Model membranes: developments in functional micelles and vesicles

Although aggregates of amphiphilic molecules have been studied for decades, systems are now being developed that are able to perform useful functions, including drug delivery, control of the availability of chemical species, sensing of ions or organic molecules, and, the most challenging, providing a reaction environment for chemical reactions that resembles that of the natural system. Such systems are therefore becoming more and more important in a variety of fields, ranging from material science to analytical chemistry and medicine.     

Analysis of infant growth curves using multivariate adaptive splines

In this paper, we study the effect of cocaine use by a pregnant woman on the growth of her infant after birth. Using a data set from a retrospective study, we found that cocaine use was a marginally significant contributor to the infant growth as measured by bodyweight. From a statistical point of view, the data represent a common, though complex, structure that has received little attention in the statistical literature. To analyze these data, we adopt and further enhance an approach developed recently called MASAL (multivariate adaptive splines for the analysis of longitudinal data). In addition to the fitting of growth curves, we demonstrate particularly how to explore and estimate the underlying covariance structures for the longitudinal data that were collected from a rather irregular schedule.     

Functional analysis of mutations in the human carnitine/acylcarnitine translocase in Aspergillus nidulans

Deficiency of the carnitine/acylcarnitine translocase (CACT), the most severe disorder of fatty acid beta-oxidation, is usually lethal in both humans and animals, precluding the development of animal models of the disease. In contrast, CACT deficiency is conditionally lethal in the fungus Aspergillus nidulans, since loss-of-function mutations in acuH, the translocase structural gene, do not prevent growth on carbon sources other than ketogenic compounds, such as fatty acids. Here, we describe the molecular characterization of extant acuH alleles and the development of a fungal model for CACT deficiency based on the ability of human CACT to fully complement, when expressed at physiological levels, the growth defect of an A. nidulans DeltaacuH strain on acetate and long-chain fatty acids. By using growth tests and in vitro assays this model enabled us to carry out a functional characterization of human CACT mutations showing that it may be useful for distinguishing potentially pathogenic human CACT missense mutations from neutral, single residue substitution-causing polymorphisms.     

Controls and models for estimating direct nitrous oxide emissions from temperate and sub-boreal agricultural mineral soils in Europe

Based on a review of N₂O field studies in Europe, major soil, climate and management controls of N₂O release from agricultural mineral soils in the European Union have been identified. Data for these N₂O emission drivers can easily be gathered from statistical services. Using stepwise multivariate linear regression analysis, empirical first order models of N₂O emissions have been established which allow – in contrast to existing large-scale approaches – a regionally disaggregated estimation of N₂O emissions at sub-national, national and continental level in the temperate and boreal climate regions of Europe. Arable soils showed lower mean and maximum emissions in oceanic temperate climate (Temperate West) than in pre-alpine temperate and sub-boreal climate (Sub-boreal Europe). Therefore, two separate regression models were developed. Nitrous oxide emissions from arable soils the Temperate West amount to an average flux rate below 2 kg N₂O-N ha^–1 yr^–1 and rarely exceed 5 kg N₂O-N ha^–1 yr^–1. They are modelled by the parameters fertiliser, topsoil organic carbon and sand content. In Sub-boreal European arable soils, N₂O emissions vary in a much wider range between 0 and 27 kg N₂O-N ha^–1 yr^–1 in dependence of available nitrogen, represented in the model by fertiliser and topsoil nitrogen content. Compared to existing methods for large scale inventories, the regression models allow a better regional fit to measured values since they integrate additional driving forces for N₂O emissions. For grasslands, a fertiliser-based model was established which yields higher emission estimates than existing ones. Due to an extreme variability, no climate, soil nor management parameters could be included in the empirical grasslands model.     

A transduction model of the Meissner corpuscle

I propose a transduction model of the Meissner corpuscle that integrates ideas put forth by Freeman and Johnson and results obtained by Looft. The principal development in the present model is its specification that RA receptor potentials are updated as a linear function of stimulus velocity above baseline; the model thus readily accommodates non-sinusoidal input. It also incorporates modifications to Freeman and Johnson's model proposed by Slavík and Bell, namely a period of refractoriness lasting 1 ms followed by a period of hyperexcitability lasting 13.5 ms. The model is applied to various psychophysical and physiological situations: psychophysical threshold vs. frequency, RA afferent impulse rates vs. intensity, impulse regularity vs. frequency, phase retardation vs. frequency, and responses to non-repeating noise and to complex stimuli. Model output closely matches psychophysical and neurophysiological data. The proposed model thus reliably predicts RA afferent responses to arbitrary stimuli and may facilitate the development of theories relating psychophysical phenomena to their underlying neural representations.     

Equivalence relationships between stage-structured population models

Matrix population models are widely applied in conservation ecology to help predict future population trends and guide conservation effort. Researchers must decide upon an appropriate level of model complexity, yet there is little theoretical work to guide such decisions. In this paper we present an analysis of a stage-structured model, and prove that the model's structure can be simplified and parameterised in such a way that the long-term growth rate, the stable-stage distribution and the generation time are all invariant to the simplification. We further show that for certain structures of model the simplified models require less effort in data collection. We also discuss features of the models which are not invariant to the simplification and the implications of our results for the selection of an appropriate model. We illustrate the ideas using a population model for short-tailed shearwaters (Puffinus tenuirostris). In this example, model simplification can increase parameter elasticity, indicating that an intermediate level of complexity is likely to be preferred.     

Automatic domain decomposition of proteins by a Gaussian Network Model

Proteins are often comprised of domains of apparently independent folding units. These domains can be defined in various ways, but one useful definition divides the protein into substructures that seem to move more or less independently. The same methods that allow fairly accurate calculation of motion can be used to help classify these substructures. We show how the Gaussian Network Model (GNM), commonly used for determining motion, can also be adapted to automatically classify domains in proteins. Parallels between this physical network model and graph theory implementation are apparent. The method is applied to a nonredundant set of 55 proteins, and the results are compared to the visual assignments by crystallographers. Apart from decomposing proteins into structural domains, the algorithm can generally be applied to any large macromolecular system to decompose it into motionally decoupled sub-systems.