Massimo Vergassola

Bio: Massimo Vergassola is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Intermittency & Turbulence. The author has an hindex of 54, co-authored 155 publications receiving 11703 citations. Previous affiliations of Massimo Vergassola include Centre national de la recherche scientifique & École Normale Supérieure.

Particles and fields in fluid turbulence

Abstract: The understanding of fluid turbulence has considerably progressed in recent years. The application of the methods of statistical mechanics to the description of the motion of fluid particles, i.e., to the Lagrangian dynamics, has led to a new quantitative theory of intermittency in turbulent transport. The first analytical description of anomalous scaling laws in turbulence has been obtained. The underlying physical mechanism reveals the role of statistical integrals of motion in nonequilibrium systems. For turbulent transport, the statistical conservation laws are hidden in the evolution of groups of fluid particles and arise from the competition between the expansion of a group and the change of its geometry. By breaking the scale-invariance symmetry, the statistically conserved quantities lead to the observed anomalous scaling of transported fields. Lagrangian methods also shed new light on some practical issues, such as mixing and turbulent magnetic dynamo.

The Listeria transcriptional landscape from saprophytism to virulence

Abstract: The bacterium Listeria monocytogenes is ubiquitous in the environment and can lead to severe food-borne infections. It has recently emerged as a multifaceted model in pathogenesis. However, how this bacterium switches from a saprophyte to a pathogen is largely unknown. Here, using tiling arrays and RNAs from wild-type and mutant bacteria grown in vitro, ex vivo and in vivo, we have analysed the transcription of its entire genome. We provide the complete Listeria operon map and have uncovered far more diverse types of RNAs than expected: in addition to 50 small RNAs (<500 nucleotides), at least two of which are involved in virulence in mice, we have identified antisense RNAs covering several open-reading frames and long overlapping 5' and 3' untranslated regions. We discovered that riboswitches can act as terminators for upstream genes. When Listeria reaches the host intestinal lumen, an extensive transcriptional reshaping occurs with a SigB-mediated activation of virulence genes. In contrast, in the blood, PrfA controls transcription of virulence genes. Remarkably, several non-coding RNAs absent in the non-pathogenic species Listeria innocua exhibit the same expression patterns as the virulence genes. Together, our data unravel successive and coordinated global transcriptional changes during infection and point to previously unknown regulatory mechanisms in bacteria.

"Infotaxis" as a strategy for searching without gradients

Abstract: Chemotactic bacteria are guided towards the source of a nutrient by local concentration gradients. That works on the microscopic scale, but at larger scales such local cues are unreliable pointers — for example, wind or water currents may disperse odours sought by foraging animals. Using statistical techniques, Vergassola et al. have developed a general search algorithm for movement strategies based on the detection of sporadic cues and partial information. The strategy, termed 'infotaxis' as it maximizes the expected rate of information gain, could find application in the design of 'sniffer' robots. A computational model of odour plume propagation and experimental data are used to devise a general search algorithm for movement strategies in chemotaxis, based on sporadic cues and partial information. The strategy is termed 'infotaxis' as it locally maximizes the expected rate of information gain. Chemotactic bacteria rely on local concentration gradients to guide them towards the source of a nutrient1. Such local cues pointing towards the location of the source are not always available at macroscopic scales because mixing in a flowing medium breaks up regions of high concentration into random and disconnected patches. Thus, animals sensing odours in air or water detect them only intermittently as patches sweep by on the wind or currents2,3,4,5,6. A macroscopic searcher must devise a strategy of movement based on sporadic cues and partial information. Here we propose a search algorithm, which we call ‘infotaxis’, designed to work under such conditions. Any search process can be thought of as acquisition of information on source location; for infotaxis, information plays a role similar to concentration in chemotaxis. The infotaxis strategy locally maximizes the expected rate of information gain. We demonstrate its efficiency using a computational model of odour plume propagation and experimental data on mixing flows7. Infotactic trajectories feature ‘zigzagging’ and ‘casting’ paths similar to those observed in the flight of moths8. The proposed search algorithm is relevant to the design of olfactory robots9,10,11, but the general idea of infotaxis can be applied more broadly in the context of searching with sparse information.

Lattice boltzmann method for fluid flows

Abstract: We present an overview of the lattice Boltzmann method (LBM), a parallel and efficient algorithm for simulating single-phase and multiphase fluid flows and for incorporating additional physical complexities. The LBM is especially useful for modeling complicated boundary conditions and multiphase interfaces. Recent extensions of this method are described, including simulations of fluid turbulence, suspension flows, and reaction diffusion systems.

Combinatorial microRNA target predictions.

Abstract: MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published microRNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results suggest widespread coordinate control executed by microRNAs. In particular, we experimentally validate common regulation of Mtpn by miR-375, miR-124 and let-7b and thus provide evidence for coordinate microRNA control in mammals.

Table Of Integrals Series And Products

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Isolation and characterization

Abstract: Isolation and Maintenance.- Isolation and Differentiation of Medaka Embryonic Stem Cells.- Maintenance of Chicken Embryonic Stem Cells In Vitro.- Derivation and Culture of Mouse Trophoblast Stem Cells In Vitro.- Derivation, Maintenance, and Characterization of Rat Embryonic Stem Cells In Vitro.- Derivation, Maintenance, and Induction of the Differentiation In Vitro of Equine Embryonic Stem Cells.- Generation and Characterization of Monkey Embryonic Stem Cells.- Derivation and Propagation of Embryonic Stem Cells in Serum- and Feeder-Free Culture.- Signaling in Embryonic Stem Cell Differentiation.- Internal Standards in Differentiating Embryonic Stem Cells In Vitro.- Matrix Assembly, Cell Polarization, and Cell Survival.- Phosphoinositides, Inositol Phosphates, and Phospholipase C in Embryonic Stem Cells.- Cripto Signaling in Differentiating Embryonic Stem Cells.- The Use of Embryonic Stem Cells to Study Hedgehog Signaling.- Transfection and Promoter Analysis in Embryonic Stem Cells.- SAGE Analysis to Identify Embryonic Stem Cell-Predominant Transcripts.- Utilization of Digital Differential Display to Identify Novel Targets of Oct3/4.- Gene Silencing Using RNA Interference in Embryonic Stem Cells.- Genetic Manipulation of Embryonic Stem Cells.- Efficient Transfer of HSV-1 Amplicon Vectors Into Embryonic Stem Cells and Their Derivatives.- Lentiviral Vector-Mediated Gene Transfer in Embryonic Stem Cells.- Use of the Cytomegalovirus Promoter for Transient and Stable Transgene Expression in Mouse Embryonic Stem Cells.- Use of Simian Immunodeficiency Virus Vectors for Simian Embryonic Stem Cells.- Generation of Green Fluorescent Protein-Expressing Monkey Embryonic Stem Cells.- DNA Damage Response and Mutagenesis in Mouse Embryonic Stem Cells.- Ultraviolet-Induced Apoptosis in Embryonic Stem Cells In Vitro.- Use of Embryonic Stem Cells in Pharmacological and Toxicological Screens.- Use of Differentiating Embryonic Stem Cells in Pharmacological Studies.- Embryonic Stem Cells as a Source of Differentiated Neural Cells for Pharmacological Screens.- Use of Murine Embryonic Stem Cells in Embryotoxicity Assays.- Use of Chemical Mutagenesis in Mouse Embryonic Stem Cells.- Epigenetic Analysis of Embryonic Stem Cells.- Nuclear Reprogramming of Somatic Nucleus Hybridized With Embryonic Stem Cells by Electrofusion.- Methylation in Embryonic Stem Cells In Vitro.- Tumor-Like Properties.- Identification of Genes Involved in Tumor-Like Properties of Embryonic Stem Cells.- In Vivo Tumor Formation From Primate Embryonic Stem Cells.- Animal Models and Therapy.- Directed Differentiation and Characterization of Genetically Modified Embryonic Stem Cells for Therapy.- Use of Differentiating Embryonic Stem Cells in the Parkinsonian Mouse Model.

Stochastic Processes in Physics and Chemistry

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