Mines ParisTech

About: Mines ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Microstructure. The organization has 6564 authors who have published 11676 publications receiving 359898 citations. The organization is also known as: École nationale supérieure des mines de Paris & École des mines de Paris.

Biofiltration of volatile organic compounds

Abstract: The removal of volatile organic compounds (VOCs) from contaminated airstreams has become a major air pollution concern. Improvement of the biofiltration process commonly used for the removal of odorous compounds has led to a better control of key parameters, enabling the application of biofiltration to be extended also to the removal of VOCs. Moreover, biofiltration, which is based on the ability of micro-organisms to degrade a large variety of compounds, proves to be economical and environmentally viable. In a biofilter, the waste gas is forced to rise through a layer of packed porous material. Thus, pollutants contained in the gaseous effluent are oxidised or converted into biomass by the action of microorganisms previously fixed on the packing material. The biofiltration process is then based on two principal phenomena: (1) transfer of contaminants from the air to the water phase or support medium, (2) bioconversion of pollutants to biomass, metabolic end-products, or carbon dioxide and water. The diversity of biofiltration mechanisms and their interaction with the microflora mean that the biofilter is defined as a complex and structured ecosystem. As a result, in addition to operating conditions, research into the microbial ecology of biofilters is required in order better to optimise the management of such biological treatment systems.

Controllability of quantum harmonic oscillators

Abstract: It is proven in a previous paper that any modal approximation of the one-dimensional quantum harmonic oscillator is controllable. We prove here that, contrary to such finite-dimensional approximations, the original infinite-dimensional system is not controllable: Its controllable part is of dimension 2 and corresponds to the dynamics of the average position. More generally, we prove that, for the quantum harmonic oscillator of any dimension, similar lacks of controllability occur whatever the number of control is: the controllable part still corresponds to the average position dynamics. We show, with the quantum particle in a moving quadratic potential, that some physically interesting motion planning questions can be however solved.

BAP1 complex promotes transcription by opposing PRC1-mediated H2A ubiquitylation.

Abstract: In Drosophila, a complex consisting of Calypso and ASX catalyzes H2A deubiquitination and has been reported to act as part of the Polycomb machinery in transcriptional silencing. The mammalian homologs of these proteins (BAP1 and ASXL1/2/3, respectively), are frequently mutated in various cancer types, yet their precise functions remain unclear. Using an integrative approach based on isogenic cell lines generated with CRISPR/Cas9, we uncover an unanticipated role for BAP1 in gene activation. This function requires the assembly of an enzymatically active BAP1-associated core complex (BAP1.com) containing one of the redundant ASXL proteins. We investigate the mechanism underlying BAP1.com-mediated transcriptional regulation and show that it does not participate in Polycomb-mediated silencing. Instead, our results establish that the function of BAP1.com is to safeguard transcriptionally active genes against silencing by the Polycomb Repressive Complex 1.

Large-scale prediction of protein-protein interactions from structures

Abstract: Background The prediction of protein-protein interactions is an important step toward the elucidation of protein functions and the understanding of the molecular mechanisms inside the cell. While experimental methods for identifying these interactions remain costly and often noisy, the increasing quantity of solved 3D protein structures suggests that in silico methods to predict interactions between two protein structures will play an increasingly important role in screening candidate interacting pairs. Approaches using the knowledge of the structure are presumably more accurate than those based on sequence only. Approaches based on docking protein structures solve a variant of this problem, but these methods remain very computationally intensive and will not scale in the near future to the detection of interactions at the level of an interactome, involving millions of candidate pairs of proteins.