Parameter identification of the calvin photosynthesis cycle

Summary This article is concerned with the determination of kinetic parameters of the Calvin photosynthesis cycle which is described by seventeen nonlinear ordinary differential equations. It is shown that the task requires dynamic data for several sets of initial conditions. The numerical technique is based upon an algorithm for non-linear optimization and Gear's numerical integration scheme for stiff systems of differential equations. The sensitivity of the parameters to noise in the data is tested with a method adapted from Rosenbrook and Storey. A preliminary set of parameters has been obtained from a preliminary set of experimental data. The numerical methods are then tested with synthetic data derived from these parameters. The mathematical model and the results obtained in the simulation are used as an aid in designing new experiments.     

Shapes and functions of species–area curves (II): a review of new models and parameterizations

This paper has extended and updated my earlier list and analysis of candidate models used in theoretical modelling and empirical examination of species–area relationships (SARs). I have also reviewed trivariate models that can be applied to include a second independent variable (in addition to area) and discussed extensively the justifications for fitting curves to SARs and the choice of model. There is also a summary of the characteristics of several new candidate models, especially extended power models, logarithmic models and parameterizations of the negative-exponential family and the logistic family. I have, moreover, examined the characteristics and shapes of trivariate linear, logarithmic and power models, including combination variables and interaction terms. The choice of models according to best fit may conflict with problems of non-normality or heteroscedasticity. The need to compare parameter estimates between data sets should also affect model choice. With few data points and large scatter, models with few parameters are often preferable. With narrow-scale windows, even inflexible models such as the power model and the logarithmic model may produce good fits, whereas with wider-scale windows where inflexible models do not fit well, more flexible models such as the second persistence (P2) model and the cumulative Weibull distribution may be preferable. When extrapolations and expected shapes are important, one should consider models with expected shapes, e.g. the power model for sample area curves and the P2 model for isolate curves. The choice of trivariate models poses special challenges, which one can more effectively evaluate by inspecting graphical plots.     

Model for external influences on cellular signal transduction pathways including cytosolic calcium oscillations

Experiments on the effects of extremely-low-frequency (ELF) electric and magnetic fields on cells of the immune system, T-lymphocytes in particular, suggest that the external field interacts with the cell at the level of intracellular signal transduction pathways. These are directly connected with changes in the calcium-signaling processes of the cell. Based on these findings, a theoretical model for receptor-controlled cytosolic calcium oscillations and for external influences on the signal transduction pathway is presented. We discuss the possibility that the external field acts on the kinetics of the signal transduction between the activated receptors at the cell membrane and the G-proteins. It is shown that, depending on the specific combination of cell internal biochemical and external physical parameters, entirely different responses of the cell can occur. We compare the effects of a coherent (periodic) modulation and of incoherent perturbations (noise). The model and the calculations are based on the theory of self-sustained, nonlinear oscillators. It is argued that these systems form an ideal basis for information-encoding processes in biological systems. © 1995 Wiley-Liss, Inc.     

Patterns of intra- and interspecific association in leaf-mining insects on three oak host species

Abstract. 1. We determined mortality and distributional patterns of leaf miners on three oak host species (Quercus falcata, Q.nigra and Q.hemisphaerica) in northern Florida, U.S.A.
2. Patterns of intra- and interspecific occurrence within leaves, and mortality of five most abundant leaf miner species were analysed as a test of competition.
3. Miners co-occurred on leaves more often that expected by chance (P<0.05) in six of ten possible species combinations and log-linear model analysis showed no negative higher-order interactions.
4. All five miner species had highly clumped distributions between leaves (P<0.01).
5. Leaf miner survival was less than expected for four of five species when co-occurring on leaves with conspecifics than when mining with heterospecifics or alone (P<0.05).
6. We conclude that interspecific competition is unapparent within this leaf miner guild and that intraspecific competition occurs in four of the five major leaf miner species. We discuss leaf miner selection of common leaves, perhaps based on chemical/physical leaf characters, as a cause of intra- and interspecific aggregation.     

Computational approaches from polymer physics to investigate chromatin folding

Microscopy and sequencing-based technologies are providing increasing insights into chromatin architecture. Nevertheless, a full comprehension of chromosome folding and its link with vital cell functions is far from accomplished at the molecular level. Recent theoretical and computational approaches are providing important support to experiments to dissect the three-dimensional structure of chromosomes and its organizational mechanisms. Here, we review, in particular, the String&Binders polymer model of chromatin that describes the textbook scenario where contacts between distal DNA sites are established by cognate binders. It has been shown to recapitulate key features of chromosome folding and to be able at predicting how phenotypes causing structural variants rewire the interactions between genes and regulators.     

Cytokine gene polymorphisms are associated with risk of urinary bladder cancer and recurrence after BCG immunotherapy

The association of interleukin-1β (IL-1B) -511C?>?T and IL-1 receptor antagonist (IL-1RN) VNTR, transforming growth factor-β (TGF-B1) +28C?>?T and interferon-γ (IFN-G)?+?874T>A polymorphisms with bladder cancer (CaB) susceptibility and risk of recurrence in Bacillus Calmette–Guérin (BCG)-treated patients was analyzed in 287 controls and 213 CaB patients (73 BCG treated). Increased risk was observed with the IL-1RN*2 allele (odds ratio (OR) 5.01) and the IFN-G +874 A allele (OR 1.78). TGF-B TT and IFN-G +874 A carriers were associated with reduced (hazard ratio (HR) 0.37) and enhanced (HR 2.24) risk of recurrence after BCG immunotherapy, respectively. The study suggests that cytokine gene variants may modulate CaB susceptibility and risk of recurrence after BCG immunotherapy.