The low GI breakfast resulted in a significantly lower food intake at lunch and a resulting decreased energy intake of 285 kcal (p = 0.02). The MAGE was significantly lower during the entire low GI treatment (p = 0.03). CONCLUSIONS: Consumption of a low GI breakfast and afternoon snack was capable of attenuating 24-h blood glucose profiles, minimize glycemic excursions and reduce food intake in healthy Asian males. This simple dietary intervention may be an acceptable approach in improving overall glycemia and energy balance in Asians. CLINICAL TRIAL REGISTRATION NUMBER: NCT02340507.

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies.

BACKGROUND: Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR) and statistical power (SP) which is the ability to correctly identify important genes. RESULTS: This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i) exposing E. coli cells to two different ethanol levels; (ii) application of myostatin to two groups of mice; and (iii) a simulated data study derived from the properties of (ii). The proposed method (PM) effectively identified critical genes in these studies based on comparison with the current method (CM). The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. CONCLUSIONS: PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.