A vertical diatomic artificial molecule in the intermediate coupling regime in a parallel and perpendicular magnetic field

We present experimental results for the ground state electrochemical potentials of a few electron semiconductor artificial molecule made by vertically coupling two quantum dots, in the intermediate coupling regime, in perpendicular and parallel magnetic fields up to 5 T. We perform a quantitative analysis based on local-spin density functional theory. The agreement between theoretical and experimental results is good, and the phase transitions are well reproduced.Comment: Typeset using Revtex, 13 pages and 8 Postscript figure

Maternal use of dietary supplements during pregnancy is not associated with coeliac disease in the offspring: The Environmental Determinants of Diabetes in the Young (TEDDY) study.

Perinatal exposure to nutrients and dietary components may affect the risk for coeliac disease (CD). We investigated the association between maternal use of vitamin D, n-3 fatty acids (FA) and Fe supplements during pregnancy and risk for CD autoimmunity (CDA) and CD in the offspring. Children at increased genetic risk were prospectively followed from birth in The Environmental Determinants of Diabetes in the Young (TEDDY) study. CDA was defined as having persistently positive tissue transglutaminase autoantibodies (tTGA). Diagnosis of CD was either biopsy-confirmed or considered likely if having persistently elevated levels of tTGA>100 AU. Of 6627 enrolled children, 1136 developed CDA at a median 3·1 years of age (range 0·9-10) and 409 developed CD at a median 3·9 years of age (range 1·2-11). Use of supplements containing vitamin D, n-3 FA and Fe was recalled by 66, 17 and 94 % of mothers, respectively, at 3-4 months postpartum. The mean cumulative intake over the entire pregnancy was 2014 μg vitamin D (sd 2045 μg), 111 g n-3 FA (sd 303 g) and 8806 mg Fe (sd 7017 mg). After adjusting for country, child's human leucocyte antigen genotype, sex, family history of CD, any breast-feeding duration and household crowding, Cox's proportional hazard ratios did not suggest a statistically significant association between the intake of vitamin D, n-3 FA or Fe, and risk for CDA or CD. Dietary supplementation during pregnancy may help boost nutrient intake, but it is not likely to modify the risk for the disease in the offspring

Predicting progression to type 1 diabetes from ages 3 to 6 in islet autoantibody positive TEDDY children.

Objective The capacity to precisely predict progression to type 1 diabetes (T1D) in young children over a short time span is an unmet need. We sought to develop a risk algorithm to predict progression in children with high-risk human leukocyte antigen (HLA) genes followed in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Methods Logistic regression and 4-fold cross-validation examined 38 candidate predictors of risk from clinical, immunologic, metabolic, and genetic data. TEDDY subjects with at least one persistent, confirmed autoantibody at age 3 were analyzed with progression to T1D by age 6 serving as the primary endpoint. The logistic regression prediction model was compared to two non-statistical predictors, multiple autoantibody status, and presence of insulinoma-associated-2 autoantibodies (IA-2A). Results A total of 363 subjects had at least one autoantibody at age 3. Twenty-one percent of subjects developed T1D by age 6. Logistic regression modeling identified 5 significant predictors - IA-2A status, hemoglobin A1c, body mass index Z-score, single-nucleotide polymorphism rs12708716_G, and a combination marker of autoantibody number plus fasting insulin level. The logistic model yielded a receiver operating characteristic area under the curve (AUC) of 0.80, higher than the two other predictors; however, the differences in AUC, sensitivity, and specificity were small across models. Conclusions This study highlights the application of precision medicine techniques to predict progression to diabetes over a 3-year window in TEDDY subjects. This multifaceted model provides preliminary improvement in prediction over simpler prediction tools. Additional tools are needed to maximize the predictive value of these approaches