Quelques aspects des réactions noyau-noyau aux énergies moyennes

École thématiqu

Toward Contention Analysis for Parallel Executing Real-Time Tasks

In measurement-based probabilistic timing analysis, the execution conditions imposed to tasks as measurement scenarios, have a strong impact to the worst-case execution time estimates. The scenarios and their effects on the task execution behavior have to be deeply investigated. The aim has to be to identify and to guarantee the scenarios that lead to the maximum measurements, i.e. the worst-case scenarios, and use them to assure the worst-case execution time estimates. We propose a contention analysis in order to identify the worst contentions that a task can suffer from concurrent executions. The work focuses on the interferences on shared resources (cache memories and memory buses) from parallel executions in multi-core real-time systems. Our approach consists of searching for possible task contenders for parallel executions, modeling their contentiousness, and classifying the measurement scenarios accordingly. We identify the most contentious ones and their worst-case effects on task execution times. The measurement-based probabilistic timing analysis is then used to verify the analysis proposed, qualify the scenarios with contentiousness, and compare them. A parallel execution simulator for multi-core real-time system is developed and used for validating our framework. The framework applies heuristics and assumptions that simplify the system behavior. It represents a first step for developing a complete approach which would be able to guarantee the worst-case behavior

Influence of M-phase chromatin on the anisotropy of microtubule asters

In many eukaryotic cells going through M-phase, a bipolar spindle is formed by microtubules nucleated from centrosomes. These microtubules, in addition to being "captured" by kinetochores, may be stabilized by chromatin in two different ways: short-range stabilization effects may affect microtubules in close contact with the chromatin, while long-range stabilization effects may "guide" microtubule growth towards the chromatin (e.g., by introducing a diffusive gradient of an enzymatic activity that affects microtubule assembly). Here, we use both meiotic and mitotic extracts from Xenopus laevis eggs to study microtubule aster formation and microtubule dynamics in the presence of chromatin. In "low-speed" meiotic extracts, in the presence of salmon sperm chromatin, we find that short-range stabilization effects lead to a strong anisotropy of the microtubule asters. Analysis of the dynamic parameters of microtubule growth show that this anisotropy arises from a decrease in the catastrophe frequency, an increase in the rescue frequency and a decrease in the growth velocity. In this system we also find evidence for long-range "guidance" effects, which lead to a weak anisotropy of the asters. Statistically relevant results on these long-range effects are obtained in "high-speed" mitotic extracts in the presence of artificially constructed chromatin stripes. We find that aster anisotropy is biased in the direction of the chromatin and that the catastrophe frequency is reduced in its vicinity. In this system we also find a surprising dependence of the catastrophe and the rescue frequencies on the length of microtubules nucleated from centrosomes: the catastrophe frequency increase and the rescue frequency decreases with microtubule length

Statistical mechanics for metabolic networks during steady-state growth

Which properties of metabolic networks can be derived solely from stoichiometric information about the network's constituent reactions? Predictive results have been obtained by Flux Balance Analysis (FBA), by postulating that cells set metabolic fluxes within the allowed stoichiometry so as to maximize their growth. Here, we generalize this framework to single cell level using maximum entropy models from statistical physics. We define and compute, for the core metabolism of Escherichia coli, a joint distribution over all fluxes that yields the experimentally observed growth rate. This solution, containing FBA as a limiting case, provides a better match to the measured fluxes in the wild type and several mutants. We find that E. coli metabolism is close to, but not at, the optimality assumed by FBA. Moreover, our model makes a wide range of predictions: (i) on flux variability, its regulation, and flux correlations across individual cells; (ii) on the relative importance of stoichiometric constraints vs. growth rate optimization; (iii) on quantitative scaling relations for singe-cell growth rate distributions. We validate these scaling predictions using data from individual bacterial cells grown in a microfluidic device at different sub-inhibitory antibiotic concentrations. Under mild dynamical assumptions, fluctuation-response relations further predict the autocorrelation timescale in growth data and growth rate adaptation times following an environmental perturbation.Comment: 12 pages, 4 figure

Noise Underlies Switching Behavior of the Bacterial Flagellum

We report the switching behavior of the full bacterial flagellum system that includes the filament and the motor in wild-type Escherichia coli cells. In sorting the motor behavior by the clockwise bias, we find that the distributions of the clockwise (CW) and counterclockwise (CCW) intervals are either exponential or nonexponential with long tails. At low bias, CW intervals are exponentially distributed and CCW intervals exhibit long tails. At intermediate CW bias (0.5) both CW and CCW intervals are mainly exponentially distributed. A simple model suggests that these two distinct switching behaviors are governed by the presence of signaling noise within the chemotaxis network. Low noise yields exponentially distributed intervals, whereas large noise yields nonexponential behavior with long tails. These drastically different motor statistics may play a role in optimizing bacterial behavior for a wide range of environmental conditions.Molecular and Cellular Biolog