Differential hypothalamic leptin sensitivity in obese rat offspring exposed to maternal and postnatal intake of chocolate and soft drink.

BACKGROUND/OBJECTIVE: Intake of high-energy foods and maternal nutrient overload increases the risk of metabolic diseases in the progeny such as obesity and diabetes. We hypothesized that maternal and postnatal intake of chocolate and soft drink will affect leptin sensitivity and hypothalamic astrocyte morphology in adult rat offspring. METHODS: Pregnant Sprague-Dawley rats were fed ad libitum chow diet only (C) or with chocolate and high sucrose soft drink supplement (S). At birth, litter size was adjusted into 10 male offspring per mother. After weaning, offspring from both dietary groups were assigned to either S or C diet, giving four groups until the end of the experiment at 26 weeks of age. RESULTS: As expected, adult offspring fed the S diet post weaning became obese (body weight: P<0.01, %body fat per kg: P<0.001) and this was due to the reduced energy expenditure (P<0.05) and hypothalamic astrogliosis (P<0.001) irrespective of maternal diet. Interesting, offspring born to S-diet-fed mothers and fed the S diet throughout postnatal life became obese despite lower energy intake than controls (P<0.05). These SS offspring showed increased feed efficiency (P<0.001) and reduced fasting pSTAT3 activity (P<0.05) in arcuate nucleus (ARC) compared with other groups. The findings indicated that the combination of the maternal and postnatal S-diet exposure induced persistent changes in leptin signalling, hence affecting energy balance. Thus, appetite regulation was more sensitive to the effect of leptin than energy expenditure, suggesting differential programming of leptin sensitivity in ARC in SS offspring. Effects of the maternal S diet were normalized when offspring were fed a chow diet after weaning. CONCLUSIONS: Maternal intake of chocolate and soft drink had long-term consequences for the metabolic phenotype in the offspring if they continued on the S diet in postnatal life. These offspring displayed obesity despite lowered energy intake associated with alterations in hypothalamic leptin signalling.

Impact of injection speed and volume on perceived pain during subcutaneous injections into the abdomen and thigh: a single-centre, randomized controlled trial.

AIM: The aim of this study was to assess pain associated with subcutaneous injection into the abdomen and thigh of different combinations of injection speeds and volumes. METHODS: The study was a single-centre, one-visit, double-blinded, randomized controlled trial in 82 adults with type 1 or type 2 diabetes receiving daily injections of insulin or glucagon-like peptide-1 (GLP-1) agonists. Participants received 17 subcutaneous injections (12 in abdomen, 5 in thigh) of saline at different injection speeds (150, 300 and 450 µl/s), with different volumes (400, 800, 1200 and 1600 µl), and two needle insertions without any injection. Pain was evaluated on a 100-mm visual analogue scale (VAS) (0 mm no pain, 100 mm worst pain) and on a yes/no scale for pain acceptability. RESULTS: Injection speed had no impact on injection pain (p = 0.833). Injection of larger volumes caused significantly more pain [VAS least square mean differences 1600 vs. 400 µl, 7 · 2 mm (95% confidence interval - CI; 4.6-9.7; p < 0.0001); 1600 vs. 800 µl, 7.2 mm (4.4-10.0; p < 0.0001); 1200 vs. 400 µl, 3.5 mm (0.4-6.6; p = 0.025) and 1200 vs. 800 µl, 3.6 mm (0.4-6.7; p = 0.027)]. Significantly more pain occurred in the thigh versus the abdomen [9.0 mm (6.7-11.3; p < 0.0001)]. CONCLUSIONS: Injection speed had no effect on injection pain, whereas higher injection volumes caused more pain. The results of this study may be of value for guiding patients to use the appropriate injection site and technique to reduce their injection pain. Furthermore, these findings may have important implications for the development of new injection devices and drug formulations for clinical practice.

Pharmacokinetics following continuous subcutaneous insulin infusion of insulin aspart with or without initial subcutaneous bolus.

AIM: To evaluate time to steady state insulin concentration (C(ss)) following continuous subcutaneous insulin infusion (CSII) of insulin aspart (IAsp) with or without an initial s.c. bolus. METHODS: In random order 10 healthy volunteers were given a basal insulin infusion rate (0.5 U/h) for 8 h with or without an initial s.c. bolus (1.4 U). Serum IAsp was measured until 3 h after infusion was stopped. RESULTS: An overshoot of IAsp was seen before C(ss) was achieved following an initial bolus of insulin as compared to no bolus. The apparent half-life (t((1/2))) with or without bolus did not differ (p = 0.15). Time to steady state (T(ss)) was evaluated in two ways: (1) T(ss) defined as the first point within an interval of C(ss)+/- 2 x CV was 233 vs. 166 min with and without a bolus respectively (p = 0.068). (2) A t-test was performed for each concentration-time point vs. mean C(ss), and the first point with no significance was defined, T(ss). This gave 208 (p = 0.09) and 178 min (p = 0.24) with and without bolus respectively. Mathematical modelling suggests that an ideal mean bolus should be 0.89 U, and that this bolus dose may result in a shorter T(ss). CONCLUSION: A bolus of 1.4 U resulted in an overshoot of serum IAsp before C(ss) and a longer period before C(ss) is achieved. Mathematical modelling suggests that a mean bolus of 0.89 U would result in a faster achievement of C(ss) compared to no bolus.

A study of trained clinicians' blood glucose predictions based on diaries of people with type 1 diabetes.

OBJECTIVES: How accurate can trained clinicians predict blood glucose concentrations? Good clinical treatment is, among other things, related to understanding the factors influencing blood glucose level. We analyze trained clinician's prediction accuracy in comparison with selected computer-implemented prediction algorithms and models. METHODS: We have in this study included diaries of 12 people with type 1 diabetes. This test group consists of seven males and five females, ages 24 to 60, HbA1c 6.0 to 8.9 and a BMI between 20 and 28 kg/m2. Eight experienced clinicians tried to predict the blood glucose measurements based on minimum three days of diary history. Selected prediction algorithms and models were used for comparison. The reason we focus on type 1 diabetes is that it has the most critical insulin requirement, so accurate prediction can be more critical than for type 2. RESULTS: An accuracy of 28.5% and an error of 26.7% were found from predictions made by the clinicians. A physiological model and an artificial intelligence model showed higher accuracy of 32.2% and 34.2% in comparison with the clinicians (p<0.05). A simple predictor algorithm based on the mean blood glucose history showed significant (p<0.05) lower total root mean square error compared to predictions made by the clinicians. CONCLUSION: To predict blood glucose level from diaries has shown to be profoundly difficult even for experienced clinicians in comparison with predictions from computer algorithms and models. This suggests that computer-based systems incorporating predicting algorithms and models are likely to contribute positively to the day-to-day treatment of people with diabetes.