High-resolution proton nuclear magnetic resonance: application to the study of leukaemic lymphocytes.

Proton Nuclear Magnetic Resonance spectroscopy (1H NMR) is able to monitor the changes that develop at a molecular level when leukaemic cells proliferate in the thymus of AKR mice. Furthermore, cultured human lymphocyte cell lines are shown to differ in their 1H-NMR spectra. These spectral differences are attributable to changes in membrane fluidity and composition, which in turn reflect the stage of differentiation and the type of transformation of the lymphocyte lines, i.e. Epstein-Barr virus (EBV) or leukaemic transformation..

Probing anharmonic properties of nuclear surface vibration by heavy-ion fusion reactions

Describing fusion reactions between ^{16}O and ^{154}Dy and, between ^{16}O and ^{144}Sm by the $sd-$ and $sdf-$ interacting boson model, we show that heavy-ion fusion reactions are strongly affected by anharmonic properties of nuclear surface vibrations and nuclear shape, and thus provide a powerful method to study details of nuclear structure and dynamics.Comment: 8 pages, 5 figures, To be published in the Proceedings of the FUSION 97 Conference, South Durras, Australia, March 1997 (J. Phys. G

Quiescience as a mechanism for cyclical hypoxia and acidosis

Tumour tissue characteristically experiences fluctuations in substrate supply. This unstable microenvironment drives constitutive metabolic changes within cellular populations and, ultimately, leads to a more aggressive phenotype. Previously, variations in substrate levels were assumed to occur through oscillations in the hæmodynamics of nearby and distant blood vessels. In this paper we examine an alternative hypothesis, that cycles of metabolite concentrations are also driven by cycles of cellular quiescence and proliferation. Using a mathematical modelling approach, we show that the interdependence between cell cycle and the microenvironment will induce typical cycles with the period of order hours in tumour acidity and oxygenation. As a corollary, this means that the standard assumption of metabolites entering diffusive equilibrium around the tumour is not valid; instead temporal dynamics must be considered

Systems biologists seek fuller integration of systems biology approaches in new cancer research programs

Systems biology takes an interdisciplinary approach to the systematic study of complex interactions in biological systems. This approach seeks to decipher the emergent behaviors of complex systems rather than focusing only on their constituent properties. As an increasing number of examples illustrate the value of systems biology approaches to understand the initiation, progression, and treatment of cancer, systems biologists from across Europe and the United States hope for changes in the way their field is currently perceived among cancer researchers. In a recent EU-US workshop, supported by the European Commission, the German Federal Ministry for Education and Research, and the National Cancer Institute of the NIH, the participants discussed the strengths, weaknesses, hurdles, and opportunities in cancer systems biology

Evolutionary Games with Affine Fitness Functions: Applications to Cancer

We analyze the dynamics of evolutionary games in which fitness is defined as an affine function of the expected payoff and a constant contribution. The resulting inhomogeneous replicator equation has an homogeneous equivalent with modified payoffs. The affine terms also influence the stochastic dynamics of a two-strategy Moran model of a finite population. We then apply the affine fitness function in a model for tumor-normal cell interactions to determine which are the most successful tumor strategies. In order to analyze the dynamics of concurrent strategies within a tumor population, we extend the model to a three-strategy game involving distinct tumor cell types as well as normal cells. In this model, interaction with normal cells, in combination with an increased constant fitness, is the most effective way of establishing a population of tumor cells in normal tissue.Comment: The final publication is available at http://www.springerlink.com, http://dx.doi.org/10.1007/s13235-011-0029-

Parameter identification through mode isolation for reaction-diffusion systems on arbitrary geometries

We present a computational framework for isolating spatial patterns arising in the steady states of reaction-diffusion systems. Such systems have been used to model many natural phenomena in areas such as developmental and cancer biology, cell motility and material science. In many of these applications, often one is interested in identifying parameters which will lead to a particular pattern for a given reaction-diffusion model. To attempt to answer this, we compute eigenpairs of the Laplacian on a variety of do- mains and use linear stability analysis to determine parameter values for the system that will lead to spatially inhomogeneous steady states whose patterns correspond to particular eigenfunctions. This method has previously been used on domains and surfaces where the eigenvalues and eigenfunctions are found analytically in closed form. Our contribution to this methodology is that we numerically compute eigenpairs on arbitrary domains and surfaces. Here we present examples and demonstrate that mode isolation is straightforward especially for low eigenvalues. Additionally we see that the inhomogeneous steady state can be a linear combination of eigenfunctions. Finally we show an example suggesting that pattern formation is robust on similar surfaces in cases that the surface either has or does not have a boundary

Coupled-channels analysis of the 16^{{\bf 16}}O+208^{{\bf 208}}Pb fusion barrier distribution

Analyses using simplified coupled-channels models have been unable to describe the shape of the previously measured fusion barrier distribution for the doubly magic $^{16}$O+$^{208}$Pb system. This problem was investigated by re-measuring the fission excitation function for $^{16}$O+$^{208}$Pb with improved accuracy and performing more exact coupled-channels calculations, avoiding the constant-coupling and first-order coupling approximations often used in simplified analyses. Couplings to the single- and 2-phonon states of $^{208}$Pb, correctly taking into account the excitation energy and the phonon character of these states, particle transfers, and the effects of varying the diffuseness of the nuclear potential, were all explored. However, in contrast to other recent analyses of precise fusion data, no satisfactory simultaneous description of the shape of the experimental barrier distribution and the fusion cross-sections for $^{16}$O+$^{208}$Pb was obtained.Comment: RevTex, 29 pages, 7 postscript figures, to appear in PR

Metabolic effects of diets differing in glycaemic index depend on age and endogenous GIP

Aims/hypothesis High- vs low-glycaemic index (GI) diets unfavourably affect body fat mass and metabolic markers in rodents. Different effects of these diets could be age-dependent, as well as mediated, in part, by carbohydrate-induced stimulation of glucose-dependent insulinotrophic polypeptide (GIP) signalling. Methods Young-adult (16 weeks) and aged (44 weeks) male wild-type (C57BL/6J) and GIP-receptor knockout (Gipr −/− ) mice were exposed to otherwise identical high-carbohydrate diets differing only in GI (20–26 weeks of intervention, n = 8–10 per group). Diet-induced changes in body fat distribution, liver fat, locomotor activity, markers of insulin sensitivity and substrate oxidation were investigated, as well as changes in the gene expression of anorexigenic and orexigenic hypothalamic factors related to food intake. Results Body weight significantly increased in young-adult high- vs low-GI fed mice (two-way ANOVA, p < 0.001), regardless of the Gipr genotype. The high-GI diet in young-adult mice also led to significantly increased fat mass and changes in metabolic markers that indicate reduced insulin sensitivity. Even though body fat mass also slightly increased in high- vs low-GI fed aged wild-type mice (p < 0.05), there were no significant changes in body weight and estimated insulin sensitivity in these animals. However, aged Gipr −/− vs wild-type mice on high-GI diet showed significantly lower cumulative net energy intake, increased locomotor activity and improved markers of insulin sensitivity. Conclusions/interpretation The metabolic benefits of a low-GI diet appear to be more pronounced in younger animals, regardless of the Gipr genotype. Inactivation of GIP signalling in aged animals on a high-GI diet, however, could be beneficial

A Taxonomy of Causality-Based Biological Properties

We formally characterize a set of causality-based properties of metabolic networks. This set of properties aims at making precise several notions on the production of metabolites, which are familiar in the biologists' terminology. From a theoretical point of view, biochemical reactions are abstractly represented as causal implications and the produced metabolites as causal consequences of the implication representing the corresponding reaction. The fact that a reactant is produced is represented by means of the chain of reactions that have made it exist. Such representation abstracts away from quantities, stoichiometric and thermodynamic parameters and constitutes the basis for the characterization of our properties. Moreover, we propose an effective method for verifying our properties based on an abstract model of system dynamics. This consists of a new abstract semantics for the system seen as a concurrent network and expressed using the Chemical Ground Form calculus. We illustrate an application of this framework to a portion of a real metabolic pathway

Multiscale modelling of vascular tumour growth in 3D: the roles of domain size & boundary condition

We investigate a three-dimensional multiscale model of vascular tumour growth, which couples blood flow, angiogenesis, vascular remodelling, nutrient/growth factor transport, movement of, and interactions between, normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. In particular, we determine how the domain size, aspect ratio and initial vascular network influence the tumour's growth dynamics and its long-time composition. We establish whether it is possible to extrapolate simulation results obtained for small domains to larger ones, by constructing a large simulation domain from a number of identical subdomains, each subsystem initially comprising two parallel parent vessels, with associated cells and diffusible substances. We find that the subsystem is not representative of the full domain and conclude that, for this initial vessel geometry, interactions between adjacent subsystems contribute to the overall growth dynamics. We then show that extrapolation of results from a small subdomain to a larger domain can only be made if the subdomain is sufficiently large and is initialised with a sufficiently complex vascular network. Motivated by these results, we perform simulations to investigate the tumour's response to therapy and show that the probability of tumour elimination in a larger domain can be extrapolated from simulation results on a smaller domain. Finally, we demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour