Sleep restriction (SR) (<6 h) and physical activity (PA) are risk factors for obesity, but little work has examined the inter-related influences of both risk factors. In a free-living environment, 13 overweight/obese adults were sleep restricted for five nights to 6 h time-in-bed each night, with and without regular exercise (45 min/65% VO2 max; counterbalanced design). Two days of recovery sleep followed SR. Subjects were measured during a mixed meal tolerance test (MMT), resting metabolic rate, cognitive testing and fat biopsy (n=8). SR increased peak glucose response (+7.3 mg/dl, p = .04), elevated fasting non-esterified fatty acid (NEFA) concentrations (+0.1 mmol/L, p = .001) and enhanced fat oxidation (p < .001) without modifying step counts or PA intensity. Inclusion of daily exercise increased step count (+4,700 steps/day, p < .001) and decreased the insulin response to a meal (p = .01) but did not prevent the increased peak glucose response or elevated NEFA levels. The weekend recovery period improved fasting glucose (p = .02), insulin (p = .02), NEFA concentrations (p = .001) and HOMA-IR (p < .01) despite reduced steps (p < .01) and increased sedentary time (p < .01). Abdominal adipose tissue (AT) samples, obtained after baseline, SR and exercise, did not differ in lipolytic capacity following SR. Fatty acid synthase protein content tended to increase following SR (p = .07), but not following exercise. In a free-living setting, SR adversely affected circulating NEFAs, fuel oxidation and peak glucose response but did not directly affect glucose tolerance or AT lipolysis. SR-associated metabolic impairments were not mitigated by exercise, yet recovery sleep completely rescued its adverse effects on glucose metabolism.

Postprandial hypoglycemia after bariatric surgery is an exigent disorder, often impacting the quality of life. Distinguishing clinically relevant hypoglycemic episodes from symptoms of other origin can be challenging. Diagnosis is demanding and often requires an extensive testing such as prolonged glucose tolerance or mixed-meal test. Therefore, we investigated whether baseline parameters of patients after gastric bypass with suspected hypoglycemia can predict the diagnosis.
We analyzed data from 35 patients after gastric bypass with suspected postprandial hypoglycemia and performed a standardized mixed-meal test. Hypoglycemia was defined by the appearance of typical symptoms, low plasma glucose, and relief of symptoms following glucose administration. Parameters that differed in patients with and without hypoglycemia during MMT were identified and evaluated for predictive precision using receiver operating characteristic (ROC) areas under the curve (AUC).
Out of 35 patients, 19 (54%) developed symptomatic hypoglycemia as a result of exaggerated insulin and C-peptide release in response to the mixed-meal. Hypoglycemic patients exhibited lower glycosylated hemoglobin A1c (HbA1c) and higher absolute and relative weight loss from pre-surgery to study date. HbA1c and absolute weight loss alone could achieve acceptable AUCs in ROC analyses (0.76 and 0.72, respectively) but a combined score of absolute weight loss divided by HbA1c (0.78) achieved the best AUC.
HbA1c and weight loss differed in patients with and without symptomatic hypoglycemia during mixed-meal test. These baseline parameters could be used for screening of postprandial hypoglycemia in patients after gastric bypass and may facilitate the selection of patients requiring further evaluation.

To date, studies of patients with islet transplantation addressing intermittently scanned continuous glucose monitoring profile and the flexibility of the graft islet function under different doses of insulin administration, both of which reflect the real daily life of patients, are quite limited. Here, we report a case of a 46-year-old woman who received islet transplantation after kidney transplantation. The patient was followed up over a period of 2 years after initial islet transplantation. Our results show that intermittently scanned continuous glucose monitoring can be useful for monitoring the reduction of glycemic variability, and suggest the appropriate regulation of insulin secretion from graft islets during mixed-meal test by using different doses of exogenous insulin administration. Additionally, during the 2-year observational period, glucagon elevation was detected only at hypoglycemia, whereas the level was within the normal range at normoglycemia or hyperglycemia.

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Metabolic challenge tests may be a valuable tool to magnify the effects of diet on health. The use of transcriptomics enables a more extensive characterization of the effects of diet. The question remains whether transcriptome time-course analyses during challenge tests will deliver more information on the effect of diet than a static fasting measurement. A dietary intervention known to improve health is energy restriction (ER). Seventy-two healthy, overweight men and women aged 50-65 were subjected to an oral glucose tolerance test (OGTT) and a mixed-meal test (MMT) before and after 12 wk of a 20% ER diet or control diet. Whole-genome gene expression of peripheral blood mononuclear cells was performed before and after the intervention. This was done during fasting, during the OGTT at 30, 60, and 120 min, and during the MMT at 60, 120, 240, and 360 min. Upon ER, the OGTT resulted in a faster and more pronounced down-regulation in gene expression of oxidative phosphorylation, cell adhesion, and DNA replication compared with the control. The MMT showed less-consistent effects. The OGTT combined with transcriptomics can be used to measure dynamic cellular adaptation upon an intervention that cannot be determined with a static fasting measurement.-Van Bussel, I. P. G., Fazelzadeh, P., Frost, G. S., Rundle, M., Afman, L. A. Measuring phenotypic flexibility by transcriptome time-course analyses during challenge tests before and after energy restriction.

Post-bypass postprandial hypoglycemia (PPH) is a frequent complication of Roux-en-Y Gastric Bypass (RYGB) but predictors remain poorly identified and are needed to assess individual risk. After RYGB, exaggerated secretion of glucagon-like peptide-1 (GLP-1) and insulin could lead to PPH, but other proglucagon-derived peptides, including glicentin and glucagon, could also contribute to this phenomenon.
To identify biological hypoglycemia in relation to the secretion of proglucagon-derived peptides during a mixed-meal test (MMT) in RYGB patients.
University hospital.
Twenty RYGB patients reporting symptoms consistent with PPH were examined 36.9 ± 5.1 months after surgery. Plasma levels of glucose, c-peptide, glucagon, GLP-1 and glicentin were assessed before and during MMT. Patients with postprandial hypoglycemia ≤3 mM (54 mg/dL) during MMT were assigned to HYPO group and compared with patients not exhibiting hypoglycemia (NONHYPO group).
Seven patients displayed hypoglycemia ≤3 mM (HYPO) during the MMT. Lower fasting glycemia (4.5 mM versus 5.3 mM, P<.05) and higher fasting glicentin (22.6 pM versus 14.0 pM, P<.05) were observed in HYPO versus NONHYPO patients. Fasting glicentin was inversely correlated with postprandial nadir glucose. Examining the receiver-operating characteristics curve analysis, a cutoff of 17.2 pM for fasting glicentin identified PPH with 85.7% sensitivity and 53.8% specificity. All patients exhibited a similar increase of postprandial GLP-1, glucagon, and glicentin secretions that correlated with each other.
These results suggest that fasting glicentin is a potential biomarker to examine in operated-obese patients at risk of developing PPH. Further studies are needed before proposing fasting glicentin as a predictive factor of PPH.

BACKGROUND: Impaired energy metabolism is a possible mechanism that contributes to insulin resistance and ectopic fat storage.
OBJECTIVE: We examined whether meal ingestion differently affects hepatic phosphorus metabolites in insulin-sensitive and insulin-resistant humans.
METHODS: Young, lean, insulin-sensitive humans (CONs) [mean ± SD body mass index (BMI; in kg/m(2)): 23.2 ± 1.5]; insulin-resistant, glucose-tolerant, obese humans (OBEs) (BMI: 34.3 ± 1.7); and type 2 diabetes patients (T2Ds) (BMI: 32.0 ± 2.4) were studied (n = 10/group). T2Ds (61 ± 7 y old) were older (P < 0.001) than were OBEs (31 ± 7 y old) and CONs (28 ± 3 y old). We quantified hepatic γATP, inorganic phosphate (Pi), and the fat content [hepatocellular lipids (HCLs)] with the use of (31)P/(1)H magnetic resonance spectroscopy before and at 160 and 240 min after a high-caloric mixed meal. In a subset of volunteers, we measured the skeletal muscle oxidative capacity with the use of high-resolution respirometry. Whole-body insulin sensitivity (M value) was assessed with the use of hyperinsulinemic-euglycemic clamps.
RESULTS: OBEs and T2Ds were similarly insulin resistant (M value: 3.5 ± 1.4 and 1.9 ± 2.5 mg · kg(-1) · min(-1), respectively; P = 0.9) and had 12-fold (P = 0.01) and 17-fold (P = 0.002) higher HCLs, respectively, than those of lean persons. Despite comparable fasting hepatic γATP concentrations, the maximum postprandial increase of γATP was 6-fold higher in OBEs (0.7 ± 0.2 mmol/L; P = 0.03) but only tended to be higher in T2Ds (0.6 ± 0.2 mmol/L; P = 0.09) than in CONs (0.1 ± 0.1 mmol/L). However, in the fasted state, muscle complex I activity was 53% lower (P = 0.01) in T2Ds but not in OBEs (P = 0.15) than in CONs.
CONCLUSIONS: Young, obese, nondiabetic humans exhibit augmented postprandial hepatic energy metabolism, whereas elderly T2Ds have impaired fasting muscle energy metabolism. These findings support the concept of a differential and tissue-specific regulation of energy metabolism, which can occur independently of insulin resistance. This trial was registered at clinicaltrials.gov as NCT01229059.

Acylcarnitines are derived from mitochondrial acyl-CoA metabolism and have been associated with diet-induced insulin resistance. However, plasma acylcarnitine profiles have been shown to poorly reflect whole body acylcarnitine metabolism. We aimed to clarify the individual role of different organ compartments in whole body acylcarnitine metabolism in a fasted and postprandial state in a porcine transorgan arteriovenous model. Twelve cross-bred pigs underwent surgery where intravascular catheters were positioned before and after the liver, gut, hindquarter muscle compartment, and kidney. Before and after a mixed meal, we measured acylcarnitine profiles at several time points and calculated net transorgan acylcarnitine fluxes. Fasting plasma acylcarnitine concentrations correlated with net hepatic transorgan fluxes of free and C2- and C16-carnitine. Transorgan acylcarnitine fluxes were small, except for a pronounced net hepatic C2-carnitine production. The peak of the postprandial acylcarnitine fluxes was between 60 and 90 min. Acylcarnitine production or release was seen in the gut and liver and consisted mostly of C2-carnitine. Acylcarnitines were extracted by the kidney. No significant net muscle acylcarnitine flux was observed. We conclude that liver has a key role in acylcarnitine metabolism, with high net fluxes of C2-carnitine both in the fasted and fed state, whereas the contribution of skeletal muscle is minor. These results further clarify the role of different organ compartments in the metabolism of different acylcarnitine species.