Rationales, design and recruitment for the Elfe longitudinal study

Background Many factors act simultaneously in childhood to influence health status, life chances and well being, including pre-birth influences, the environmental pollutants of early life, health status but also the social influences of family and school. A cohort study is needed to disentangle these influences and explore attribution. Methods Elfe will be a nationally representative cohort of 20 000 children followed from birth to adulthood using a multidisciplinary approach. The cohort will be based on the INSEE Permanent Demographic Panel (EDP) established using census data and civil records. The sample size has been defined in order to match the representativeness criteria and to obtain some prevalence estimation, but also to address the research area of low exposure/rare effects. The cohort will be based on repeated surveys by face to face or phone interview (at birth and each year) as well as medical interview (at 2 years) and examination (at 6 years). Furthermore, biological samples will be taken at birth to evaluate the foetal exposition to toxic substances, environmental sensors will be placed in the child's homes. Pilot studies have been initiated in 2007 (500 children) with an overall acceptance rate of 55% and are currently under progress, the 2-year survey being carried out in October this year. Discussion The longitudinal study will provide a unique source of data to analyse the development of children in their environment, to study the various factors interacting throughout the life course up to adulthood and to determine the impact of childhood experience on the individual's physical, psychological, social and professional development

Intelligent Threshold Prediction for Hybrid Mesh Segmentation Through Artificial Neural Network

Accurate and reliable Area deviation factor (threshold) is one of the decisive factors in hybrid mesh segmentation. Inadequate threshold leads to under-segmentation or over-segmentation. Setting the optimal threshold is a difficult task for a layman. This proposed method, automatically predicts the threshold using artificial neural networks (ANN). ANN predicts the threshold by considering mesh quality of Computer-Aided Design (CAD) mesh model as input feature vectors. Extensive testing on benchmark test cases validates ANN prediction model, and based on Levenberg-Marquardt back propagation (LM-BP) improves the accuracy and stability of prediction. The efficacy of the approach is quantified by measuring coverage. The ANN predicts the threshold elegantly using LM-BP algorithm with coverage for hybrid mesh segmentation greater than 95%. The novelty of the proposed method lies in the “mesh quality”-based threshold prediction through ANN. The predicted threshold finds application in automatic feature recognition from CAD mesh model using hybrid mesh segmentation

Maternal but Not Fetal FADS Gene Variants Modify the Association between Maternal Long-Chain PUFA Intake in Pregnancy and Birth Weight

Several studies have shown a positive association between maternal fish intake in pregnancy and pregnancy duration and child birth weight (BW), probably due to fish n-3 (omega-3) long-chain polyunsaturated fatty acids (LC-PUFAs). n-3 LC-PUFAs can also be synthesized endogenously, and their synthesis depends on single nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) gene encoding for FADS. We assessed the associations of maternal docosahexaenoic acid (DHA) intake in pregnancy with pregnancy duration and BW and investigated whether these associations are modified by maternal or fetal FADS SNP genotypes. We hypothesized that we would find stronger associations in minor allele homozygous mothers or fetuses due to their lower n-3 LC-PUFA endogenous synthesis and hence higher dependence on dietary supply. Data on maternal diet, pregnancy duration, and BW were available for 2622 mother-child pairs from the KOALA (Kind, Ouders en gezondheid: Aandacht voor Leefstijl en Aanleg) Birth Cohort Study. The rs174556 FADS SNP was genotyped in 1516 mothers and 1515 children. Associations and gene-diet interactions were tested with linear regression adjusting for potential confounders, including intake of other PUFAs. Women at the 75th percentile of DHA intake had 0.7-d longer pregnancies (P = 0.016) and 28-g heavier infants (P = 0.039) than did women at the 25th percentile of intake. Associations with arachidonic acid intake were of the same order but in the opposite direction. Mothers who were homozygous for the minor allele had 2-d shorter pregnancies (P = 0.035) and infants who were nearly 140 g lighter (P = 0.006) than did mothers who were major allele homozygotes. Post hoc analyses revealed that they had higher prepregnancy BMI (P = 0.020). Among the women homozygous for the minor allele, those at the 75th percentile of DHA intake had 226-g heavier infants than those at the 25th percentile of intake (P = 0.030), whereas DHA intake was not significantly associated with BW in major allele carriers. These findings suggest that maternal and fetal fatty acid requirements during pregnancy depend on maternal genetic variation in LC-PUFA synthesis