Assessment of limb muscle and adipose tissue by dual-energy X-ray absorptiometry using magnetic resonance imaging for comparison

OBJECTIVE: To use magnetic resonance imaging (MRI) to validate estimates of muscle and adipose tissue (AT) in lower limb sections obtained by dual-energy X-ray absorptiometry (DXA) modelling. DESIGN: MRI measurements were used as reference for validating limb muscle and AT estimates obtained by DXA models that assume fat-free soft tissue (FFST) comprised mainly muscle: model A accounted for bone hydration only; model B also applied constants for FFST in bone and skin and fat in muscle and AT; model C was as model B but allowing for variable fat in muscle and AT. SUBJECTS: Healthy men (n = 8) and women (n = 8), ages 41 - 62 y; mean (s.d.) body mass indices (BMIs) of 28.6 (5.4) kg/m(2) and 25.1 (5.4) kg/m2, respectively. MEASUREMENTS: MRI scans of the legs and whole body DXA scans were analysed for muscle and AT content of thigh (20 cm) and lower leg (10 cm) sections; 24 h creatinine excretion was measured. RESULTS: Model A overestimated thigh muscle volume (MRI mean, 2.3 l) substantially (bias 0.36 l), whereas model B underestimated it by only 2% (bias 0.045 l). Lower leg muscle (MRI mean, 0.6 l) was better predicted using model A (bias 0.04 l, 7% overestimate) than model B (bias 0.1 l, 17% underestimate). The 95% limits of agreement were high for these models (thigh,+/- 20%; lower leg,+/- 47%). Model C predictions were more discrepant than those of model B. There was generally less agreement between MRI and all DXA models for AT. Measurement variability was generally less for DXA measurements of FFST (coefficient of variation 0.7 - 1.8%) and fat (0.8 - 3.3%) than model B estimates of muscle (0.5-2.6%) and AT (3.3 - 6.8%), respectively. Despite strong relationships between them, muscle mass was overestimated by creatinine excretion with highly variable predictability. CONCLUSION: This study has shown the value of DXA models for assessment of muscle and AT in leg sections, but suggests the need to re-evaluate some of the assumptions upon which they are based.

Anisotropy-based performance analysis of linear discrete time invariant control systems

The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.

Probing the effect of vehicles on topical delivery: Understanding the basic relationship between solvent and solute penetration using silicone membranes

Purpose. In the present study we examined the relationship between solvent uptake into a model membrane (silicone) with the physical properties of the solvents (e.g., solubility parameter, melting point, molecular weight) and its potential predictability. We then assessed the subsequent topical penetration and retention kinetics of hydrocortisone from various solvents to define whether modifications to either solute diffusivity or partitioning were dominant in increasing permeability through solvent-modified membranes. Methods. Membrane sorption of solvents was determined from weight differences following immersion in individual solvents, corrected for differences in density. Permeability and retention kinetics of H-3-hydrocortisone, applied as saturated solutions in the various solvents, were determined over 48 h in horizontal Franz-type glass diffusion cells. Results. Solvent sorption into the membrane could be related to differences in solubility parameters, MW and hydrogen bonding (r(2) = 0.76). The actual and predicted volume of solvent sorbed into the membrane was also found to be linearly related to Log hydrocortisone flux, with changes in both diffusivity and partitioning of hydrocortisone observed for the different solvent vehicles. Conclusions. A simple structure-based predictive model can be applied to the sorption of solvents into silicone membranes. Changes in solute diffusivity and partitioning appeared to contribute to the increased hydrocortisone flux observed with the various solvent vehicles. The application of this predictive model to the more complex skin membrane remains to be determined.

Effects of adsorbate-adsorbate interaction in the description of adsorption isotherm of hydrocarbons in micro-mesoporous carbonaceous materials

In this paper, we present a model accounting for the adsorbate-adsorbate interaction in the adsorbed phase in the description of adsorption of pure vapors on carbonaceous materials. The details of the adsorbate-adsorbate interaction of a particular species are obtained from the analysis of its adsorption data on non-porous carbon black. The predictability of the model is tested against the adsorption isotherm data for benzene, toluene, n-pentane, n-hexane, carbon tetrachloride, methanol and ethanol on microporous activated carbon. It was found that the model prediction for non-polar adsorbates are satisfactory while it under-predicts for polar adsorbates, which is attributed to their additional interaction with functional groups. (C) 2002 Elsevier Science B.V. All rights reserved.

The threat of predictable and unpredictable pain: Differential effects on central nervous system processing?

Central nervous system performance is disrupted by pain and by the threat of pain. It is not known whether disruption caused by the threat of pain is dependent on the likelihood of pain occurring. We hypothesised that when a painful stimulus is possible but unpredictable central nervous system performance is reduced, but when the pain is predictable and unavoidable it is not. Sixteen healthy subjects performed a reaction time task during predictable and unpredictable conditions (100% and 50% probability of pain, respectively). Group data showed increased reaction time with the threat of pain by 50 ms (95% Cl 16 to 83 ms) for the predictable condition and 46 ms (95% CI 12 to 80 ms) for the unpredictable condition (p < 0.01 for both), but there was no difference between predictable and unpredictable conditions (p = 0.41). However, individual data showed that there was a differential effect in 75% of subjects (p < 0.05 for all) and that there was a greater effect of predictable pain for some subjects and a greater effect of unpredictable pain for others. Reaction time was related to reported anxiety (r = 0.49, p = 0.02 for both conditions). The predictability of a painful stimulus may have a differential effect on central nervous system performance within individuals, but anxiety about the impending pain appears to be important in determining this effect.

Learning of foraging skills by fish

This chapter outlines the relationships between a number of key factors that influence learning and memory, and illustrates them by reference to studies on the foraging behaviour of fish. Learning can lead to significant improvements in foraging performance in only a few exposures, and at least some fish species are capable of adjusting their foraging strategy as patterns of patch profitability change. There is also evidence that the memory window for prey varies between fish species, and that this may be a function of environmental predictability. Convergence between behavioural ecology and comparative psychology offers promise in terms of developing more mechanistically realistic foraging models and explaining apparently 'suboptimal' patterns of behaviour. Foraging decisions involve the interplay between several distinct systems of learning and memory, including those that relate to habitat, food patches, prey types, conspecifics and predators. Fish biologists, therefore, face an interesting challenge in developing integrated accounts of fish foraging that explain how cognitive sophistication can help individual animals to deal with the complexity of the ecological context.

Consumption habit and international stock returns

We use the consumption-based asset pricing model with habit formation to study the predictability and cross-section of returns from the international equity markets. We find that the predictability of returns from many developed countries' equity markets is explained in part by changing prices of risks associated with consumption relative to habit at the world as well as local levels. We also provide an exploratory investigation of the cross-sectional implications of the model under the complete world market integration hypothesis and find that the model performs mildly better than the traditional consumption-based model. the unconditional and conditional world CAPMs and a three-factor international asset pricing model. (C) 2004 Elsevier B.V. All rights reserved.

Forecasting stock returns using model-selection criteria

This paper examines the economic significance of return predictability in Australian equities. In light of considerable model uncertainty, formal model-selection criteria are used to choose a specification for the predictive model. A portfolio-switching strategy is implemented according to model predictions. Relative to a buy-and-hold market investment, the returns to the portfolio-switching strategy are impressive under several model-selection criteria, even after accounting for transaction costs. However, as these findings are not robust across other model-selection criteria examined, it is difficult to conclude that the degree of return predictability is economically significant.

Three putative types of El Nino revealed by spatial variability in impact on Australian wheat yield

The El Nino-Southern Oscillation (ENSO) phenomenon significantly impacts rainfall and ensuing crop yields in many parts of the world. In Australia, El Nino events are often associated with severe drought conditions. However, El Nino events differ spatially and temporally in their manifestations and impacts, reducing the relevance of ENSO-based seasonal forecasts. In this analysis, three putative types of El Nino are identified among the 24 occurrences since the beginning of the twentieth century. The three types are based on coherent spatial patterns (footprints) found in the El Nino impact on Australian wheat yield. This bioindicator reveals aligned spatial patterns in rainfall anomalies, indicating linkage to atmospheric drivers. Analysis of the associated ocean-atmosphere dynamics identifies three types of El Nino differing in the timing of onset and location of major ocean temperature and atmospheric pressure anomalies. Potential causal mechanisms associated with these differences in anomaly patterns need to be investigated further using the increasing capabilities of general circulation models. Any improved predictability would be extremely valuable in forecasting effects of individual El Nino events on agricultural systems.

Congruence in QTL for adventitious rooting in Pinus elliottii X Pinus caribaea hybrids resolves between and within-species effects

Targeting between-species effects for improvement in synthetic hybrid populations derived from outcrossing parental tree species may be one way to increase the efficacy and predictability of hybrid breeding. We present a comparative analysis of the quantitative trait loci (QTL) which resolved between from within-species effects for adventitious rooting in two populations of hybrids between Pinus elliottii and P. caribaea, an outbred F-1 (n=287) and an inbred-like F-2 family (n=357). Most small to moderate effect QTL (each explaining 2-5% of phenotypic variation, PV) were congruent (3 out of 4 QTL in each family) and therefore considered within-species effects as they segregated in both families. A single large effect QTL (40% PV) was detected uniquely in the F-2 family and assumed to be due to a between-species effect, resulting from a genetic locus with contrasting alleles in each parental species. Oligogenic as opposed to polygenic architecture was supported in both families (60% and 20% PV explained by 4 QTL in the F-2 and F-1 respectively). The importance of adventitious rooting for adaptation to survive water-logged environments was thought in part to explain oligogenic architecture of what is believed to be a complex trait controlled by many hundreds of genes.

Personality and goal orientation as predictors of performance in a learning context

The current study aimed to investigate and provide furthering evidence of individual differences as determinants of task performance. This research focused on the effects of the personality traits Openness to Experience and Neuroticism, and two goal orientation traits. Learning Orientation and Avoid Orientation, on task performance. The hypotheses addressed the predictability of the traits, the differential effects of personality and goal orientation traits, and the mediating effects of goal orientation on the relationship between personality and performance. The results were based on questionnaire responses completed by a sample of 103 students. Scores on a computerised Air Traffic Control (ATC) decision-making task were used as a measure of task performance. Learning Orientation was found to be a significant predictor of performance, whilst the effect of Neuroticism was 'approaching' significance. Results indicated strong support for the differential relationship between personality traits and corresponding goal orientation traits. The mediating relationship between Openness to Experience, Learning Orientation and performance was also found to be 'approaching' significance. Results were indicative of the influences of personality and goal orientation on consequent performance outcomes. Implications were discussed, as well as suggestions for possible future directions in research assessing the predictabilit)' of individual differences in learning contexts.