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.

Integrable Kondo impurity in one-dimensional q-deformed t-J models

Integrable Kondo impurities in two cases of one-dimensional q-deformed t-J models are studied by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary K matrices depending on the local magnetic moments of the impurities are presented as nontrivial realizations of the reflection equation algebras in an impurity Hilbert space. Furthermore, these models are solved by using the algebraic Bethe ansatz method and the Bethe ansatz equations are obtained.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Mathematical models in percutaneous absorption

A number of mathematical models have been used to describe percutaneous absorption kinetics. In general, most of these models have used either diffusion-based or compartmental equations. The object of any mathematical model is to a) be able to represent the processes associated with absorption accurately, b) be able to describe/summarize experimental data with parametric equations or moments, and c) predict kinetics under varying conditions. However, in describing the processes involved, some developed models often suffer from being of too complex a form to be practically useful. In this chapter, we attempt to approach the issue of mathematical modeling in percutaneous absorption from four perspectives. These are to a) describe simple practical models, b) provide an overview of the more complex models, c) summarize some of the more important/useful models used to date, and d) examine sonic practical applications of the models. The range of processes involved in percutaneous absorption and considered in developing the mathematical models in this chapter is shown in Fig. 1. We initially address in vitro skin diffusion models and consider a) constant donor concentration and receptor conditions, b) the corresponding flux, donor, skin, and receptor amount-time profiles for solutions, and c) amount- and flux-time profiles when the donor phase is removed. More complex issues, such as finite-volume donor phase, finite-volume receptor phase, the presence of an efflux. rate constant at the membrane-receptor interphase, and two-layer diffusion, are then considered. We then look at specific models and issues concerned with a) release from topical products, b) use of compartmental models as alternatives to diffusion models, c) concentration-dependent absorption, d) modeling of skin metabolism, e) role of solute-skin-vehicle interactions, f) effects of vehicle loss, a) shunt transport, and h) in vivo diffusion, compartmental, physiological, and deconvolution models. We conclude by examining topics such as a) deep tissue penetration, b) pharmacodynamics, c) iontophoresis, d) sonophoresis, and e) pitfalls in modeling.

General properties of cosmological models with an isotropic singularity

Much of the published work regarding the Isotropic Singularity is performed under the assumption that the matter source for the cosmological model is a barotropic perfect fluid, or even a perfect fluid with a gamma-law equation of state. There are, however, some general properties of cosmological models which admit an Isotropic Singularity, irrespective of the matter source. In particular, we show that the Isotropic Singularity is a point-like singularity and that vacuum space-times cannot admit an Isotropic Singularity. The relationships between the Isotropic Singularity, and the energy conditions, and the Hubble parameter is explored. A review of work by the authors, regarding the Isotropic Singularity, is presented.

Human response to environmental noise: The role of perceived control

Negative impacts of noise exposure on health and performance may result in part from learned helplessness, the syndrome of deficits typically produced by exposure to uncontrollable events. People may perceive environmental noise to be uncontrollable, and several effects of noise exposure appear to parallel learned helplessness deficits. In the present socioacoustic survey (N = 1,015), perceived control over aircraft noise correlated negatively with some effects of noise (though not others). Furthermore, these effects were better predicted by perceived control than by noise level. These observational data support the claim that learned helplessness contributes to the effects of noise exposure.

Algebraic Bethe ansatz for integrable one-dimensional extended Hubbard models with open boundary conditions

Nine classes of integrable open boundary conditions, further extending the one-dimensional U-q (gl (212)) extended Hubbard model, have been constructed previously by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary systems are now solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained for all nine cases.

Response selection deficits in melancholic but not nonmelancholic unipolar major depression

One consistent functional imaging finding from patients with major depression has been abnormality of the anterior cingulate cortex (ACC). Hypoperfusion has been most commonly reported, but some studies suggest relative hyperperfusion is associated with response to somatic treatments. Despite these indications of the possible importance of the ACC in depression there have been relatively few cognitive studies ACC function in patients with major depression. The present study employed a series of reaction time (RT) tasks involving selection with melancholic and nonmelancholic depressed patients, as well as age-matched controls. Fifteen patients with unipolar major depression (7 melancholic, 8 nonmelancholic) and 8 healthy age-matched controls performed a series of response selection tasks (choice RT, spatial Stroop, spatial stimulus-response compatibility (SRC), and a combined Stroop + SRC condition). Reaction time and error data were collected. Melancholic patients were significantly slower than controls on all tasks but were slower than nonmelancholic patients only on the Stroop and Stroop + SRC conditions. Nonmelancholic patients did not differ from the control group on any task. The Stroop task seems crucial in differentiating the two depressive groups, they did not differ on the choice RT or SRC tasks. This may reflect differential task demands, the SRC involved symbolic manipulation that might engage the dorsal ACC and dorsolateral prefrontal cortex (DLPFC) to a greater extent than the, primarily inhibitory, Stroop task which may engage the ventral ACC and orbitofrontal cortex (OFC). This might suggest the melancholic group showed a greater ventral ACC-OFC deficit than the nonmelancholic group, while both groups showed similar dorsal ACC-DLPFC deficit.

Ecosystem process models at multiple scales for mapping tropical forest productivity

Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

Use of bulk density profiles from X-radiography to examine structural crust models

Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.

Ladder operators for integrable one-dimensional lattice models

A generalised ladder operator is used to construct the conserved operators for any one-dimensional lattice model derived from the Yang-Baxter equation. As an example, the low order conserved operators for the XYh model are calculated explicitly.

Cost-effectiveness of cognitive behavioural therapy and selective serotonin reuptake inhibitors for major depression in children and adolescents

Objective: To assess from a health sector perspective the incremental cost-effectiveness of cognitive behavioural therapy (CBT) and selective serotonin reuptake inhibitors (SSRIs) for the treatment of major depressive disorder (MDD) in children and adolescents, compared to 'current practice'. Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analysis of randomised controlled trials. An assessment on second stage filter criteria ('equity'; 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are tracked for the duration of a new episode of MDD arising in eligible children (age 6-17 years) in the Australian population in the year 2000. Simulation-modelling techniques are used to present a 95% uncertainty interval (UI) around the cost-effectiveness ratios. Results: Compared to current practice, CBT by public psychologists is the most cost-effective intervention for MDD in children and adolescents at A$9000 per DALY saved (95% UI A$3900 to A$24 000). SSRIs and CBT by other providers are less cost-effective but likely to be less than A$50 000 per DALY saved (> 80% chance). CBT is more effective than SSRIs in children and adolescents, resulting in a greater total health benefit (DALYs saved) than could be achieved with SSRIs. Issues that require attention for the CBT intervention include equity concerns, ensuring an adequate workforce, funding arrangements and acceptability to various stakeholders. Conclusions: Cognitive behavioural therapy provided by a public psychologist is the most effective and cost-effective option for the first-line treatment of MDD in children and adolescents. However, this option is not currently accessible by all patients and will require change in policy to allow more widespread uptake. It will also require 'start-up' costs and attention to ensuring an adequate workforce.