text:
Metabolism| October 16 2012
Diurnal Pattern to Insulin Secretion and Insulin Action in Healthy Individuals
Ahmed Saad;
Ahmed Saad
1Division of Endocrinology and Metabolism, Mayo College of Medicine, Rochester, Minnesota
Chiara Dalla Man;
Chiara Dalla Man
2Department of Information Engineering, University of Padova, Via Gradenigo 6B, Padova, Italy
Debashis K. Nandy;
Debashis K. Nandy
James A. Levine;
James A. Levine
Adil E. Bharucha;
Adil E. Bharucha
Robert A. Rizza;
Robert A. Rizza
Rita Basu;
Rita Basu
Rickey E. Carter;
Rickey E. Carter
3Department of Health Sciences Research, Mayo College of Medicine, Rochester, Minnesota
Claudio Cobelli;
Claudio Cobelli
Yogish C. Kudva;
Yogish C. Kudva
Ananda Basu
Corresponding author: Ananda Basu, basu.ananda@mayo.edu.
A.S., C.D.M., and D.K.N. contributed equally to this study.
Ahmed Saad, Chiara Dalla Man, Debashis K. Nandy, James A. Levine, Adil E. Bharucha, Robert A. Rizza, Rita Basu, Rickey E. Carter, Claudio Cobelli, Yogish C. Kudva, Ananda Basu; Diurnal Pattern to Insulin Secretion and Insulin Action in Healthy Individuals. Diabetes 1 November 2012; 61 (11): 2691–2700. https://doi.org/10.2337/db11-1478
Evaluation of the existence of a diurnal pattern of glucose tolerance after mixed meals is important to inform a closed-loop system of treatment for insulin requiring diabetes. We studied 20 healthy volunteers with normal fasting glucose (4.8 ± 0.1 mmol/L) and HbA1c (5.2 ± 0.0%) to determine such a pattern in nondiabetic individuals. Identical mixed meals were ingested during breakfast, lunch, or dinner at 0700, 1300, and 1900 h in randomized Latin square order on 3 consecutive days. Physical activity was the same on all days. Postprandial glucose turnover was measured using the triple tracer technique. Postprandial glucose excursion was significantly lower (P < 0.01) at breakfast than lunch and dinner. β-Cell responsivity to glucose and disposition index was higher (P < 0.01) at breakfast than lunch and dinner. Hepatic insulin extraction was lower (P < 0.01) at breakfast than dinner. Although meal glucose appearance did not differ between meals, suppression of endogenous glucose production tended to be lower (P < 0.01) and insulin sensitivity tended to be higher (P < 0.01) at breakfast than at lunch or dinner. Our results suggest a diurnal pattern to glucose tolerance in healthy humans, and if present in type 1 diabetes, it will need to be incorporated into artificial pancreas systems.
A better understanding of the factors involved in glucose homeostasis is crucial to develop physiological models that can be incorporated into an optimal personalized artificial endocrine pancreas to improve glucose control, minimize glucose variability, and thus reduce morbidity and target-organ complications in individuals with diabetes mellitus, especially type 1 diabetes. These factors include, but are not limited to, variabilities introduced by diurnal differences in postprandial insulin secretion and action, timing and pattern of meal glucose appearance, and changes in physical activity.
Investigations evaluating diurnal pattern of glucose excursions have provided conflicting and confusing results. Although earlier studies (1) showed higher postprandial insulin concentrations in the morning than evening without any differences in postprandial glucose concentrations, subsequent studies (2) showed higher postprandial glucose excursion in the evening. In healthy individuals, some (2–4) but not all (1) studies suggest that postprandial glucose excursion is greater in the evening than morning. Both diminished insulin secretion and action have been considered responsible for decreased glucose tolerance in the evening (5). The reverse pattern has been observed in people with type 2 diabetes (6) and obesity (7). However, these studies (8) controlled for neither meal size, composition, and caloric content nor for levels of physical activity, all of which influence postprandial glucose excursions. Moreover, because these studies did not use glucose tracers and modeling techniques, hepatic and peripheral insulin action, meal glucose appearance, and postprandial insulin secretion were not assessed.
The purpose of this study was to determine if there are diurnal changes in postprandial glucose tolerance, insulin action, insulin secretion, and meal glucose appearance in nondiabetic subjects using the triple-tracer technique (9) while controlling for meal macronutrient composition and caloric content and levels of physical activity. We report that in healthy volunteers, glucose tolerance declines as the day advances.
After approval from the Mayo institutional review board and collection of signed informed consent, 20 nondiabetic subjects were recruited. Inclusion criteria were age 18–60 years, BMI <40 kg/m2, HbA1c ≤5.5%, creatinine ≤1.5 mg/dL, normal fasting glucose, and standard 75-g oral glucose tolerance test (OGTT) and normal gastric emptying to solids and liquids. Exclusion criteria were significant gastrointestinal symptoms by questionnaire, documented recent upper gastrointestinal disorder, medications affecting gastric motility (e.g., erythromycin), pregnancy or breastfeeding, or other comorbidities precluding participation. Medications (except stable thyroid hormone or hormone replacement therapy) that could influence glucose tolerance, history of diabetes in first degree family members, or prior history of diabetes were also exclusionary. Subjects did not engage in regular vigorous physical activities for 72 h before screen and study visits. Each subject underwent two screen visits.
Screen visit 1.
Subjects reported in the morning after an overnight fast to the Clinical Research Unit (CRU) of the Mayo Center for Translational Science Activities for a history, physical examination, screening laboratory tests, a 75-g standard OGTT, standard urinalysis, and resting electrocardiogram. All women of childbearing potential had a negative pregnancy test within 24 h of study visit. A dietary history was taken to ensure adherence to a weight maintaining diet consisting of at least 200 g of carbohydrates per day and that diet met American Diabetes Association guidelines for protein, fat, and carbohydrates. Body composition was also measured using dual energy X-ray absorptiometry (10).
With the use of established scintigraphic techniques (11), gastric emptying of solids and liquids were assessed in all subjects who were eligible after the first screening visit; results were summarized as the time required for 50% of solids and separately liquids to empty (GE T1/2). Thereafter, subjects who had normal gastric emptying for solids and liquids proceeded to the inpatient study visit within 3 weeks of the second screening visit.
In-patient study visit.
All subjects spent 3 days and 4 nights in the CRU. Subjects reported at ∼1600 h on the evening before the first study day. Continuous glucose sensor and triaxial accelerometer devices were placed. They consumed a standard 10 kcal/kg meal (55% carbohydrate, 15% protein, and 30% fat) between 1700 and 1730 h. No additional food was eaten until the next morning. All subjects were provided with breakfast (B) at 0700 h, lunch (L) at 1300 h, and dinner (D) at 1900 h for 3 consecutive days. An 18-gauge intravenous catheter was inserted ∼3 h before start of each labeled mixed meal study for infusion of tracer during the triple-tracer studies. Another intravenous cannula was inserted into a forearm vein in a retrograde fashion, and the hand was placed in a heated Plexiglass box as described before (10), to draw arterialized venous blood for hormone, glucose concentrations, and tracer enrichment periodically for 6 h after initiation of the labeled meal each day.
Study meals.
All meals were provided by the CRU metabolic kitchen. Study participants received 3 days of weighed meals, three meals each day (0700, 1300, and 1900 h) with each meal comprising 33% of total estimated calorie intake based on Harris Benedict calorie requirements with ∼50 g of carbohydrate in each meal adjusted for a low level of physical activity. The macronutrient contents for the labeled meals and the six unlabeled meals that each participant consumed were identical. No snacks or calorie-containing drinks were permitted between meals. Unfinished food was weighed and excluded from calculated caloric intake. One meal daily was randomly selected per Latin square design to include 50 g of glucose labeled with [1-13C]glucose in Jell-O as the carbohydrate component. The randomization sequence for the Latin square design was restricted to three potential sequences to maximize the time between tracer meals (i.e., minimize carryover effects). This design was specifically chosen to remove confounding effects of unequal glycogen labeling and carryover effects of residual tracer glucose plasma concentrations on postprandial glucose fluxes that would have occurred if all three successive meals were labeled within a 24-h period. Furthermore, a 1-day study design would have necessitated the subjects to be resting in bed the entire day, which is not representative of daily living. While we realize that meals were not evenly spaced (every 8 h), we wished to maintain a real-world approach to our study design by timing the meals in a pragmatic fashion, i.e., breakfast at 0700 h, lunch at 1300 h, and dinner at 1900 h.
Triple-tracer mixed meal.
A primed-continuous infusion of [6,6-2H2]glucose (11.84 mg/kg free fat mass prime; 0.1184 mg/kg free fat mass/min continuous; Mass-Trace, Woburn, MA) was started 3 h (−180 min) before the first bite of the mixed meal used to estimate postprandial glucose kinetics (9). Jell-O containing [1-13C]glucose was consumed within 15 min along with the rest of the mixed meal of eggs and Canadian bacon/steak. An infusion of [6-3H]glucose was started at time 0, and the rate varied to mimic the anticipated rate of appearance of the [1-13C]glucose contained within the meal. Simultaneously, the rate of infusion of [6,6-2H2]glucose was altered to approximate the anticipated pattern of change in endogenous glucose production (EGP) (10). Blood was sampled at −180, −30, 0, 5, 10, 20, 30, 60, 90, 120, 150, 180, 270, and 360 min for measurement of tracer-to-tracee ratios, glucose, insulin, glucagon, and C-peptide concentrations.
Physical activity protocol.
We used triaxial accelerometers (Physical Activity Monitoring System) that captured data on body posture and movement in duplicate every 0.5 s. Activity data were captured using one device for each half of the body and attached over the base of the spine. The participants were given a carefully planned physical activity protocol, adherence to which was captured using the Physical Activity Monitoring System. Subjects walked 5 to 6 h each day during the study period; the distribution of their active and nonactive time varied depending upon labeled meal schedules. Walking velocity of 1.2 mph was chosen (12) totaling to about 3.5 to 4.2 miles walked during the active times mimicking activities of daily living. The activity performed was ∼2.2 metabolic equivalents while walking and averaged about 1.7 metabolic equivalents during the active times. Caloric requirements of each participant were assessed by measurement of resting and walking energy expenditure during the physical activity program. Each of the labeled meals was preceded by at least 3 h and followed by 6 h of inactivity when the subjects were resting in bed to enable periodic blood draws. By design, there was a longer period of inactivity before breakfast than the other two meals.
Hormone analyses.
C-peptide was measured on the Cobas e411 (Roche Diagnostics, Indianapolis, IN) using a two-site electrochemiluminescence immunometric assay. Insulin was measured by a two-site immunoenzymatic assay performed on the DxI automated system (Beckman Instruments, Chaska, MN) and glucagon by a direct, double antibody radioimmunoassay (Linco Research, St. Charles, MO) (10).
Glucose tracers.
Plasma samples were placed on ice, centrifuged at 4°C, separated, and stored at −80°C until assay. Plasma glucose concentration was measured using a glucose oxidase method (YSI, Yellow Springs, OH). Plasma [6-3H]glucose specific activity was measured by liquid scintillation counting as described (10). Plasma enrichment of [1-13C]glucose and [6,6-2H2]glucose were measured using gas chromatography–mass spectrometry (Thermoquest, San Jose, CA) to simultaneously quantitate C1,2 and C3–6 fragments (9).
Glucose kinetics.
Fasting and postprandial rates of glucose turnover were calculated as described (9). The systemically infused [6-3H]glucose was used to trace the systemic rate of appearance of [1-13C]glucose contained in the meal, whereas [6,6-2H2]glucose was used to trace the rate of appearance of endogenously produced glucose. The ratio of plasma concentration of [6-3H]glucose to [1-13C]glucose was used to calculate the rate of appearance of ingested [1-13C]glucose, and the ratio of plasma concentration of [6,6-2H2]glucose to endogenously produced glucose was used to calculate EGP. The plasma concentration of endogenously produced glucose was calculated by subtracting the concentration of exogenously derived (ingested)glucose (i.e., plasma [1-13C]glucose concentration multiplied by meal [1-13C]glucose enrichment) from total plasma glucose concentration (9).
Meal indices.
The oral glucose minimal model (13,14) was used to interpret plasma glucose and insulin concentrations measured during the meal test. The model assumes that insulin action on glucose production and disposal emanates from a compartment remote from plasma, which is usually identified with the interstitium. The most important parameter of the model, estimated from data, is net insulin sensitivity, Si , which measures the overall effect of insulin to stimulate whole-body (liver and periphery) glucose disposal and inhibit glucose production. The oral C-peptide minimal model (15) was used together with the oral insulin minimal model (16) to interpret the interaction of plasma glucose with C-peptide and insulin, respectively. The oral C-peptide minimal model provides indices of dynamic (Φd) and static (Φs) β-cell responsivity to glucose, which measure the ability of rate of change of plasma glucose and plasma glucose concentration, respectively, to stimulate pancreatic insulin secretion. An index of total β-cell responsivity (Φtotal) can then be derived. The static component is derived from the ratio of the insulin secretion rate and the glucose concentrations above a threshold level at steady state. The dynamic index is a measure of the stimulatory effect of the rate at which glucose changes upon secretion of stored insulin. It is defined as the quantity of insulin released in response to maximum glucose concentration achieved during the meal normalized to the glucose increase from baseline. The total index is defined as the average increase over basal of insulin secretion over the average glucose stimulus above threshold level. The oral insulin minimal model, coupled with the C-peptide minimal model, provides estimates of both basal (HEb) and total (HE) hepatic insulin extraction. C-peptide is secreted in equimolar amounts to insulin from the β-cells, but while insulin is extracted by the liver, C-peptide is not. Hence, the simultaneous integration and modeling of insulin secretion rate from C-peptide data and insulin delivery rate to the systemic circulation from the insulin data after its passage through the liver provides an estimate of hepatic insulin extraction. In addition, a composite measure of insulin secretion appropriate to the prevailing degree of insulin resistance can be obtained by calculating dynamic (DId; composite of SI and ϕd), static (DIs; composite of SI and ϕs), and total (DItotal) disposition indices, from the product of insulin sensitivity (Si) and respective indices of β-cell responsivity (ϕ indices). All of the above models have been described in detail in the Supplementary Data.
Statistical analyses.
The experimental design translated statistically into a three-treatment (meals), three-period (study days) crossover study. SAS PROC Mixed (Cary, NC) was used to test for carryover effects and period effects using the methodology of Brown and Prescott (17). Carryover effects were presumed to be negligible given the short half-life of glucose and glucose tracers and the restricted randomization process. This assumption was supported by the statistical modeling and by the critical observation that there were no detectable glucose tracers in plasma from the prior labeled meals on days 2 and 3 in any subject. A period effect, however, was observed in the data for some outcome variables. As such, model-based estimates (least squares [LS] means) were calculated to provide an average effect over the study period. This analysis was supplemented with a sensitivity analysis of the first treatment period (i.e., similar to a parallel group design). These results were consistent with the full dataset (data not shown), so the results of the full experimental design were reported. Distributional assumptions for the mixed model were assessed using graphical displays and numerical summaries by meal-study day. Longitudinal summary statistics (18) were used to synthesize the serial measurements into a single index. Area under the curve (AUC) and incremental AUC (AUC after subtraction of the baseline area) were calculated by the trapezoidal rule. Post hoc comparison of postprandial states after meals (breakfast, lunch, and dinner) was tested at the 0.05 level of significance using the Tukey-Kramer correction factor. The overall effect of meal (i.e., a Type III analysis) was conducted using the Kenward-Rogers approach for determining degrees of freedom (19). Measures of insulin action (DI and Si ) had residuals that were mildly heteroscedastic, so the natural log-transformed values were reanalyzed as a sensitivity analysis.
Subject characteristics.
A total of 32 participants were screened for the study. There were eight screen failures (6 abnormal OGTT, 1 low hemoglobin, and 1 did not return for screen visit 2). Four additional participants were withdrawn after being successfully screened because of the inability to obtain IV access. The remaining 20 subjects completed the study and comprised the study group. Subject characteristics are provided in Table 1. Fasting glucose concentrations, HbA1c, and OGTT were normal. Physical activity levels, measured in Accelerometer Units (AU), did not differ among the 3 days. Gastric emptying rates for liquids (T1/2: M = 24.6, SD = 13.1 min) and solids (T1/2: M = 112.0, SD = 32.5 min) were normal in all subjects.
Baseline characteristics of the participants completing the three meal study (n = 20): subject anthropometric characteristics
Glucose, insulin, C-peptide, and glucagon concentrations.
In Fig. 1, preprandial plasma glucose concentrations were statistically different across the three meals (P = 0.004) with higher values at breakfast than at lunch or dinner (Table 2). Postprandial peak glucose concentrations were not different among the three meals (P = 0.09). The area above baseline of postprandial glucose excursion, however, was different (P < 0.001) with the lowest values occurring at breakfast, which indicated better glucose tolerance at breakfast than at lunch or dinner. In contrast, postprandial glucose excursions were not different between lunch and dinner.
A: Plasma glucose and insulin concentrations obtained after labeled breakfast, lunch, and dinner. B: Plasma C-peptide and glucagon concentrations obtained after labeled breakfast, lunch, and dinner.
Outcome measures of 3-day meal sequence
Preprandial plasma insulin concentrations did not differ among meals (P = 0.081), whereas postprandial peak insulin concentrations did (P = 0.008). In post hoc comparisons, peak insulin levels at dinner were less than those at breakfast (P < 0.05 after Tukey adjustment). Insulin area above baseline did not differ between meals (P = 0.23). Similarly, C-peptide concentrations did not differ among meals at baseline (P = 0.63) and were different with respect to the peak value (P = 0.029). In contrast with insulin concentrations, the area above baseline was different across meals (P = 0.024). Notably, the C-peptide concentrations over the postprandial period were over 16% higher at lunch relative to breakfast (P < 0.05 after Tukey adjustment).
Preprandial plasma glucagon concentrations and the postprandial area above basal were different among the meals (P < 0.001 for both). Interestingly, the preprandial glucagon levels at breakfast were approximately 20% less than at lunch or dinner (P < 0.05 after Tukey adjustment), but the postprandial area under the curve was over 2.5 times higher at breakfast than at lunch or dinner (P < 0.05 after Tukey adjustment).
Meal appearance, EGP, and glucose disappearance.
In Fig. 2A and B, there were no differences in Ra of meal glucose between the three meals (P = 0.99, Table 2), indicating that the differences in postprandial plasma glucose concentration between meals were not the result of differences in the Ra of meal glucose. Preprandial rate of EGP was different among the meals (P = 0.002) with lower production at breakfast than lunch or dinner. The incremental area below baseline of postprandial EGP was different among meals (P < 0.001), as was the percent suppression of EGP from baseline (P < 0.001). For both measures, breakfast was lower than lunch and dinner (P < 0.05 for both end points after Tukey correction). Likewise, the integrated Rd did not differ among meals (P = 0.89); however, percent increase in rates of Rd from baseline were different across meals (P = 0.029). The percent increase at breakfast was approximately 30% higher than at lunch or dinner (P < 0.05 for both after Tukey correction).
A: Ra of meal glucose, rate of EGP, and rate of Rd obtained after labeled breakfast, lunch, and dinner. B: Percent suppression of EGP and percent increase in Rd obtained after labeled breakfast, lunch, and dinner. *P < 0.05 vs. breakfast.
Indices of β-cell responsiveness and hepatic insulin extraction.
In Fig. 3, the index of β-cell responsiveness to a given glucose concentration (Φs) was higher at breakfast than at dinner but did not differ from lunch (P = 0.006), and β-cell responsiveness to a change in glucose concentration (Φd) was also higher at breakfast than at both lunch and dinner (P = 0.002, Table 2). Taken together, total β-cell responsivity (Φtotal) was over 20% higher at breakfast than at lunch and dinner (P = 0.002). Hepatic insulin extraction at baseline (HEb) was lower at breakfast than both lunch and dinner (P < 0.001). Likewise postprandial hepatic insulin extraction (HE) was also lower at breakfast than at lunch and dinner (P = 0.003). None of these indices differed between lunch and dinner.
A: Indices of β-cell responsiveness Φs, Φd, and Φtotal obtained after labeled breakfast, lunch, and dinner. *P < 0.05 vs. breakfast. B: Indices of hepatic insulin extraction (basal and total) were obtained after labeled breakfast, lunch, and dinner. *P < 0.05 vs. breakfast.
Indices of insulin action.
In Fig. 4, Si was higher at breakfast when compared with lunch and dinner (P < 0.05 after Tukey adjustment). Si did not differ between lunch and dinner. Likewise, disposition index (DI), DId, DIs were higher (P < 0.05) at breakfast than at lunch or dinner. As with many of the prior results, none of the indices differed between lunch and dinner. In the sensitivity analysis using natural log-transformed indices, all results remained the same except one. The transformed Si at dinner was no longer statistically different from baseline (P = 0.08 after Tukey correction). The details of the models applied including the weighted residuals are provided in the Supplementary Data online.
Si, DI static, DI dynamic, and DI total obtained after labeled breakfast, lunch, and dinner. *P < 0.05 vs. breakfast.
Si and DI distribution.
In Fig. 5, the individual patterns of Si and DI are depicted in log-transformed scale for the three meals. As shown in five of the 20 subjects, the diurnal pattern of Si and DI (high-low-low) was not maintained, reflecting the heterogeneity of responses.
A: Model-based Si for all subjects for each meal shown individually with log-transformed data. The boldface line indicates the average estimates for each meal. B: Model-based DI total for all subjects for each meal shown individually with log-transformed data. The boldface line indicates the average estimates for each meal. (A high-quality color representation of this figure is available in the online issue.)
Understanding diurnal patterns in glucose tolerance is critical for informing closed-loop control algorithm of insulin delivery to treat diabetes. However, to determine the existence of such a pattern, care needs to be taken to minimize confounding effects of variability in meal size, meal composition, and degree of physical activity, major factors that influence postprandial glucose tolerance. Our observations showing lower postprandial glucose excursion at breakfast than at lunch and dinner suggest the presence of a diurnal pattern to glucose tolerance in healthy nondiabetic subjects under carefully controlled conditions. This is characterized by a trend to reduced β-cell responsiveness and insulin action with increasing hepatic insulin extraction after lunch and dinner than at breakfast.
Although premeal physical activity could influence postprandial insulin action and hence glucose tolerance, our results demonstrating that postprandial glucose excursion was significantly lower at breakfast (preceded by a longer duration of inactivity) than at lunch or dinner support our case for a diurnal decline in glucose tolerance.
The primary observation of our study is that postprandial glucose excursion was lower at breakfast than at lunch or dinner. Diurnal variation in postprandial glucose excursions may result from changes in Ra of meal glucose, EGP, Rd, or a combination of these fluxes that were calculated with the triple-tracer approach (20). The Ra of meal glucose of ingested glucose did not differ between the three meals, thus eliminating alterations in glucose absorption and/or splanchnic uptake of meal glucose contributing to the observed changes in glucose tolerance. Moreover, these data suggest that the Ra of meal glucose, a reflection of net balance between rate of glucose absorption and splanchnic retention of meal glucose and by extension glucokinase activity (21,22), do not follow a diurnal pattern. Our data show that Si, reflecting composite effect of insulin on the rate of EGP and the rate of whole-body (liver and periphery) glucose disappearance, tended to be greater at breakfast than at lunch or dinner. However, in the sensitivity analysis using the log-transformed Si, statistical significance between breakfast and dinner was lost (P = 0.08). We are unable to directly calculate hepatic insulin action. However, because meal-derived glucose appearance did not differ between meals and because meal glucose contents were identical, it implies that splanchnic/hepatic glucose uptake (component of whole-body glucose disappearance) did not differ between meals. Therefore, it is reasonable to propose that the primary reason for greater Si at breakfast was an improved peripheral glucose disappearance although there were no detectable differences in whole-body Rd between meals. EGP was less suppressed at breakfast than at lunch or dinner likely because of the lower portal insulin concentrations (reflected by the lower C-peptide levels at breakfast) and lower plasma glucose concentrations. However, postprandial glucose disappearance did not differ at breakfast compared with lunch or dinner despite lower glucose concentrations, thereby providing support to our conclusion of improved insulin action (Si) during this meal.
With that said, it is important to underscore the limitations in the measurements of the various components of glucose turnover (i.e., Ra of meal glucose, Rd, and EGP) and meal indices (Si, DI) that do not consistently provide mechanistic insights and explanation to the primary observation of reduced postprandial glucose excursion at breakfast. This shortcoming likely reflects the relative imprecision of the estimation of both the meal indices and glucose flux calculations when compared with actual plasma glucose measurements, despite our rigorous study design applying state-of-the-art mathematical models (as detailed in the Supplementary Data online). For example, although Si (composite effect of insulin on both EGP and Rd) appeared to be higher at breakfast, the integrated responses of postprandial EGP and Rd were discordant. Specifically, although Si was higher, insulin suppression of EGP was lower at breakfast than the later meals. Additionally, fasting glucose concentrations were statistically slightly higher at breakfast despite slightly lower baseline EGP than the other two meals (Table 2). These observations are contradictory and reflect limitations in estimation of glucose turnover when compared with the precision in measurement of plasma glucose concentrations.
Our study was powered to detect differences in postprandial glucose excursions but underpowered to detect differences in the components of glucose turnover between meals. Furthermore, it is important to stress that our study did not investigate the repeatability of pattern of glucose tolerance within a subject over multiple 24-h periods. Such a study would be difficult to execute. Therefore, we cannot draw any conclusions regarding existence of a true circadian pattern to insulin secretion or action, nor was this study designed to test it.
Indices of β-cell responsiveness were higher after breakfast than after lunch or dinner, suggesting the presence of a diurnal pattern to β-cell responsiveness to absolute and changing glucose concentrations. This observation was further enhanced by the intriguing finding that hepatic insulin extraction also followed a diurnal pattern with the lowest extraction after breakfast than after lunch or dinner. The observation that lower hepatic insulin extraction at breakfast is associated with higher Si is corroborated by prior reports (23,24) showing similar observations between postprandial hepatic insulin extraction and whole-body insulin action.
DI was significantly higher at breakfast than at lunch or dinner, thus suggesting a diurnal pattern to this index. Likewise, Si, an index of insulin action, was higher at breakfast than the other two meals. As alluded to earlier and recorded in Table 2, sensitivity analyses of log-transformed DI did not reveal any changes to statistical significance, whereas for Si, statistical significance between breakfast and dinner was lost. Additionally, as shown in Fig. 5, there appears to be a degree of heterogeneity in the individual patterns to both DI and Si. In five subjects, the pattern shows low-high-low, whereas in the remaining fifteen subjects, the predominant pattern of high-low-low is maintained. Perhaps this heterogeneity of response patterns suggests diversity in demographic and/or physiological factors splitting the study population, although this was not evident on closer scrutiny of the demographic characteristics. However, we realize that in the limited sample size it would be unlikely to see tangible demographic differences in study cohorts. Furthermore, although our observations imply a diurnal pattern to postprandial insulin secretion, β-cell responsiveness, and insulin action in healthy people, the effect of other factors such as age, sex, adiposity, shift work, time-zone travel, and sleep-wake cycle disturbances on diurnal pattern will need to be investigated in future studies.
Our data also demonstrate, for the first time, an intriguing diurnal variation in postprandial plasma glucagon excursions. In contrast with insulin and C-peptide concentrations, preprandial glucagon concentrations were significantly lower at breakfast than at lunch or dinner. In contrast, postprandial glucagon excursion was significantly higher at breakfast than at lunch or dinner. It is possible that the longer (12 h) gap between dinner and breakfast (resulting in lower meal-derived amino acid concentrations) than the other two meals could explain the lower preprandial glucagon concentration at breakfast. However, this explanation is speculative at best. Additional studies are needed to determine the cause(s) of this observation.
In summary, this study demonstrates that under carefully controlled conditions of identical meal composition and physical activity in healthy individuals, postprandial glucose tolerance (as evidenced by lower postprandial glucose excursions) was better at breakfast than at lunch or dinner. This is in part the result of better β-cell responsiveness accompanied by a tendency to better insulin action and DI and lower hepatic insulin extraction at breakfast than later in the day. If a pattern in postprandial insulin action is observed in people with type 1 diabetes, this information will need to be incorporated into closed-loop systems of insulin delivery.
The work was supported by Grant DK R01 085561 from the National Institutes of Health (NIH) and Grant UL1 RR024150-01 from the National Center for Research Resources (NCRR), a component of the NIH, and NIH Roadmap for Medical Research.
A.S. and D.K.N. helped conduct the study and helped with data handling. C.D.M. and C.C. helped with the study design, data analyses, and manuscript review and editing. J.A.L., A.E.B., R.A.R., R.B., and R.E.C. helped with the study design and manuscript review and editing. Y.C.K. and A.B. helped with the study design, manuscript writing and editing, and researched data. A.B. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Parts of this study were presented at the 71st Scientific Sessions of the American Diabetes Association, San Diego, California, 24–28 June 2011, and at the 47th Annual Meeting of the European Association for the Study of Diabetes, Lisbon, Portugal, 12–16 September 2011.
The authors thank the research participants and the staff of the Mayo Clinic Center for Translational Science Activities CRU, the GI Motility Core, the CRU Mass Spectroscopy Laboratory, CRU Immunochemical Core Laboratory, Pamela Reich (research assistant), Betty Dicke (laboratory technician), Brent McConahey (research assistant), and Shelly McCrady Spitzer (research assistant). All people mentioned above are at the Endocrine Research Unit, Mayo Clinic (Rochester, MN).
De Gasparo
De Hertogh
Hoet
Circadian variations of blood sugar and plasma insulin levels in man
Van Cauter
Tillil
Polonsky
Circadian modulation of glucose and insulin responses to meals: relationship to cortisol rhythm
Am J Physiol
Diurnal variation in oral glucose tolerance: blood sugar and plasma insulin levels morning, afternoon, and evening
Effects of size, time of day and sequence of meal ingestion on carbohydrate tolerance in normal subjects
Aspostolakou
Diurnal variations in peripheral insulin resistance and plasma non-esterified fatty acid concentrations: a possible link?
Ann Clin Biochem
Dunseath
Luzio
Roy Choudhury
Daytime variability of postprandial glucose tolerance and pancreatic B-cell function using 12-h profiles in persons with Type 2 diabetes
Diabet Med
Ader
Diurnal variation in glucose tolerance. Cyclic suppression of insulin action and insulin secretion in normal-weight, but not obese, subjects
Waldhäusl
Circadian rhythms of insulin needs and actions
Diabetes Res Clin Pract
Basu
Di Camillo
Toffolo
Use of a novel triple-tracer approach to assess postprandial glucose metabolism
Am J Physiol Endocrinol Metab
Dalla Man
Cobelli
Effects of type 2 diabetes on insulin secretion, insulin action, glucose effectiveness and postprandial glucose metabolism
Bharucha
Forstrom
Zinsmeister
Relationship between clinical features and gastric emptying disturbances in diabetes mellitus
Clin Endocrinol (Oxf)
McCrady
Lanningham-Foster
Manohar
The role of free-living daily walking in human weight gain and obesity
Caumo
The oral glucose minimal model: estimation of insulin sensitivity from a meal test
IEEE Trans Biomed Eng
Minimal model estimation of glucose absorption and insulin sensitivity from oral test: validation with a tracer method
Cavaghan
Oral glucose tolerance test minimal model indexes of beta-cell function and insulin sensitivity
Minimal model assessment of hepatic insulin extraction during an oral test from standard insulin kinetic parameters
Applied Mixed Models in Medicine
. 2nd ed.
Everitt
Staistical Analysis of Medical Data using SAS
Chapman and Hall/CRC
Littell
Stroup
Wolfinger
Scabenberger
SAS for Mixed Models
The SAS Institute
Assessment of postprandial glucose metabolism: conventional dual- vs. triple-tracer method
Effects of type 2 diabetes on the ability of insulin and glucose to regulate splanchnic and muscle glucose metabolism: evidence for a defect in hepatic glucokinase activity
Type 2 diabetes impairs splanchnic uptake of glucose but does not alter intestinal glucose absorption during enteral glucose feeding: additional evidence for a defect in hepatic glucokinase activity
Effects of age and sex on postprandial glucose metabolism: differences in glucose turnover, insulin secretion, insulin action, and hepatic insulin extraction
Assessment of beta-cell function in humans, simultaneously with insulin sensitivity and hepatic extraction, from intravenous and oral glucose tests
Supplementary Figures- pptx file


text:
Riverhead, Southold police combat distracted driving
(Credit: Times/Review stock art)
Southold and Riverhead police officers will be stepping up their patrols later this month as part of a nationwide effort to curb distracted driving.
From today, April 10, through Tuesday, April 15, officers will focus on distracted driving enforcement in observation of the National Safety Council's Distracted Driving Month. The purpose of the initiative is to raise awareness of the dangers of distracted driving — such as texting and driving, police said.
The National Safety Council estimates more than one out of every four motor vehicle crashes involves cellphone use at the time of the crash. The departments will employ both traditional and innovative strategies to crack down on people who are texting and driving, police said.
"When you text while driving, you take your eyes off the road, hands off the wheel and mind off the task of driving," said Riverhead Town highway patrol officer Dennis Cavanagh.
"That puts everyone else's lives in danger, and no one has the right to do that."
There are thousands of death each year nationwide linked to distracted driving, with hundreds of thousands of injuries, officials said.
Email Michael White Email Created with Sketch. Email Michael White
Riverhead Town Police
Southold Town Police
Blotters: Driver charged with DWI after crash in Flanders
Southampton Town police arrested an Ozone Park man for driving while intoxicated following a motor vehicle accident in Flanders...
'Listening tour' sessions scheduled for Jan. 12, 14 for Riverhead Town's Law Enforcement Advisory Panel
Riverhead Town's Law Enforcement Advisory Panel will have a two-meeting "listening tour" next week, according to Supervisor Yvette Aguiar....
Updated: Body of missing kayaker found in Peconic Bay identified
A report of an overdue kayaker that sparked a broad search of the western Peconic Estuary ended in tragedy...
Cops: Man with handgun arrested at Riverhead laundromat
Riverhead Town police arrested a man who was armed with a handgun at a laundromat at 1080 Old Country...
Blotters: Patchogue man arrested for possession of crack cocaine in Flanders
Southampton Town police arrested Philip Fiasconaro, 52, of Patchogue, on drug charges in Flanders last Wednesday. Police said he...
Cops: Riverhead man arrested after throwing knife at officer
A Riverhead man who was threatening people with a large kitchen knife Wednesday morning was arrested after an officer...

redpajama_set_name: RedPajamaCommonCrawl


text:
An Electric Rivalry
Written By Adeetya Jain (Grade 8)
A lot of people have called some battles or rivalries legend. Few of them include the story of Bill Gates and Steve Job's bitter fights and quarrels. But nothing was like it when I saw the highlights of rivalry in an electric circuit. It was between a young Croatian genius and a big fancy inventor of that time. Yes, it was none other than Thomas Edison and Nikola Tesla. This story ended to be unfair for one of the parties but disgraceful for the other.
Let us get ourselves familiarized with some background information of these two men. Thomas Edison was the heart of the nation then. It was just a few days back that Edison achieved his breakthrough with the bulb. Not only America was counting on him but the whole world seemed to be tagging along in the journey of electricity. Edison would often envision the whole of America being lit up and slowly the world too. On the other hand, was a young university going boy in Croatia. He was not famous or cared for at that time. Though he was doing well in his physics lectures. The boy did not know that he was going to rewrite history and become the centre of legendary science debates.
Tesla was learning about the electric motor and station then. He used to draw graphs and envision changes in his mind itself. Not that he was looked upon as a prodigy, but his talent was going to help him attain the fame he has today. While learning about the engine he was thinking about the massive friction and the waste of energy. On the other hand, Edison had started his project on direct current (DC). It was a method on which Edison had depended on to provide electricity. He was sure that DC was the way to move forward. Nikola Tesla was eager on finding a better and productive way of giving electricity. A more efficient way of propagation of electric waves and a high amount of distribution of electricity using fewer powerhouses. Both of them had flaws. But we'll leave that for later. Let us get back on the story.
Tesla had got the inspiration from a simple class lecture. He knew he could invent something mindboggling. But for that, he needed help and funds. He was going to take the biggest risk of his life. He had to meet face to face with the world's greatest inventor, Thomas Edison. The young gentleman boarded his ship to luck, hope and his destiny. Reaching America was no more than an emotional rollercoaster. He knew that he could do something useful there. Edison Laboratories was a dream place for most inventors at that time. Not only because of the great man himself but for the renowned advancement in apparatus also. This laboratory was also heavily funded.
Tesla made his first acquaintance with Edison in the lab itself. Edison was known for his sheer arrogance and pride. Edison did not put anyone in his laboratory just like that. He wanted to test Tesla. He gave Tesla an impossible job to do. It was to test his patience and perseverance. The job proved to be quite difficult. Though Tesla could not accomplish his job, he did impress Edison with his patience and calm. Edison showed him the plan of direct current. It did have problems and needed to be repaired quickly.
But on the contrary, Tesla wanted to show Edison his model of Alternative Current to grab his attention. For the project, Edison had promised a $100,000 prize. Edison wanted to know other possible methods. Eventually, Tesla showed his work. It came out that Edison wanted an improvement on his direct current plan. But Tesla had shown something completely new. But this did not open Edison's eyes and he remained as arrogant as before. Nikola was denied of his $100,000 prize by being told that it was a joke and part of American humour. This enraged Tesla. He calmed himself by saying that he did not need Edison. He will do it on his own. But how will he do it?
Part 2 Coming Soon!!
Featured Image Courtesy – Engineer Mind
Adeetya Jain
I am Adeetya and I am 13 years old. I have a keen interest in political happenings around the world. I am also an avid reader. A keen blogger and love expressing my opinions. Here is a link to my blog.
Lata Mangeshkar – The Indian Nightingale


three families began meeting almost a year ago. they drank amazing coffee and shared hours of laughter and tears. but they shared something else as well – each of them was working tirelessly to bring a son or daughter home from africa.
and the reason i know about their amazing time together? i was one of the three.
and then we heard it. somebody yelled, i see them coming!
the crowd erupted into cheers and applause as dylan and carrie made their way through the terminal. that's when i realized it was official – mila was home.
dylan and carrie, words can't possibly express how ecstatic our family is for yours. we love you dearly, and we're so excited to finally say welcome home, friends. welcome home.
and praise god from whom all these little blessings flowed!
Great pics…. LAuren and I can't wait to meet Mila. Wish we could have been there for her first steps in America. Miss you guys!
Carrie and Dylan, words can't express the joy I have in my heart for your so precious gift from God. He is the Greatest!!! Mila is beautiful and all three of you are so precious to my family! The Banks' love you so much! CONGRATULATIONS!!!!!!


text:
Russian MP: Joint group of forces of Russia, Belarus will not be used in special military operation
State Duma
MINSK, 10 October (BelTA) - There is no need to use the joint group of forces of Russia and Belarus in the special military operation, RIA Novosti reported with reference to the head of the State Duma Committee on Defense Andrei Kartapolov.
"As for the participation [of the joint group] in the special military operation, I think that this will not be necessary. The group that is currently deployed there is quite capable of performing the task," the MP said. According to him, the aim of the deployment of the joint group of the Russian Federation and Belarus is to alleviate the concerns of our Belarusian brothers."
He also noted that the joint group will be deployed in response to the actions of the opponents, primarily Poland and its military buildup on the border with Belarus. "So, of course, we cannot disregard it. The joint group is not something new. It is stipulated in the Union State documents. Therefore it is called the regional group of the Armed Forces of the Republic of Belarus and the Russian Federation. Every year, we drilled its deployment and task performance at regular exercises. To date, a decision has simply been made at the request of the Belarusian president to deploy it. How large it will be is too early to say. The decision will be made by the general staffs of our countries," Andrei Kartapolov said.
More about Politics
Opinion: Europe is ruled by yes-people


text:
90 Day Fiance spoilers: Angela Deem says if Michael can't move to America, they'll be over
8th December 2019 12:55 PM ET
Angela says that moving to Nigeria is out of the question. Pic credit: TLC
Controversial 90 Day Fiance couple Angela Deem and Michael Ilesanmi have finally made their Season 7 debut. However, at the time of filming, Michael still didn't have his K-1 visa and if he doesn't get it, that could spell the end of Angela and Michael forever.
In the first scenes for Angela Deem on Season 7 of 90 Day Fiance, viewers see her getting quite a bit of Botox. She explains that she wants to look her best when Michael arrives in the United States and photos of Angela in the time since have proved that she does have a much smoother face.
But the biggest shocker for Angela and Michael happened in the confessional when she was talking about what might happen if Michael's visa doesn't get approved.
After all, he still lives in Nigeria and she's made a life for herself in Hazelhurst, Georgia, where she lives with her daughter Skyla and her six grandchildren. Angela even said that she's the sole breadwinner for the large household and that when Michael gets there, since he can't work right away, he'll be helping to take care of the large brood.
'K-1 or K-done'
So what would happen if Michael's visa is denied and he can't move to Georgia to live with Angela? She says that it will be the end of their relationship.
Sumit explains secret wife, declares love for Jenny but will 90 Day Fiance viewers forgive him?
In the confessional, she explained, "This interview is the last step to get the K-1 visa approved. It's a yes or a no to come to the States. He has to bring all kinds of documents. Proof of our relationship. They're going to ask him questions about my family."
'If he doesn't take this seriously, the government officials will not take it seriously and his *ss can be denied," Angela continued."
And when Michael suggests that if he doesn't pass this interview, he'll just try again, Angela loses it.
"You know the consequences, if you screw up, we'll be done," Angela tells Michael on 90 Day Fiance.
"If Michael fails this interview, I told him we're probably done," Angela said in the confessional. "I'm not moving to Nigeria. I've done told him this. If he don't get this visa, what are we gonna do? Have a relationship going over there once a year?"
"I don't have the strength," Angela continues. "I'm not getting younger. It's either the K-1 or K-done."
It's still not clear if Michael ends up coming to America or not. That's something that TLC and Sharp Entertainment have managed to keep close to the vest. We have seen photos of Angela and Michael that could be here in the United States based on Angela's appearance post-Botox but it could also be a filtered photo.
Rumor has it that Michael's visa was denied
There are 90 Day Fiance rumors that Michael Ilesanmi's visa may have been denied and they come from a trusted source. However, that source has even said that she doesn't know if it's true yet or not.
I have not been able to verify this yet but I have heard from multiple sources his visa is denied. Some people are saying he is here in the states but I have not been able to verify that either (I.e., no pictures of him spotted). Katrina's Court can't make a ruling on this one yet. Insufficient evidence to confirm. #90dayfiance 90daytheotherway #theotherway #90dayfiancebeforethe90days #90daysbeforethe90days #beforethe90days #90dayfiancehappilyeverafter #90dayfiancepillowtalk #podcast #podcasts #90dayfiancepodcast #realitytvpodcast #trashtvpodcast #thefraudcast #fraudedbytlc #tellalltea
A post shared by 90 Day Fiance (@fraudedbytlc) on Dec 8, 2019 at 8:05am PST
We'll just have to stay tuned to see what happens with Angela and Michael when they make their debut on Season 7.
90 Day Fiance airs Sundays at 8/7c on TLC. The first hour of Episode 6 can be watched now on the TLC Go app.
Tags: 90 Day Fiance, Angela Deem, Michael Ilesanmi


It seems it's time to terminate the partnership between SpamCop and CES Mail and find a vendor that knows how to manage and provision to an acceptable service availability agreement.
...Oh, I'm sure they care! However, only SpamCop staff would be able to explain why it hasn't been done. And they may either be unable (contracturally) or unwilling to do so.
...I understand your point but it's based on a complete misconception: just because your e-mail domain mentions "spamcop" does not mean that the SpamCop staff have any control over its behavior.
Complete and utter bullsh**. One and only one entity controls the domain. They have chosen to redirect subdomains to a provider that, at least at one time, they must vet. They could choose to review the integrity of the service as often as spamcop likes. If the service does not live up to the good name then they can ask them to shape up or ship out.
It's either a partnership or it's not. If it's not, then it should be opened up to any Internet mail provider who wishes to deliver reliable service in "partnership" with spamcop.
...We'll just have to agree to disagree. I defend your right to hold any position you choose but will assert that your view is no more authoritative than mine. And, frankly, I see nothing in what you wrote that in any way contradicts what I wrote. The fact that SpamCop has chosen to not exercise any control over "SpamCop e-mail" (my point) is orthogonal to your argument, with which I agree, that they should.
With all due respect, you say "just because your e-mail domain mentions 'spamcop' does not mean that the SpamCop staff have any control over its behavior."
I say that's not true. One entity controls the domain, not two. The entity that controls that domain - Spamcop, Cisco, whatever - has the ability to control anything that is done in that domain's name. They can ask for improvements from CES, hold them to a higher standard, kick them out for sullying the service's good name. But to say the owner of the domain "has no control" is just plain doublespeak.
The fact that SpamCop has chosen to not exercise any control over "SpamCop e-mail" (my point) is orthogonal to your argument, with which I agree, that they should.
Agreed then. They can, and they should. But getting a straight answer out of SC's staff or management is as easy as getting CES Mail to tell their customers what they have done to ensure this doesn't happen again.
...True but not comparable because we are (mostly) not paying customers of SpamCop (Cisco) but you are a paying customer of CES. My sense of why we don't get much visibility into SpamCop is that either they can not provide it to us due to legal considerations or they're busy enhancing the parser to handle evolving spammer "tricks" or they fear making information public that might help spammers avoid being caught by the parser.
If this problem doesn't get fixed pretty fast, I am filing a complaint with the B.B.B.
UltraDNS was hit with a massive DDOS attack today, could this be the problem?
...Oh, I'm sure they care!
What is your evidence for being sure they care?
I can tell you with certainty that this kind of poor service would not persist on MY watch month after month after month if I cared -- and I expect that most members of this newsgroup hold themselves to a similar standard.
Messages have started coming through again.
All fairly recent stuff. Not seeing the messages from earlier today yet though. They will probably be the last to arrive. It was a server that died then they would have to retrieve the data from backups first I suppose, assuming they have backups.
No, I don't think this situation will involve restoring from backups, because it was a "pass-through" filtering and routing server that appears to have been offline, not the MX or the final webmail system. The MX couldn't talk to the filtering server, so it was rejecting all incoming mail, so I'm pretty sure what we're seeing is entirely the "retries" coming from outside sources, and their retry intervals vary, so things will be jumbled until all the external servers that couldn't deliver decide to try again.
Rejecting all incoming mail? Oh crikey, that means all my mail since last night until the trickle that just started is lost, because I doubt very much if any ISP will process huge volumes of rejected mail. Is Spamcop trying to get us all labelled as spammers or what?
I hope you are wrong there. My ISP is typical of many and they tend to act first and think later, so if I get my service terminated SC will be hearing a lot from me.
...I deduce that they care from the fact that SpamCop staff (Don D'Minion) has been much more visible than the CES staff and doing what little is in his power to help (via communication with CES) when the e-mail issues arise, in spite of the fact that he has no direct control (or at least has opted, for whatever reason, to not execute whatever control he might have) over the behavior of the e-mail product.
I don't know. I just know that the MX server couldn't talk to the next-level server (which I think is "filter8") and so was giving a 400-level failure during the SMTP delivery attempt. I don't have my account doing much POPing, so I don't know the details of how those messages work their way through the system. You'd have to check with Email_Support.
Rejecting all incoming mail? Oh crikey, that means all my mail since last night until the trickle that just started is lost, because I doubt very much if any ISP will process huge volumes of rejected mail. I hope you are wrong there. My ISP is typical of many and they tend to act first and think later, so if I get my service terminated SC will be hearing a lot from me.
Mail servers are almost universally programmed to handle multiple failed attempts at delivery, as long as they're 400-level errors and not fatal 500-level ones (such as "no such user" etc.). If I'm correct, external sources that were trying to deliver to our spamcop.net (or cesmail.net) addresses during the outage would come back hours later (or sometimes a day later) and try again. This typically will continue for up to about three days, if I remember correctly.
This explains why some of us received a few hours' worth of mail and then everything ground to a halt again. No ETA given, unfortunately.
Yeah, all I got was 6 spams. I finally redirected my email away from spamcop and asked people (who I know had sent email) to resend and have already received the 2nd copies.
Well at least it's working now, thankfully.
Unfortunately not. See the message about reconfiguration of a server.
Some mailing list stuff arrived, often duplicated or triplicated and ordinary mail but nothing in the last three hours.
Well it is working, with delays in some of the mail that was originally blocked. That should eventually arrive. I too am missing some mail from earlier yesterday.
If the POP process was merrily grabbing the mail from POP servers but then couldn't talk to the filtering server(s), I guessing that a lot of mail could have been permanently lost, but that's a guess. Email_Support hasn't posted nor tweeted lately.


We are constantly on the looking out for PASSIONATE people craving for a new challenge.
If you are interested in working at the forefront of new technology at a brand new UK start-up, just contact us.
We are listening, tell us about your challenges.
Level39 | One Canada Square | Canary Wharf | London | E14 5AB Company number 11116051. Registered Office in England & Wales.