Geometrical aspects of surface morphogenesis

This paper is concerned with the morphogenesis of structures which form thin deformable sheets. A general formalism is presented for the deformation of a sheet in the presence of an isotropic local body stress. This formalism leads to a set of equations, based on the theory of shells, in which corrections are made in the geometry due to large deformations. Under certain conditions the equations may be solved to give the surface metric tensor as a function of the local tension. A numerical example based on a simple "threshold" model is also presented.     

Enzyme organization and stability of metabolic pathways: A comparison of various approaches

The aim of this paper is to compare various methods for the quantification of metabolic pathways dynamics. A Yates-Pardee metabolic pathway with enzyme organization, i.e. with spatial localization of the enzymes in a specific cellular compartment, was studied using: (i) the classical Henri-Michaelis-Menten (HMM) equations, (ii) linearization of the HMM equations in the vicinity of a steady state (linearized formalism), and (iii) Biochemical Systems Theory formalism (BST formalism). It is shown that transient solutions computed via either the linearized formalism or the BST formalism can greatly differ from transient solutions computed with the HMM equations. However, in the studied example, results remain qualitatively the same for the three formalisms. This suggests that the study of the topology of the system may give useful insights into the metabolic pathways dynamics.     

On the use of qualitative reasoning to simulate and identify metabolic pathways

MOTIVATION: Perhaps the greatest challenge of modern biology is to develop accurate in silico models of cells. To do this we require computational formalisms for both simulation (how according to the model the state of the cell evolves over time) and identification (learning a model cell from observation of states). We propose the use of qualitative reasoning (QR) as a unified formalism for both tasks. The two most commonly used alternative methods of modelling biochemical pathways are ordinary differential equations (ODEs), and logical/graph-based (LG) models. RESULTS: The QR formalism we use is an abstraction of ODEs. It enables the behaviour of many ODEs, with different functional forms and parameters, to be captured in a single QR model. QR has the advantage over LG models of explicitly including dynamics. To simulate biochemical pathways we have developed 'enzyme' and 'metabolite' QR building blocks that fit together to form models. These models are finite, directly executable, easy to interpret and robust. To identify QR models we have developed heuristic chemoinformatics graph analysis and machine learning procedures. The graph analysis procedure is a series of constraints and heuristics that limit the number of ways metabolites can combine to form pathways. The machine learning procedure is generate-and-test inductive logic programming. We illustrate the use of QR for modelling and simulation using the example of glycolysis. AVAILABILITY: All data and programs used are available on request.     

Limitations of entropy maximization in ecology

Applying ideas of statistical mechanics in ecology have recently received quite some attention. The entropy maximization (EM) formalism looks particularly attractive, as it provides a simple algorithm to infer detailed system variables from a limited number of constraints. However, we point out that a blind application of this formalism can easily lead to wrong conclusions. To illustrate this, we reanalyze an ecological data set that has been used to claim the good performance of EM in predicting species abundances from trait measurements. We show that these results are entirely due to the restrictive constraints, and do not provide any support for the applicability of EM in ecology. By comparing with a simple example from physics, we indicate which characteristic mechanism of EM, and of statistical mechanics in general, is missing for the ecological example. This analysis introduces a series of methods to evaluate future attempts to apply EM in ecology.     

Random Leslie matrices in population dynamics

We generalize the concept of the population growth rate when a Leslie matrix has random elements (correlated or not), i.e., characterizing the disorder in the vital parameters. In general, we present a perturbative formalism to deal with linear non-negative random matrix difference equations, then the non-trivial effective eigenvalue of which defines the long-time asymptotic dynamics of the mean-value population vector state is presented as the effective growth rate. This effective eigenvalue is calculated from the smallest positive root of a secular polynomial. Analytical (exact and perturbative calculations) results are presented for several models of disorder. In particular, a 3 × 3 numerical example is applied to study the effective growth rate characterizing the long-time dynamics of a biological population model. The present analysis is a perturbative method for finding the effective growth rate in cases when the vital parameters may have negative covariances across populations.     

Piecewise-linear Models of Genetic Regulatory Networks: Equilibria and their Stability

A formalism based on piecewise-linear (PL) differential equations, originally due to Glass and Kauffman, has been shown to be well-suited to modelling genetic regulatory networks. However, the discontinuous vector field inherent in the PL models raises some mathematical problems in defining solutions on the surfaces of discontinuity. To overcome these difficulties we use the approach of Filippov, which extends the vector field to a differential inclusion. We study the stability of equilibria (called singular equilibrium sets) that lie on the surfaces of discontinuity. We prove several theorems that characterize the stability of these singular equilibria directly from the state transition graph, which is a qualitative representation of the dynamics of the system. We also formulate a stronger conjecture on the stability of these singular equilibrium sets.     

Macroscopic Models of Local Field Potentials and the Apparent 1/f Noise in Brain Activity

The power spectrum of local field potentials (LFPs) has been reported to scale as the inverse of the frequency, but the origin of this 1/f noise is at present unclear. Macroscopic measurements in cortical tissue demonstrated that electric conductivity (as well as permittivity) is frequency-dependent, while other measurements failed to evidence any dependence on frequency. In this article, we propose a model of the genesis of LFPs that accounts for the above data and contradictions. Starting from first principles (Maxwell equations), we introduce a macroscopic formalism in which macroscopic measurements are naturally incorporated, and also examine different physical causes for the frequency dependence. We suggest that ionic diffusion primes over electric field effects, and is responsible for the frequency dependence. This explains the contradictory observations, and also reproduces the 1/f power spectral structure of LFPs, as well as more complex frequency scaling. Finally, we suggest a measurement method to reveal the frequency dependence of current propagation in biological tissue, and which could be used to directly test the predictions of this formalism.     

Species-area curves, diversity indices, and species abundance distributions: a multifractal analysis

Although fractals have been applied in ecology for some time, multifractals have, in contrast, received little attention. In this article, we apply multifractals to the species-area relationship and species abundance distributions. We highlight two results: first, species abundance distributions collected at different spatial scales may collapse into a single curve after appropriate renormalization, and second, the power-law form of the species-area relationship and the Shannon, Simpson, and Berger-Parker diversity indices belong to a family of equations relating the species number, species abundance, and area through the moments of the species abundance-probability density function. Explicit formulas for these diversity indices, as a function of area, are derived. Methods to obtain the multifractal spectra from a data set are discussed, and an example is shown with data on tree and shrub species collected in a 50-ha plot on Barro Colorado Island, Panama. Finally, we discuss the implications of the multifractal formalism to the relationship between species range and abundance and the relation between the shape of the species abundance distribution and area.     

A Rapid-Mutation Approximation for Cell Population Dynamics

Carcinogenesis and cancer progression are often modeled using population dynamics equations for a diverse somatic cell population undergoing mutations or other alterations that alter the fitness of a cell and its progeny. Usually it is then assumed, paralleling standard mathematical approaches to evolution, that such alterations are slow compared to selection, i.e., compared to subpopulation frequency changes induced by unequal subpopulation proliferation rates. However, the alterations can be rapid in some cases. For example, results in our lab on in vitro analogues of transformation and progression in carcinogenesis suggest there could be periods where rapid alterations triggered by horizontal intercellular transfer of genetic material occur and quickly result in marked changes of cell population structure. We here initiate a mathematical study of situations where alterations are rapid compared to selection. A classic selection-mutation formalism is generalized to obtain a “proliferation-alteration” system of ordinary differential equations, which we analyze using a rapid-alteration approximation. A system-theoretical estimate of the total-population net growth rate emerges. This rate characterizes the diverse, interacting cell population acting as a single system; it is a weighted average of subpopulation rates, the weights being components of the Perron–Frobenius eigenvector for an ergodic Markov-process matrix that describes alterations by themselves. We give a detailed numerical example to illustrate the rapid-alteration approximation, suggest a possible interpretation of the fact that average aneuploidy during cancer progression often appears to be comparatively stable in time, and briefly discuss possible generalizations as well as weaknesses of our approach.     

Linear network representation of multistate models of transport.

By introducing external driving forces in rate-theory models of transport we show how the Eyring rate equations can be transformed into Ohm's law with potentials that obey Kirchhoff's second law. From such a formalism the state diagram of a multioccupancy multicomponent system can be directly converted into linear network with resistors connecting nodal (branch) points and with capacitances connecting each nodal point with a reference point. The external forces appear as emf or current generators in the network. This theory allows the algebraic methods of linear network theory to be used in solving the flux equations for multistate models and is particularly useful for making proper simplifying approximation in models of complex membrane structure. Some general properties of linear network representation are also deduced. It is shown, for instance, that Maxwell's reciprocity relationships of linear networks lead directly to Onsager's relationships in the near equilibrium region. Finally, as an example of the procedure, the equivalent circuit method is used to solve the equations for a few transport models.     

Positive circuits and d-dimensional spatial differentiation: application to the formation of sense organs in Drosophila

We discuss a rule proposed by the biologist Thomas according to which the possibility for a genetic network (represented by a signed directed graph called a regulatory graph) to have several stable states implies the existence of a positive circuit. This result is already known for different models, differential or discrete formalism, but always with a network of genes contained in a single cell. Thus, we can ask about the validity of this rule for a system containing several cells and with intercellular genetic interactions. In this paper, we consider the genetic interactions between several cells located on a d-dimensional lattice, i.e., each point of lattice represents a cell to which we associate the expression level of n genes contained in this cell. With this configuration, we show that the existence of a positive circuit is a necessary condition for a specific form of multistationarity, which naturally corresponds to spatial differentiation. We then illustrate this theorem through the example of the formation of sense organs in Drosophila.     

Effects of detergent micelles on the recombination reaction of opsin and 11-cis-retinal

When detergent-solubilized proteins interact with hydrophobic or amphiphilic molecules in the presence of detergent micelles, the solubility of the latter species in the micelles must be included in both thermodynamic and kinetic treatments. In this paper, we derive equations which describe the distribution of species present at equilibrium for a system in which a detergent-solubilized protein binds a hydrophobic (or amphiphilic) ligand. We have applied the formalism developed in this paper to the reaction describing the formation of rhodopsin from its apoprotein and 11-cis-retinal. Qualitatively, the results demonstrate that a significant portion of the observed decrease in the extent of recombination for rhodopsin solubilized in either sodium cholate or Tween 80 may be attributed to the partition of retinal into detergent micelles and that a detergent-induced protein denaturation need not be invoked to explain the data. We also discuss results for rhodopsin solubilized in a nonionic detergent (octaethylene glycol n-dodecyl ether) in which the detergent is clearly causing irreversible loss of the capability to recombine with 11-cis-retinal.     

Hierarchically organized populations: interactions between individual,population, and ecosystem levels

We consider a population of individuals which can be distributed in different equivalence classes. These classes are gathered in groups so that intragroup transformations are much more frequent than intergroup ones. We study linear systems in general, illustrated by the example of coupled individual and population levels. Then, we study nonlinear systems with the example of coupled population and ecosystem levels. We give methods to derive the dynamical equations for the different levels and to calculate interlevel coupling terms. We compare the coupling effects in the linear and in the nonlinear case.     

Biochemical systems theory: increasing predictive power by using second-order derivatives measurements

Models based on the power-law formalism provide a useful tool for analyzing metabolic systems. Within this methodology, the S-system variant furnishes the best strategy. In this paper we explore an extension of this formalism by considering second-order derivative terms of the Taylor series which the power-law is based upon. Results show that the S-system equations which include second-order Taylor coefficients give better accuracy in predicting the response of the system to a perturbation. Hence, models based on this new approach could provide a useful tool for quantitative purposes if one is able to measure the required derivatives experimentally. In particular we show the utility of this approach when it comes to discriminating between two mechanisms that are equivalent in the S-system a representation based on first-order coefficients. However, the loss of analytical tractability is a serious disadvantage for using this approach as a general tool for studying metabolic systems.     

Calculation of physiological acid-base parameters in multicompartment systems with application to human blood.

A general formalism for calculating parameters describing physiological acid-base balance in single compartments is extended to multicompartment systems and demonstrated for the multicompartment example of human whole blood. Expressions for total titratable base, strong ion difference, change in total titratable base, change in strong ion difference, and change in Van Slyke standard bicarbonate are derived, giving calculated values in agreement with experimental data. The equations for multicompartment systems are found to have the same mathematical interrelationships as those for single compartments, and the relationship of the present formalism to the traditional form of the Van Slyke equation is also demonstrated. The multicompartment model brings the strong ion difference theory to the same quantitative level as the base excess method.     

The systematic formulation of population models for insects with dynamically varying instar duration

We develop a formalism for insect population dynamics which covers the situation where maturation from one instar to its successor is triggered by weight gain and not by chronological age. We specify assumptions which result in the instantaneous “subpopulations” of various instars obeying delay-defferential equations with time delays (representing instar duration) which are themselves dynamic variables, changing in response to the availability of food. We demonstrate the stabilizing potential of variable time delays by studying an idealised two-stage model in which maturation to the adult stage occurs after absorption of a given (fixed) quantity of food.