Key aspects of the expression of long-term potentiation (LTP) and long-term depression (LTD) remain unresolved despite decades of investigation. Alterations in postsynaptic glutamate receptors are believed to contribute to the expression of various forms of LTP and LTD, but the relative importance of presynaptic mechanisms is controversial. In addition, while aggregate synaptic input to a cell can undergo sequential and graded (incremental) LTP and LTD, it has been suggested that individual synapses may only support binary changes between initial and modified levels of strength. We have addressed these issues by combining electrophysiological methods with two-photon optical quantal analysis of plasticity at individual active (non-silent) Schaffer collateral synapses on CA1 pyramidal neurons in acute slices of hippocampus from adolescent rats. We find that these synapses sustain graded, bidirectional long-term plasticity. Remarkably, changes in potency are small and insignificant; long-term plasticity at these synapses is expressed overwhelmingly via presynaptic changes in reliability of transmitter release.

SUMMARYThe theoretical principles and practical implementation of a new method for multivariate data analysis, maximum likelihood principal component analysis (MLPCA), are described. MLCPA is an analog to principal component analysis (PCA) that incorporates information about measurement errors to develop PCA models that are optimal in a maximum likelihood sense. The theoretical foundations of MLPCA are initially established using a regression model and extended to the framework of PCA and singular value decomposition (SVD). An efficient and reliable algorithm based on an alternating regression method is described. Generalization of the algorithm allows its adaptation to cases of correlated errors provided that the error covariance matrix is known. Models with intercept terms can also be accommodated. Simulated data and near-infrared spectra, with a variety of error structures, are used to evaluate the performance of the new algorithm. Convergence times depend on the error structure but are typically around a few minutes. In all cases, models determined by MLPCA are found to be superior to those obtained by PCA when non-uniform error distributions are present, although the level of improvement depends on the error structure of the particular data set.

B. ANTHONY ARMSON, MD, FRCS (C) 2 M. VANDENHOF, MD, FRCS (C)2 OBJECTIVE -To determine the recurrence rate of gestational diabetes (GDM) during a subsequent pregnancy among women who had GDM during an index pregnancy and to identify factors associated with the probability of recurrence.RESEARCH DESIGN AND METHODS -A retrospective longitudinal study was performed in Nova Scotia, Canada, of women who were diagnosed as having GDM during a pregnancy between the years of 1980 and 1996 and who had at least one subsequent pregnancy during this time period. When only the index and first subsequent pregnancy were analyzed, the cohort included 651 women. The recurrence rate of GDM in the pregnancy after the pregnancy with the initial diagnosis of GDM was determined. Multivariate regression models were constructed to model the recurrence of GDM in a subsequent pregnancy as functions of potential predictors to estimate RRs and CIs.RESULTS -The rate of recurrence of GDM in the pregnancy subsequent to the index pregnancy was found to be 35.6% (95% CI ϭ 31.9 -39.3%). Multivariate regression models showed that infant birth weight in the index pregnancy and maternal prepregnancy weight before the subsequent pregnancy were predictive of recurrent GDM.CONCLUSIONS -In this large cohort of women, slightly more than one-third of the subjects had diabetes in a subsequent pregnancy, which is consistent with recurrence rates in other predominately white populations. Strategies to reduce the occurrence of neonatal macrosomia and maternal prepregnancy obesity may help lower the rate of recurrence of GDM. Diabetes Care 24:659 -662, 2001I t is estimated that gestational diabetes (GDM) recurs in 30 -69% of subsequent pregnancies after a pregnancy with GDM (1-6). One of the major risk factors for developing GDM is having had a previous pregnancy complicated by the disease. Other factors that have been identified as predictive of recurrent GDM include obesity, multiparity, early diagnosis of GDM during the initial pregnancy, need for insulin during the initial pregnancy, macrosomia during the initial pregnancy, advanced maternal age, maternal prepregnancy weight during the initial pregnancy, and an increase in prepregnancy weight between the initial and subsequent pregnancies.Whereas previous studies have provided useful information regarding recurrence rates and factors predictive for recurrent GDM, they have been limited by relatively small numbers of subjects. The purpose of this study was to examine the recurrence rates of GDM in a large population-based cohort of women who had GDM during an initial pregnancy and to examine factors associated with recurrence.

Summary Background Research into lifetime costs of obesity in childhood is growing. This review synthesizes that knowledge. Methodology A computerized search of the international literature since 2000 was conducted. Mean total lifetime healthcare and productivity costs were estimated and inflated to 2014 Irish euros. Results This resulted in 13 published articles. The methodology used in these studies varied widely, and only one study estimated both healthcare and productivity costs. Cognizant of this heterogeneity, the mean total lifetime cost of a child or adolescent with obesity was €149,206 (range, €129,410 to €178,933) for a boy and €148,196 (range, €136,576 to €173,842) for a girl. This was divided into an average of €16,229 (range, €6,580 to €35,810) in healthcare costs and €132,977 (range, €122,830 to €143,123) in productivity losses for boys and €19,636 (range, €8,016 to €45,283) and €128,560, respectively, for girls. Income penalty accounted for the greater part of productivity costs, amounting to €97,118 (range, €86,971 to €107,264) per male adolescent with obesity and €126,108 per female adolescent. Conclusions Healthcare costs and income penalty appear greater in girls while costs because of workdays lost seem greater in boys. There is proportionality between body mass index and costs. Productivity costs are greater than healthcare costs.

BackgroundWhile there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objective of the current study was to identify predictors of fetal growth abnormalities using logistic regression and machine learning methods, and compare diagnostic properties in a population-based sample of infants.MethodsData for 30,705 singleton infants born between 2009 and 2014 to mothers resident in Nova Scotia, Canada was obtained from the Nova Scotia Atlee Perinatal Database. Primary outcomes were small (SGA) and large for gestational age (LGA). Maternal characteristics pre-pregnancy and at 26 weeks were studied as predictors. Logistic regression and select machine learning methods were used to build the models, stratified by parity. Area under the curve was used to compare the models; relative importance of predictors was compared qualitatively.Results7.9% and 13.5% of infants were SGA and LGA, respectively; 48.6% of births were to primiparous women and 51.4% were to multiparous women. Prediction of SGA and LGA was poor to fair (area under the curve 60–75%) and improved with increasing parity and pregnancy information. Smoking, previous low birthweight infant, and gestational weight gain were important predictors for SGA; pre-pregnancy body mass index, gestational weight gain, and previous macrosomic infant were the strongest predictors for LGA.ConclusionsThe machine learning methods used in this study did not offer any advantage over logistic regression in the prediction of fetal growth abnormalities. Prediction accuracy for SGA and LGA based on maternal information is poor for primiparous women and fair for multiparous women.Electronic supplementary materialThe online version of this article (10.1186/s12884-018-1971-2) contains supplementary material, which is available to authorized users.