Sex differences in the programming effects of prenatal stress on psychopathology and stress responses: an evolutionary perspective

There is strong evidence from animal studies that prenatal stress has different effects on male and female offspring. In general, although not always, prenatal stress increases anxiety, depression and stress responses, both hypothalamic–pituitary–adrenal and cardiovascular, in female offspring rather than in male. Males are more likely to show learning and memory deficits. There have been few studies so far in humans which differentiate effects of prenatal stress on male and female psychopathology. Some studies support the animal models, but the evidence is inconsistent. The mediating mechanisms for any sex specific effects are little understood, but there is evidence that placental function can differ depending on the sex of the fetus. We suggest that there may be an evolutionary reason for any sex differences in the long term effects of prenatal stress. In a stressful environment it may be adaptive for females, who are more likely to stay in one place and look after children, to be more vigilant, alert to danger and thus show more stress responsiveness. This can give rise to a more anxious or depressed phenotype. With males it may be more adaptive to go out and explore new environments, compete with other males, and be more aggressive. For this it may help to be less responsive to external stressors. More research is needed into sex differences in the effects of prenatal stress in humans, to test these ideas.

Evidence for sex differences in fetal programming of physiological stress reactivity in infancy

Associations between low birth weight and prenatal anxiety and later psychopathology may arise from programming effects likely to be adaptive under some, but not other, environmental exposures and modified by sex differences. If physiological reactivity, which also confers vulnerability or resilience in an environment-dependent manner, is associated with birth weight and prenatal anxiety, it will be a candidate to mediate the links with psychopathology. From a general population sample of 1,233 first-time mothers recruited at 20 weeks gestation, a sample of 316 stratified by adversity was assessed at 32 weeks and when their infants were aged 29 weeks (N = 271). Prenatal anxiety was assessed by self-report, birth weight from medical records, and vagal reactivity from respiratory sinus arrhythmia during four nonstressful and one stressful (still-face) procedure. Lower birth weight for gestational age predicted higher vagal reactivity only in girls (interaction term, p = .016), and prenatal maternal anxiety predicted lower vagal reactivity only in boys (interaction term, p = .014). These findings are consistent with sex differences in fetal programming, whereby prenatal risks are associated with increased stress reactivity in females but decreased reactivity in males, with distinctive advantages and penalties for each sex.

Maternal antenatal anxiety, postnatal stroking and emotional problems in children: outcomes predicted from pre and postnatal programming hypotheses

Background Mothers' self-reported stroking of their infants over the first weeks of life modifies the association between prenatal depression and physiological and emotional reactivity at 7 months, consistent with animal studies of the effects of tactile stimulation. We now investigate whether the effects of maternal stroking persist to 2.5 years. Given animal and human evidence for sex differences in the effects of prenatal stress we compare associations in boys and girls. Method From a general population sample of 1233 first-time mothers recruited at 20 weeks gestation we drew a random sample of 316 for assessment at 32 weeks, stratified by reported inter-partner psychological abuse, a risk indicator for child development. Of these mothers, 243 reported at 5 and 9 weeks how often they stroked their infants, and completed the Child Behavior Checklist (CBCL) at 2.5 years post-delivery. Results There was a significant interaction between prenatal anxiety and maternal stroking in the prediction of CBCL internalizing (p = 0.001) and anxious/depressed scores (p < 0.001). The effects were stronger in females than males, and the three-way interaction prenatal anxiety × maternal stroking × sex of infant was significant for internalizing symptoms (p = 0.003). The interactions arose from an association between prenatal anxiety and internalizing symptoms only in the presence of low maternal stroking. Conclusions The findings are consistent with stable epigenetic effects, many sex specific, reported in animal studies. While epigenetic mechanisms may be underlying the associations, it remains to be established whether stroking affects gene expression in humans.

Fetal programming of adipose tissue function: an evolutionary perspective

Obesity is an escalating threat of pandemic proportions and has risen to such unrivaled prominence in such a short period of time that it has come to define a whole generation in many countries around the globe. The burden of obesity, however, is not equally shared among the population, with certain ethnicities being more prone to obesity than others, while some appear to be resistant to obesity altogether. The reasons behind this ethnic basis for obesity resistance and susceptibility, however, have remained largely elusive. In recent years, much evidence has shown that the level of brown adipose tissue thermogenesis, which augments energy expenditure and is negatively associated with obesity in both rodents and humans, varies greatly between ethnicities. Interestingly, the incidence of low birth weight, which is associated with an increased propensity for obesity and cardiovascular disease in later life, has also been shown to vary by ethnic background. This review serves to reconcile ethnic variations in BAT development and function with ethnic differences in birth weight outcomes to argue that the variation in obesity susceptibility between ethnic groups may have its origins in the in utero programming of BAT development and function as a result of evolutionary adaptation to cold environments.

Enzymatically-triggered, isothermally responsive polymers: re-programming poly(oligoethylene glycols) to respond to phosphatase

Polymers which can respond to externally applied stimuli have found much application in the biomedical field due to their (reversible) coil–globule transitions. Polymers displaying a lower critical solution temperature are the most commonly used, but for blood-borne (i.e., soluble) biomedical applications the application of heat is not always possible, nor practical. Here we report the design and synthesis of poly(oligoethylene glycol methacrylate)-based polymers whose cloud points are easily varied by alkaline phosphatase-mediated dephosphorylation. By fine-tuning the density of phosphate groups on the backbone, it was possible to induce an isothermal transition: A change in solubility triggered by removal of a small number of phosphate esters from the side chains activating the LCST-type response. As there was no temperature change involved, this serves as a model of a cell-instructed polymer response. Finally, it was found that both polymers were non cytotoxic against MCF-7 cells (at 1 mg·mL–1), which confirms promise for biomedical applications.

An approximate dynamic programming approach for improving accuracy of lossy data compression by Bloom filters

Bloom filters are a data structure for storing data in a compressed form. They offer excellent space and time efficiency at the cost of some loss of accuracy (so-called lossy compression). This work presents a yes-no Bloom filter, which as a data structure consisting of two parts: the yes-filter which is a standard Bloom filter and the no-filter which is another Bloom filter whose purpose is to represent those objects that were recognised incorrectly by the yes-filter (that is, to recognise the false positives of the yes-filter). By querying the no-filter after an object has been recognised by the yes-filter, we get a chance of rejecting it, which improves the accuracy of data recognition in comparison with the standard Bloom filter of the same total length. A further increase in accuracy is possible if one chooses objects to include in the no-filter so that the no-filter recognises as many as possible false positives but no true positives, thus producing the most accurate yes-no Bloom filter among all yes-no Bloom filters. This paper studies how optimization techniques can be used to maximize the number of false positives recognised by the no-filter, with the constraint being that it should recognise no true positives. To achieve this aim, an Integer Linear Program (ILP) is proposed for the optimal selection of false positives. In practice the problem size is normally large leading to intractable optimal solution. Considering the similarity of the ILP with the Multidimensional Knapsack Problem, an Approximate Dynamic Programming (ADP) model is developed making use of a reduced ILP for the value function approximation. Numerical results show the ADP model works best comparing with a number of heuristics as well as the CPLEX built-in solver (B&B), and this is what can be recommended for use in yes-no Bloom filters. In a wider context of the study of lossy compression algorithms, our researchis an example showing how the arsenal of optimization methods can be applied to improving the accuracy of compressed data.

Perinatal salt restriction: A new pathway to programming adiposity indices in adult female Wistar rats

Low birth weight has been associated with increased obesity in adulthood. It has been shown that dietary salt restriction during intrauterine life induces low birth weight and insulin resistance in adult Wistar rats. The present study had a two-fold objective: to evaluate the effects that low salt intake during pregnancy and lactation has on the amount and distribution of adipose tissue; and to determine whether the phenotypic changes in fat mass in this model are associated with alterations in the activity of the renin-angiotensin system. Maternal salt restriction was found to reduce birth weight in male and female offspring. In adulthood, the female offspring of dams fed the low-salt diet presented higher adiposity indices than those seen in the offspring of dams fed a normal-salt diet. This was attributed to the fact that adipose tissue mass (retroperitoneal but not gonadal, mesenteric or inguinal) was greater in those rats than in the offspring of dams fed a normal diet. The adult offspring of dams fed the low-salt diet, compared to those dams fed a normal-salt diet, presented the following: plasma leptin levels higher in males and lower in females; plasma renin activity higher in males but not in females; and no differences in body weight, mean arterial blood pressure or serum angiotensin-converting enzyme activity. Therefore, low salt intake during pregnancy might lead to the programming of obesity in adult female offspring. (c) 2009 Elsevier Inc. All rights reserved.

An integer linear programming approach for approximate string comparison

We introduce a problem called maximum common characters in blocks (MCCB), which arises in applications of approximate string comparison, particularly in the unification of possibly erroneous textual data coming from different sources. We show that this problem is NP-complete, but can nevertheless be solved satisfactorily using integer linear programming for instances of practical interest. Two integer linear formulations are proposed and compared in terms of their linear relaxations. We also compare the results of the approximate matching with other known measures such as the Levenshtein (edit) distance. (C) 2008 Elsevier B.V. All rights reserved.

A pointcut-based coverage analysis approach for aspect-oriented programs

Aspect-oriented programming (AOP) is a promising technology that supports separation of crosscutting concerns (i.e., functionality that tends to be tangled with, and scattered through the rest of the system). In AOP, a method-like construct named advice is applied to join points in the system through a special construct named pointcut. This mechanism supports the modularization of crosscutting behavior; however, since the added interactions are not explicit in the source code, it is hard to ensure their correctness. To tackle this problem, this paper presents a rigorous coverage analysis approach to ensure exercising the logic of each advice - statements, branches, and def-use pairs - at each affected join point. To make this analysis possible, a structural model based on Java bytecode - called PointCut-based Del-Use Graph (PCDU) - is proposed, along with three integration testing criteria. Theoretical, empirical, and exploratory studies involving 12 aspect-oriented programs and several fault examples present evidence of the feasibility and effectiveness of the proposed approach. (C) 2010 Elsevier Inc. All rights reserved.

Proximal methods for nonlinear programming: double regularization and inexact subproblems

This paper describes the first phase of a project attempting to construct an efficient general-purpose nonlinear optimizer using an augmented Lagrangian outer loop with a relative error criterion, and an inner loop employing a state-of-the art conjugate gradient solver. The outer loop can also employ double regularized proximal kernels, a fairly recent theoretical development that leads to fully smooth subproblems. We first enhance the existing theory to show that our approach is globally convergent in both the primal and dual spaces when applied to convex problems. We then present an extensive computational evaluation using the CUTE test set, showing that some aspects of our approach are promising, but some are not. These conclusions in turn lead to additional computational experiments suggesting where to next focus our theoretical and computational efforts.

Analytic Methods for the Logic of Proofs

The logic of proofs (lp) was proposed as Gdels missed link between Intuitionistic and S4-proofs, but so far the tableau-based methods proposed for lp have not explored this closeness with S4 and contain rules whose analycity is not immediately evident. We study possible formulations of analytic tableau proof methods for lp that preserve the subformula property. Two sound and complete tableau decision methods of increasing degree of analycity are proposed, KELP and preKELP. The latter is particularly inspired on S4-proofs. The crucial role of proof constants in the structure of lp-proofs methods is analysed. In particular, a method for the abduction of proof constant specifications in strongly analytic preKELP proofs is presented; abduction heuristics and the complexity of the method are discussed.

Algorithms for two-dimensional cutting stock and strip packing problems using dynamic programming and column generation

We investigate several two-dimensional guillotine cutting stock problems and their variants in which orthogonal rotations are allowed. We first present two dynamic programming based algorithms for the Rectangular Knapsack (RK) problem and its variants in which the patterns must be staged. The first algorithm solves the recurrence formula proposed by Beasley; the second algorithm - for staged patterns - also uses a recurrence formula. We show that if the items are not so small compared to the dimensions of the bin, then these algorithms require polynomial time. Using these algorithms we solved all instances of the RK problem found at the OR-LIBRARY, including one for which no optimal solution was known. We also consider the Two-dimensional Cutting Stock problem. We present a column generation based algorithm for this problem that uses the first algorithm above mentioned to generate the columns. We propose two strategies to tackle the residual instances. We also investigate a variant of this problem where the bins have different sizes. At last, we study the Two-dimensional Strip Packing problem. We also present a column generation based algorithm for this problem that uses the second algorithm above mentioned where staged patterns are imposed. In this case we solve instances for two-, three- and four-staged patterns. We report on some computational experiments with the various algorithms we propose in this paper. The results indicate that these algorithms seem to be suitable for solving real-world instances. We give a detailed description (a pseudo-code) of all the algorithms presented here, so that the reader may easily implement these algorithms. (c) 2007 Elsevier B.V. All rights reserved.

A logic-based agent that plans for extended reachability goals

Planning to reach a goal is an essential capability for rational agents. In general, a goal specifies a condition to be achieved at the end of the plan execution. In this article, we introduce nondeterministic planning for extended reachability goals (i.e., goals that also specify a condition to be preserved during the plan execution). We show that, when this kind of goal is considered, the temporal logic CTL turns out to be inadequate to formalize plan synthesis and plan validation algorithms. This is mainly due to the fact that the CTL`s semantics cannot discern among the various actions that produce state transitions. To overcome this limitation, we propose a new temporal logic called alpha-CTL. Then, based on this new logic, we implement a planner capable of synthesizing reliable plans for extended reachability goals, as a side effect of model checking.

New Improvements in Automatic Structure Elucidation Using the LSD (Logic for Structure Determination) and the SISTEMAT Expert Systems

This article describes the integration of the LSD (Logic for Structure Determination) and SISTEMAT expert systems that were both designed for the computer-assisted structure elucidation of small organic molecules. A first step has been achieved towards the linking of the SISTEMAT database with the LSD structure generator. The skeletal descriptions found by the SISTEMAT programs are now easily transferred to LSD as substructural constraints. Examples of the synergy between these expert systems are given for recently reported natural products.