The role of cognitive vulnerability and stress in the prediction of postpartum depressive symptomatology

Objectives. The present study was designed to test the diathesis-stress components of Beck's cognitive theory of depression and the reformulated learned helplessness model of depression in the prediction of postpartum depressive symptomatology. Design and methods. The research used a two-wave longitudinal design-data were collected from 65 primiparous women during their third trimester of pregnancy and then 6 weeks after the birth. Cognitive vulnerability and initial depressive symptomatology were assessed at Time 1, whereas stress and postpartum depressive symptomatology were assessed at Time 2. Results. There was some support for the diathesis-stress component of Beck's cognitive theory, to the extent that the negative relationship between both general and maternal-specific dysfunctional attitudes associated with performance evaluation and Time 2 depressive symptomatology was strongest for women who reported high levels of parental stress. In a similar vein, the effects of dysfunctional attitudes (general and maternal-specific) associated with performance evaluation and need for approval (general measure only) on partner ratings of emotional distress were evident only among those women whose infants were rated as being temperamentally difficult. Conclusion. There was no support for the diathesis-stress component of the reformulated learned helplessness model of depression; however, there was some support for the diathesis-stress component of Beck's cognitive theory.

Experimental study of phase equilibria in the systems Fe-Zn-O and Fe-Zn-Si-O at metallic iron saturation

The reported experimental work on the systems Fe-Zn-O and Fe-Zn-Si-O in equilibrium with metallic iron is part of a wider research program that combines experimental and thermodynamic computer modeling techniques to characterize zinc/lead industrial slags and sinters in the system PbO-ZnO-SiO2-CaO-FeO-Fe2O3. Extensive experimental,investigations using high-temperature equilibration and quenching techniques followed by electron probe X-ray microanalysis (EPMA) were carried out. Special experimental; procedures were developed to enable accurate measurements in these ZnO-containing systems to be performed in equilibrium with metallic iron; The systems Fe-Zn-O and FeZn-Si-O were experimentally investigated in equilibrium with metallic iron in the temperature ranges 900 degreesC to 1200 degreesC (1173 to 1473 K) and from 1000 degreesC to 1350 degreesC (1273 to 1623 K), respectively. The liquidus surface in the system Fe-Zn-Si-O in equilibrium with metallic iron was characterized in the composition ranges 0 to 33 wt pet ZnO and 0 to 40 wt pet SiO2. The wustite (Fe,Zn)O, zincite (Zn,Fe)O, willemite (Zn,Fe)(2)SiO4, arid fayalite: (Fe,Zn)(2)SiO4 solid solutions in equilibrium with metallic iron were measured.

Recombinant human growth hormone, but not insulin-like growth factor-I, enhances central fat loss in postmenopausal women undergoing a diet and exercise program

We examined the effect of recombinant human growth hormone (rhGH) and/or recombinant human insulin-like growth factor-I (rhIGF-I) on regional fat loss in postmenopausal women undergoing a weight loss regimen of diet plus exercise. Twenty-seven women aged 59-79 years, 20-40% above ideal body weight, completed a 12-week program consisting of resistance training 2 days/week and walking 3 days/week, while consuming a diet that was 500 kcal/day less than that required for weight maintenance, Participants were randomly assigned in a double-blind fashion to receive rhGH (0.025 mg/kg BW/day: n=7), rhIGF-I (0.015 mg/kg BW/day: n=7), rhGH + rhIGF-I (n = 6), or placebo (PL: n = 7). Regional and whole body fat mass were determined by dual X-ray absorptiometry. Body fat distribution was assessed by the ratios of trunk fat-to-limb fat (TrF/LimbF) and trunk fat-to-total fat (TrF/TotF), Limb and trunk fat decreased in all groups (p < 0.01). For both ratios of fat distribution, the rhGH treated group experienced an enhanced loss of truncal compared to peripheral fat (p less than or equal to 0.01), with no significant change for those administered rhIGF-I or FL. There was no association between change in fat distribution and indices of cardiovascular disease risk as determined by serum lipid/lipoprotein levels and maximal aerobic capacity. These results suggest that administration of rhGH facilitates a decrease in central compared to peripheral fat in older women undertaking a weight loss program that combines exercise and moderate caloric restriction, although no beneficial effects are conferred to lipid/lipoprotein profiles, Further, the effect of rhGH is not enhanced by combining rhCH with rhIGF-I administration. In addition, rhIGF-I does not augment the loss of trunk fat when administered alone.

The efficacy of a universal school-based program to prevent adolescent depression

Evaluated whether a universal school-based program, designed to prevent depression in adolescents, could be effectively implemented within the constraints of the school environment. Participants were 260 Year 9 secondary school students. Students completed measures of depressive symptoms and hopelessness and were then assigned to 1 of 3 groups: (a) Resourceful Adolescent Program Adolescents (RAP A), an 11-session school-based resilience building program, as part of the school curriculum; (b) Resourceful Adolescent Program-Family (RAP-F), the same program as in RAP A, but in which each student's parents were also invited to participate in a 3-session parent program; and (c) Adolescent Watch, a comparison group in which adolescents simply completed the measures. The program was implemented with a high recruitment (88%), low attrition rate (5.8%), and satisfactory adherence to program protocol. Adolescents in either of the RAP programs reported significantly lower levels of depressive symptomatology and hopelessness at post-intervention and 10-month follow-up, compared with those in the comparison group. Adolescents also reported high satisfaction with the program. The study provides evidence for the efficacy of a school-based universal program designed to prevent depression in adolescence.

Gender differences in bone geometry during the adolescent growth spurt

To investigate whether there are gender differences in the bone geometry of the proximal femur during the adolescent years we used an interactive computer program ?Hip Strength Analysis? developed by Beck and associates (Beck et al., Invest Radiol. 1990,25:6-18.) to derive femoral neck geometry parameters from DXA bone scans (Hologic 2000, array mode). We analyzed a longitudinal data-set collected on 70 boys and 68 girls over a seven year period. Distance and velocity curves for height were fitted for each child utilizing a cubic spline procedure and the age of peak height velocity (PHV) was determined. To control for maturational differences between children of the same chronological age and between boys and girls, section modulus (Z) an index of bending strength, cross sectional area of bone (CSA), sub-periosteal width (SPW), and BMD values at the neck and shaft of the proximal femur were determined for points on each individual?s curve at the age of PHV and one and two years on either side of peak. To control for size differences, height and weight were introduced as co-variates in the two-way analyses of variance looking at gender over time measured at the maturational age points (-2, -1, age of PHV, +1, +2). The following figure presents the results of the analyses on two variables, BMD and Z at neck and shaft regions:After the age of peak linear growth (PHV), independent of body size, there was a gender difference in BMD at the shaft but not at the neck. Section modulus at both sites indicated that male bones became significantly stronger after PHV. Underlying these maturational changes, male bones became wider (SPW) after PHV in both the neck and shaft and enclosed more material (CSA) at all maturational age points at both regions. These results call into question the emphasis on using BMD as a measure of skeletal integrity in growing children

Efficient discovery of immune response targets by cyclical refinement of QSAR models of peptide binding

Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-All binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes. (C) 2001 by Elsevier Science Inc.

An L-system-based plant modeling language

Cpfg is a program for simulating and visualizing plant development, based on the theory of L-systems. A special-purpose programming language, used to specify plant models, is an essential feature of cpfg. We review postulates of L-system theory that have influenced the design of this language. We then present the main constructs of this language, and evaluate it from a user's perspective.

Using biplots to interpret gene expression patterns in plants

Sum: Plant biologists in fields of ecology, evolution, genetics and breeding frequently use multivariate methods. This paper illustrates Principal Component Analysis (PCA) and Gabriel's biplot as applied to microarray expression data from plant pathology experiments. Availability: An example program in the publicly distributed statistical language R is available from the web site (www.tpp.uq.edu.au) and by e-mail from the contact. Contact: scott.chapman@csiro.au.

Computer simulations of coupled problems in geological and geochemical systems

The finite element method is used to simulate coupled problems, which describe the related physical and chemical processes of ore body formation and mineralization, in geological and geochemical systems. The main purpose of this paper is to illustrate some simulation results for different types of modelling problems in pore-fluid saturated rock masses. The aims of the simulation results presented in this paper are: (1) getting a better understanding of the processes and mechanisms of ore body formation and mineralization in the upper crust of the Earth; (2) demonstrating the usefulness and applicability of the finite element method in dealing with a wide range of coupled problems in geological and geochemical systems; (3) qualitatively establishing a set of showcase problems, against which any numerical method and computer package can be reasonably validated. (C) 2002 Published by Elsevier Science B.V.

Prediction of promiscuous peptides that bind HLA class I molecules

Promiscuous T-cell epitopes make ideal targets for vaccine development. We report here a computational system, multipred, for the prediction of peptide binding to the HLA-A2 supertype. It combines a novel representation of peptide/MHC interactions with a hidden Markov model as the prediction algorithm. multipred is both sensitive and specific, and demonstrates high accuracy of peptide-binding predictions for HLA-A*0201, *0204, and *0205 alleles, good accuracy for *0206 allele, and marginal accuracy for *0203 allele. multipred replaces earlier requirements for individual prediction models for each HLA allelic variant and simplifies computational aspects of peptide-binding prediction. Preliminary testing indicates that multipred can predict peptide binding to HLA-A2 supertype molecules with high accuracy, including those allelic variants for which no experimental binding data are currently available.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

Inter-subband redundancy prediction using neural network for video coding

High performance video codec is mandatory for multimedia applications such as video-on-demand and video conferencing. Recent research has proposed numerous video coding techniques to meet the requirement in bandwidth, delay, loss and Quality-of-Service (QoS). In this paper, we present our investigations on inter-subband self-similarity within the wavelet-decomposed video frames using neural networks, and study the performance of applying the spatial network model to all video frames over time. The goal of our proposed method is to restore the highest perceptual quality for video transmitted over a highly congested network. Our contributions in this paper are: (1) A new coding model with neural network based, inter-subband redundancy (ISR) prediction for video coding using wavelet (2) The performance of 1D and 2D ISR prediction, including multiple levels of wavelet decompositions. Our result shows a short-term quality enhancement may be obtained using both 1D and 2D ISR prediction.

Prediction of carbon monoxide in fires by conditional moment closure

Carbon monoxide is the chief killer in fires. Dangerous levels of CO can occur when reacting combustion gases are quenched by heat transfer, or by mixing of the fire plume in a cooled under- or overventilated upper layer. In this paper, carbon monoxide predictions for enclosure fires are modeled by the conditional moment closure (CMC) method and are compared with laboratory data. The modeled fire situation is a buoyant, turbulent, diffusion flame burning under a hood. The fire plume entrains fresh air, and the postflame gases are cooled considerably under the hood by conduction and radiation, emulating conditions which occur in enclosure fires and lead to the freezing of CO burnout. Predictions of CO in the cooled layer are presented in the context of a complete computational fluid dynamics solution of velocity, temperature, and major species concentrations. A range of underhood equivalence ratios, from rich to lean, are investigated. The CMC method predicts CO in very good agreement with data. In particular, CMC is able to correctly predict CO concentrations in lean cooled gases, showing its capability in conditions where reaction rates change considerably.