Development of q-PCR approaches to assess water quality: effects of cadmium on gene expression of the diatom Eolimna minima

This study was undertaken to develop molecular tools to assess water quality using diatoms as the biological model. Molecular approaches were designed following the development of a rapid and easy RNA extraction method suited to diatoms and the sequencing of genes involved in mitochondrial and photosystem metabolism. Secondly the impact of cadmium was evaluated at the genetic level by q-PCR on 9 genes of interest after exposure of Eolimna minima diatom populations cultured in suspension under controlled laboratory conditions. Their growth kinetics and Cd bioaccumulation were followed.Population growth rates revealed the high impact of Cd at 100 μg/L with total inhibition of growth. These results are linked to the high bioaccumulation values calculated after 14 days of exposure, 57.0 ± 6.3 μg Cd/g dw and 734.1 ± 70 μg Cd/g dw for exposures of 10 and 100 μg Cd/L respectively.Genetic responses revealed the impact of Cd on the mitochondrial metabolism and the chloroplast photosystem of E. minima exposed to 10 and 100 μg Cd/L with induction of cox1, 12S, d1 and psaA after 7 days of exposure for the concentration of 100 μg Cd/L and of nad5, d1 and psaA after 14 days of exposure for both conditions.This is the first reported use of q-PCR for the assessment of toxic pollution on benthic river diatoms. The results obtained presage interesting perspectives, but the techniques developed need to be optimized before the design of new water quality diagnosis tools for use on natural biofilms.     

Flexible querying of Web data to simulate bacterial growth in food

A preliminary step in microbial risk assessment in foods is the gathering of experimental data. In the framework of the Sym’Previus project, we have designed a complete data integration system opened on the Web which allows a local database to be complemented by data extracted from the Web and annotated using a domain ontology. We focus on the Web data tables as they contain, in general, a synthesis of data published in the documents. We propose in this paper a flexible querying system using the domain ontology to scan simultaneously local and Web data, this in order to feed the predictive modeling tools available on the Sym’Previus platform. Special attention is paid on the way fuzzy annotations associated with Web data are taken into account in the querying process, which is an important and original contribution of the proposed system.     

In Situ Generation of n-Type Dopants by Thermal Decarboxylation

Molecular doping is a powerful and increasingly popular approach toward enhancing electronic properties of organic semiconductors (OSCs) past their intrinsic limits. The development of n-type dopants has been hampered, however, by their poor stability and high air-reactivity, a consequence of their generally electron rich nature. Here, the use of air-stable carboxylated dopant precursors is reported to overcome this challenge. Active dopants are readily generated in solution by thermal decarboxylation and applied in n-type organic field-effect transistors (OFETs). Both 1,3-dimethylimidazolium-2-carboxylate (CO₂-DMI) and novel dopant 1,3-dimethylbenzimidazolium-2-carboxylate (CO₂-DMBI) are applied to n-type OFETs employing well-known organic semiconductors (OSCs) P(NDI2OD-T2), PCBM, and O-IDTBR. Successful improvement of performance in all devices demonstrates the versatility of the dopants across a variety of OSCs. Experimental and computational studies indicate that electron transfer from the dopant to the host OSC is preceded by decarboxylation of the precursor, followed by dimerization to form the active dopant species. Transistor studies highlight CO₂-DMBI as the most effective dopant, improving electron mobility by up to one order of magnitude, while CO₂-DMI holds the advantage of commercial availability.     

Experimental methods in chemical engineering: Computational fluid dynamics/finite volume method—CFD/FVM

Computational fluid dynamics (CFD) applies numerical methods to solve transport phenomena problems. These include, for example, problems related to fluid flow comprising the Navier–Stokes transport equations for either compressible or incompressible fluids, together with turbulence models and continuity equations for single and multi-component (reacting and inert) systems. The design space is first segmented into discrete volume elements (meshing). The finite volume method, the subject of this article, discretizes the equations in time and space to produce a set of non-linear algebraic expressions that are assigned to each volume element—cell. The system of equations is solved iteratively with algorithms like the semi-implicit method for pressure-linked equations (SIMPLE) and the pressure implicit splitting of operators (PISO). CFD is especially useful for testing multiple design elements because it is often faster and cheaper than experiments. The downside is that this numerical method is based on models that require validation to check their accuracy. According to a bibliometric analysis, the broad research domains in chemical engineering include: (1) dynamics and CFD-DEM, (2) fluid flow, heat transfer, and turbulence, (3) mass transfer and combustion, (4) ventilation and the environment, and (5) design and optimization. Here, we review the basic theoretical concepts of CFD and illustrate how to set up a problem in the open-source software OpenFOAM to isomerize n-butane to i-butane in a notched reactor under turbulent conditions. We simulated the problem with 1000, 4000, and 16 000 cells. According to the Richardson extrapolation, the simulation underestimates the adiabatic temperature rise by 7% with 16 000 cells.