Lecturer at the University Paris Diderot (Paris 7), doing his research in the IMNC laboratory, in the team for modeling of biological systems. Formerly post-doc, in the team of Thomas Nattermann. Former PhD student at the LPTENS under the advice of Rémi Monasson.
Campus d'Orsay - Building 104
91406 Orsay CEDEX - France
E-mail: deroulers # imnc.in2p3.fr |
Phone: +33 1 69 15 36 41
Fax: +33 1 69 15 71 96
Background: Digital pathology images are increasingly used both
for diagnosis and research, because slide scanners are nowadays broadly
available and because the quantitative study of these images yields new
insights in systems biology. However, such virtual slides build up a
technical challenge since the images occupy often several gigabytes and
cannot be fully opened in a computer's memory. Moreover, there is no
standard format. Therefore, most common open source tools such as ImageJ
fail at treating them, and the others require expensive hardware while
still being prohibitively slow.
Results: We have developed several cross-platform open source software tools to overcome these limitations. The NDPITools provide a way to transform microscopy images initially in the loosely supported NDPI format into one or several standard TIFF files, and to create mosaics (division of huge images into small ones, with or without overlap) in various TIFF and JPEG formats. They can be driven through ImageJ plugins. The LargeTIFFTools achieve similar functionality for huge TIFF images which do not fit into RAM. We test the performance of these tools on several digital slides and compare them, when applicable, to standard software. A statistical study of the cells in a tissue sample from an oligodendroglioma was performed on an average laptop computer to demonstrate the efficiency of the tools.
Conclusions: Our open source software enables dealing with huge images with standard software on average computers. They are cross-platform, independent of proprietary libraries and very modular, allowing them to be used in other open source projects. They have excellent performance in terms of execution speed and RAM requirements. They open promising perspectives both to the clinician who wants to study a single slide and to the research team or data centre who do image analysis of many slides on a computer cluster.
Background: Supratentorial diffuse low-grade gliomas in adults
extend beyond maximal visible MRI-defined abnormalities and a gap
exists between the imaging signal changes and the actual tumor
margins. Direct quantitative comparisons between imaging and
histological analyses are lacking even if they are mandatory to
develop realistic models for diffuse glioma growth.
Methods: In this study, we quantitatively compare the cell concentration and the edema fraction from human histological biopsy samples (BSs) performed within and outside imaging abnormalities during serial imaging- based stereotactic biopsy of diffuse low-grade gliomas.
Results: The cell concentration was significantly higher in BSs located inside (1189±378 cell/mm2) than outside (740±124 cell/mm2) MRI-defined abnormalities (p=0.0003). The edema fraction was significantly higher in BSs located inside (mean, 45±23%) than outside (mean, 5±9%) MRI-defined abnormalities (p<0.0001). At the MRI-defined abnormalities borders, the edema fraction corresponded to 20% whereas tumor cells occupied a mean surface of 3%. The cycling cell concentration was significantly higher in BSs located inside (10±12 cell/mm2) than outside (0.5±0.9 cell/mm2) MRI-defined abnormalities (p=0.0001).
Conclusions: We show that the margins of T2-weighted signal changes are mainly correlated to the edema fraction. In 62.5% of patients, the cycling tumor cell fraction (defined as the ratio of the cycling tumor cell concentration to the total number of tumor cells) was higher at the inner limits of the MRI-defined abnormalities than inside the tumor center. In the remaining patients, the cycling tumor cell fraction increased towards the center of the tumor.
We analyze the out-of-equilibrium behavior of exclusion processes where agents interact with their nearest neighbors, and we study the short-range correlations which develop because of the exclusion and other contact interactions. The form of interactions we focus on, including adhesion and contact-preserving interactions, is especially relevant for migration processes of living cells. We show the local agent density and nearest-neighbor two-point correlations resulting from simulations on two-dimensional lattices in the transient regime where agents invade an initially empty space from a source and in the stationary regime between a source and a sink. We compare the results of simulations with the corresponding quantities derived from the master equation of the exclusion processes, and in both cases, we show that, during the invasion of space by agents, a wave of correlations travels with velocity v(t) ~ t^(-1/2). The relative placement of this wave to the agent density front and the time dependence of its height may be used to discriminate between different forms of contact interactions or to quantitatively estimate the intensity of interactions. We discuss, in the stationary density profile between a full and an empty reservoir of agents, the presence of a discontinuity close to the empty reservoir. Then we develop a method for deriving approximate hydrodynamic limits of the processes. From the resulting systems of partial differential equations, we recover the self-similar behavior of the agent density and correlations during space invasion.
It has been shown experimentally that contact interactions may influence the migration of cancer cells. Previous works have modelized this thanks to stochastic, discrete models (cellular automata) at the cell level. However, for the study of the growth of real-size tumors with several million cells, it is best to use a macroscopic model having the form of a partial differential equation (PDE) for the density of cells. The difficulty is to predict the effect, at the macroscopic scale, of contact interactions that take place at the microscopic scale. To address this, we use a multiscale approach: starting from a very simple, yet experimentally validated, microscopic model of migration with contact interactions, we derive a macroscopic model. We show that a diffusion equation arises, as is often postulated in the field of glioma modeling, but it is nonlinear because of the interactions. We give the explicit dependence of diffusivity on the cell density and on a parameter governing cell-cell interactions. We discuss in detail the conditions of validity of the approximations used in the derivation, and we compare analytic results from our PDE to numerical simulations and to some in vitro experiments. We notice that the family of microscopic models we started from includes as special cases some kinetically constrained models that were introduced for the study of the physics of glasses, supercooled liquids, and jamming systems.
Motivated by recent experiments on nanowires and carbon nanotubes, we study theoretically the effect of strong, point-like impurities on the linear electrical resistance R of finite length quantum wires. Charge transport is limited by Coulomb blockade and cotunneling. ln R is slowly self-averaging and non Gaussian. Its distribution is Gumbel with finite-size corrections which we compute. At low temperatures, the distribution is similar to the variable range hopping (VRH) behaviour found long ago in doped semiconductors. We show that a result by Raikh and Ruzin does not apply. The finite-size corrections decay with the length L like 1/ln L. At higher temperatures, this regime is replaced by new laws and the shape of the finite-size corrections changes strongly: if the electrons interact weakly, the corrections vanish already for wires with a few tens impurities.
The probability Psuccess(α, N) that stochastic greedy algorithms successfully solve the random SATisfiability problem is studied as a function of the ratio α of constraints per variable and the number N of variables. These algorithms assign variables according to the unit-propagation (UP) rule in presence of constraints involving a unique variable (1-clauses), to some heuristic (H) prescription otherwise. In the infinite N limit, Psuccess vanishes at some critical ratio α_H which depends on the heuristic H. We show that the critical behaviour is determined by the UP rule only. In the case where only constraints with 2 and 3 variables are present, we give the phase diagram and identify two universality classes: the power law class, where Psuccess[αH (1+ε N-1/3), N] ∼ A(ε)/Nγ; the stretched exponential class, where Psuccess[αH (1+ε N-1/3), N] ∼ exp[-N1/6 Φ(ε)]. Which class is selected depends on the characteristic parameters of input data. The critical exponent γ is universal and calculated; the scaling functions A and Φ weakly depend on the heuristic H and are obtained from the solutions of reaction-diffusion equations for 1-clauses. Computation of some non-universal corrections allows us to match numerical results with good precision. The critical behaviour for constraints with >3 variables is given. Our results are interpreted in terms of dynamical graph percolation and we argue that they should apply to more general situations where UP is used.
The probability P(α, N) that search algorithms for random Satisfiability problems successfully find a solution is studied as a function of the ratio α of constraints per variable and the number N of variables. P is shown to be finite if α lies below an algorithm-dependent threshold α_A, and exponentially small in N above. The critical behaviour is universal for all algorithms based on the widely-used unitary propagation rule: P[ (1 + ε) αA , N] ∼ exp[-N1/6 Φ(ε N1/3) ]. Exponents are related to the critical behaviour of random graphs, and the scaling function Φ is exactly calculated through a mapping onto a diffusion-and-death problem.
A quantum field theoretic formulation of the dynamics of the Contact Process on a regular graph of degree z is introduced. A perturbative calculation in powers of 1/z of the effective potential for the density of particles φ(t) and an instantonic field ψ(t) emerging from the quantum formalism is performed. Corrections to the mean-field distribution of densities of particles in the out-of-equilibrium stationary state are derived in powers of 1/z. Results for typical (e.g. average density) and rare fluctuation (e.g. lifetime of the metastable state) properties are in very good agreement with numerical simulations carried out on D-dimensional hypercubic (z=2D) and Cayley lattices.
We study the dynamics of the q-state random bond Potts ferromagnet on the square lattice at its critical point by Monte Carlo simulations with single spin-flip dynamics. We concentrate on q=3 and q=24 and find, in both cases, conventional, rather than activated, dynamics. We also look at the distribution of relaxation times among different samples, finding different results for the two q values. For q=3 the relative variance of the relaxation time tau at the critical point is finite. However, for q=24 this appears to diverge in the thermodynamic limit and it is ln(tau) which has a finite relative variance. We speculate that this difference occurs because the transition of the corresponding pure system is second order for q=3 but first order for q=24.
View slides (in PDF format) by clicking on the talks' titles.
|Curriculum Vitae:||PostScript||outdated HTML version|
|Research project membership:|