Predicting regrowth of low-grade gliomas after radiotherapy.

Diffuse low grade gliomas are invasive and incurable brain tumors that inevitably transform into higher grade ones. A classical treatment to delay this transition is radiotherapy (RT). Following RT, the tumor gradually shrinks during a period of typically 6 months to 4 years before regrowing.

Levy geometric graphs.

We present a family of graphs with remarkable properties. They are obtained by connecting the points of a random walk when their distance is smaller than a given scale. Their degree (number of neighbors) does not depend on the graph's size but only on the considered scale.

The Effect of Radiotherapy on Diffuse Low-Grade Gliomas Evolution: Confronting Theory with Clinical Data.

Diffuse low-grade gliomas are slowly growing tumors that always recur after treatment. In this paper, we revisit the modeling of the evolution of the tumor radius before and after the radiotherapy process and propose a novel model that is simple yet biologically motivated and that remedies some shortcomings of previously proposed ones. We confront this with clinical data consisting of time series of tumor radii from 43 patient records by using a stochastic optimization technique and obtain very good fits in all cases.

Effective epidemic model for COVID-19 using accumulated deaths.

The severe acute respiratory syndrome COVID-19 has been in the center of the ongoing global health crisis in 2020. The high prevalence of mild cases facilitates sub-notification outside hospital environments and the number of those who are or have been infected remains largely unknown, leading to poor estimates of the crude mortality rate of the disease. Here we use a simple model to describe the number of accumulated deaths caused by COVID-19.

Experimental and modeling study of the formation of cell aggregates with differential substrate adhesion.

The study of cell aggregation in vitro has a tremendous importance these days. In cancer biology, aggregates and spheroids serve as model systems and are considered as pseudo-tumors that are more realistic than 2D cell cultures. Recently, in the context of brain tumors (gliomas), we developed a new poly(ethylene glycol) (PEG)-based hydrogel, with adhesive properties that can be controlled by the addition of poly(L-lysine) (PLL), and a stiffness close to the brain's.

Modeling the dynamics of oligodendrocyte precursor cells and the genesis of gliomas.

Oligodendrocyte precursor cells (OPCs) have remarkable properties: they represent the most abundant cycling cell population in the adult normal brain and they manage to achieve a uniform and constant density throughout the adult brain. This equilibrium is obtained by the interplay of four processes: division, differentiation or death, migration and active self-repulsion. They are also strongly suspected to be at the origin of gliomas, when their equilibrium is disrupted.

Surgical Decision Making From Image-Based Biophysical Modeling of Glioblastoma: Not Ready for Primetime.

Background: Biophysical modeling of glioma is gaining more interest for clinical practice. The most popular model describes aggressivity of tumor cells by two parameters: net proliferation rate (ρ) and propensity to migrate (D). The ratio ρ/D, which can be estimated from a single preoperative magnetic resonance imaging (MRI), characterizes tumor invasiveness profile (high ρ/D: nodular; low ρ/D: diffuse).

Arterial Spin Labeling to Predict Brain Tumor Grading in Children: Correlations between Histopathologic Vascular Density and Perfusion MR Imaging.

Purpose To compare arterial spin labeling (ASL) data between low- and high-grade brain tumors in children to establish a cutoff to distinguish low- from high-grade neoplasms and to assess potential correlations between cerebral blood flow (CBF) and quantitative histologic microvascular data. Materials and Methods Approval was obtained from the regional review board. ASL data obtained in 129 children between 2011 and 2015 were retrospectively analyzed.

ROCK1 and 2 differentially regulate actomyosin organization to drive cell and synaptic polarity.

RhoGTPases organize the actin cytoskeleton to generate diverse polarities, from front-back polarity in migrating cells to dendritic spine morphology in neurons. For example, RhoA through its effector kinase, RhoA kinase (ROCK), activates myosin II to form actomyosin filament bundles and large adhesions that locally inhibit and thereby polarize Rac1-driven actin polymerization to the protrusions of migratory fibroblasts and the head of dendritic spines. We have found that the two ROCK isoforms, ROCK1 and ROCK2, differentially regulate distinct molecular pathways downstream of RhoA, and their coordinated activities drive polarity in both cell migration and synapse formation.

Oedema-based model for diffuse low-grade gliomas: application to clinical cases under radiotherapy.

Objectives: Diffuse low-grade gliomas are characterized by slow growth. Despite appropriate treatment, they change inexorably into more aggressive forms, jeopardizing the patient's life. Optimizing treatments, for example with the use of mathematical modelling, could help to prevent tumour regrowth and anaplastic transformation.

The silent phase of diffuse low-grade gliomas. Is it when we missed the action?

Background: It is commonly believed that, before being diagnosed after onset of symptoms, diffuse low-grade glioma evolve silently for a long time. The present study aimed to estimate for the first time the exact duration of this silent phase, during which the glioma is radiologically visible but undiscovered.

Methods: We retrospectively reviewed our French national database of diffuse low-grade glioma, searching for patients with an MRI-based assessment of their velocity of diameter growth at diagnosis and before any treatment (at least three MRIs over more than 6 months).

Analyzing huge pathology images with open source software.

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.

Quantitative characterization of the imaging limits of diffuse low-grade oligodendrogliomas.

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 to date. However, they are of the utmost importance if one wishes to develop realistic models for diffuse glioma growth.

Exclusion processes: short-range correlations induced by adhesion and contact interactions.

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.

Modeling the role of water in Bacillus subtilis colonies.

We propose a simple cellular automaton model for the description of the evolution of a colony of Bacillus subtilis. The originality of our model lies in the fact that the bacteria can move in a pool of liquid. We assume that each migrating bacterium is surrounded by an individual pool, and the overlap of the latter gives rise to a collective pool with a higher water level.

Improving the time-machine: estimating date of birth of grade II gliomas.

Objectives: Here we present a model aiming to provide an estimate of time from tumour genesis, for grade II gliomas. The model is based on a differential equation describing the diffusion-proliferation process. We have applied our model to situations where tumour diameter was shown to increase linearly with time, with characteristic diametric velocity.

Modelling intercellular communication and its effects on tumour invasion.

We present a model aiming at the description of intercellular communication on the invasive character of gliomas. We start from a previous model of ours based on a cellular automaton and develop a new version of it in a three-dimensional geometry. Introducing the hydrodynamic limit of the automaton we obtain a macroscopic model involving a nonlinear diffusion equation.

Diffuse low-grade oligodendrogliomas extend beyond MRI-defined abnormalities.

Background: Imaging determinations of the spatial extent of diffuse low-grade gliomas (DLGGs) are of paramount importance in evaluating the risk-to-benefit ratio of surgical resection. However, it is not clear how accurately preoperative conventional MRI can delineate DLGGs.

Methods: We report a retrospective histologic and imaging correlation study in 16 adult patients who underwent serial stereotactic biopsies for the diagnosis of untreated supratentorial well-defined and non-contrast-enhanced DLGG, in whom biopsy samples were taken within and beyond (OutBSs) MRI-defined abnormalities.

Pregnancy increases the growth rates of World Health Organization grade II gliomas.

Twelve pregnancies in 11 adult women harboring World Health Organization (WHO) grade II gliomas (GIIGs) prior to pregnancy were reviewed to address whether pregnancy affects tumor growth using a quantitative approach of the radiological velocity of diametric expansion (VDE) on successive magnetic resonance images. VDE was significantly increased during pregnancy as compared to prepregnancy (p < 0.001) and to postdelivery (p = 0.

Modeling tumor cell migration: From microscopic to macroscopic models.

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.

A model for short- and long-range interactions of migrating tumour cell.

We examine the consequences of long-range effects on tumour cell migration. Our starting point are previous results of ours where we have shown that the migration patterns of glioma cells are best interpreted if one assumes attractive interactions between cells. Here we complement the cellular automaton model previously introduced by the assumption of the existence of a chemorepellent produced by the main bulk of large spheroids (in the hypoxic/necrotic areas).

A model for glioma cell migration on collagen and astrocytes.

We present a model for the migration of glioma cells on substrates of collagen and astrocytes. The model is based on a cellular automaton where the various dynamical effects are introduced through adequate evolution rules. Using our model, we investigate the role of homotype and heterotype gap junction communication and show that it is possible to reproduce the corresponding experimental migration patterns.

A cellular automaton model for the migration of glioma cells.

We present a study of in vitro cell migration in two dimensions as a first step towards understanding the mechanisms governing the motility of glioma cells. Our study is based on a cellular automaton model which aims at reproducing the kinetics of a lump of glioma cells deposited on a substrate of collagen. The dynamical effects of cell attraction and motion inertia are introduced through adequate automaton rules.

Biophysical and phenomenological models of multiple spike interactions in spike-timing dependent plasticity.

Spike-timing dependent plasticity (STDP) is a form of associative synaptic modification which depends on the respective timing of pre- and post-synaptic spikes. The biophysical mechanisms underlying this form of plasticity are currently not known. We present here a biophysical model which captures the characteristics of STDP, such as its frequency dependency, and the effects of spike pair or spike triplet interactions.

A method to estimate synaptic conductances from membrane potential fluctuations.

In neocortical neurons, network activity can activate a large number of synaptic inputs, resulting in highly irregular subthreshold membrane potential (V(m)) fluctuations, commonly called "synaptic noise." This activity contains information about the underlying network dynamics, but it is not easy to extract network properties from such complex and irregular activity. Here, we propose a method to estimate properties of network activity from intracellular recordings and test this method using theoretical and experimental approaches.