Theoretical investigation of the dependence of population parameters on initial population size.

In a series of experiments with yeast, classical dynamical models were fitted to populations that differed only in their initial population size (Pylvänäinen 2005). The results revealed a surprising dependence between estimated growth rate and initial population size. Perceived as an artefact, this undesired relationship was tentatively removed by an ad-hoc procedure. This strategy reflects the usual approach of population models in which parameters are not considered to depend on initial conditions. However, our analysis reveals that the observed relationship between estimated growth rate and initial population size is unavoidable when the dimension of a system is reduced. For the present case, the two-dimensional food-yeast system was reduced to a model for yeast only. The consequence of system reduction questions our conception of one-dimensional population models.

Phylogenetic constraints and adaptation explain food-web structure.

Food webs are descriptions of who eats whom in an ecosystem. Although extremely complex and variable, their structure possesses basic regularities. A fascinating question is to find a simple model capturing the underlying processes behind these repeatable patterns. Until now, two models have been devised for the description of trophic interactions within a natural community. Both are essentially based on the concept of ecological niche, with the consumers organized along a single niche dimension; for example, prey size. Unfortunately, they fail to describe adequately recent and high-quality data. Here, we propose a new model built on the hypothesis that any species' diet is the consequence of phylogenetic constraints and adaptation. Simple rules incorporating both concepts yield food webs whose structure is very close to real data. Consumers are organized in groups forming a nested hierarchy, which better reflects the complexity and multidimensionality of most natural systems.

Complexity in quantitative food webs.

Food webs depict who eats whom in communities. Ecologists have examined statistical metrics and other properties of food webs, but mainly due to the uneven quality of the data, the results have proved controversial. The qualitative data on which those efforts rested treat trophic interactions as present or absent and disregard potentially huge variation in their magnitude, an approach similar to analyzing traffic without differentiating between highways and side roads. More appropriate data are now available and were used here to analyze the relationship between trophic complexity and diversity in 59 quantitative food webs from seven studies (14-202 species) based on recently developed quantitative descriptors. Our results shed new light on food-web structure. First, webs are much simpler when considered quantitatively, and link density exhibits scale invariance or weak dependence on food-web size. Second, the "constant connectance" hypothesis is not supported: connectance decreases with web size in both qualitative and quantitative data. Complexity has occupied a central role in the discussion of food-web stability, and we explore the implications for this debate. Our findings indicate that larger webs are more richly endowed with the weak trophic interactions that recent theories show to be responsible for food-web stability.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

FiRe and microarrays: a fast answer to burning questions.

FiRe is a user-friendly Excel macro designed to survey microarray data rapidly. This software interactively assembles data from different experiments and produces lists of candidate genes according to patterns of gene expression. Furthermore, macros bundled with FiRe can compare lists of genes, merge information from different spreadsheets, link candidates to information available from web-based databases, and produce heat-maps for easy visualization of microarray data. FiRe is freely available at http://www.unifr.ch/plantbio/FiRe/main.html .

Mathematical Modeling of the Dynamics of Shoot-Root Interactions and Resource Partitioning in Plant Growth.

Plants are highly plastic in their potential to adapt to changing environmental conditions. For example, they can selectively promote the relative growth of the root and the shoot in response to limiting supply of mineral nutrients and light, respectively, a phenomenon that is referred to as balanced growth or functional equilibrium. To gain insight into the regulatory network that controls this phenomenon, we took a systems biology approach that combines experimental work with mathematical modeling. We developed a mathematical model representing the activities of the root (nutrient and water uptake) and the shoot (photosynthesis), and their interactions through the exchange of the substrates sugar and phosphate (Pi). The model has been calibrated and validated with two independent experimental data sets obtained with Petunia hybrida. It involves a realistic environment with a day-and-night cycle, which necessitated the introduction of a transitory carbohydrate storage pool and an endogenous clock for coordination of metabolism with the environment. Our main goal was to grasp the dynamic adaptation of shoot:root ratio as a result of changes in light and Pi supply. The results of our study are in agreement with balanced growth hypothesis, suggesting that plants maintain a functional equilibrium between shoot and root activity based on differential growth of these two compartments. Furthermore, our results indicate that resource partitioning can be understood as the emergent property of many local physiological processes in the shoot and the root without explicit partitioning functions. Based on its encouraging predictive power, the model will be further developed as a tool to analyze resource partitioning in shoot and root crops.

Conduction velocity of nerve and muscle fiber action potentials after a space mission or a bed rest.

OBJECTIVE: The purpose of the present investigation was to study the readaptation of a human muscle after a prolonged stay in microgravity and after a bed rest of several months. METHODS: The surface electromyogram of the soleus muscle was recorded in 6 cosmonauts and 6 bed rest subjects at 5 different torque levels and, in addition, the direct muscle responses (M responses) to supramaximal stimulation of the posterior tibial nerve were also recorded in the bed rest subjects. In a supplementary experiment in normal subjects, M response was recorded with an array of electrodes. RESULTS: The median frequency (MF) of the power spectrum of the surface electromyogram was reduced, at all torque levels, immediately after the test period. In the bed rest subjects, the latency of the M response peaks and the inter-peak interval increased during the test period. Recovery to normal occurred within about 10 days. In the normal subjects, the peaks of the M response were conducted along the muscle with a velocity between 21 and 30 m/s. CONCLUSIONS: All these results point to a reduction of the conduction velocity in the branching axon terminals and in the muscle fibers during space missions and bed rest.