Quantitative comparison of two cardiac electrophysiology models using personalisation to optical and MR data

International audienceIn order to translate the important modelling work into clinical tools, the selection of the best model for a given application is crucial. In this paper, we quantitatively compare personalisation of two different cardiac electrophysiology models on the same dataset, in order to help such a selection. One is a phenomenological model, the AlievPanfilov model (1996), and the other one is a simplified ionic model, the Mitchell-Schaeffer model (2003). In the preliminary steps of model personalisation, we optimise the forward problem with the determination of an optimum time integration scheme for each model, which could result in stable and accurate simulations without the use of unnecessary expensive high temporal and spatial resolutions. Next, we personalise the two models by optimising their respective parameters, to match the depolarisation and repolarisation maps obtained ex-vivo from optical imaging of large porcine healthy heart. Last, we compare the personalisation results of the two different model

Quasiparticle transport in the vortex state of YBa_2Cu_3O_6.9

The effect of vortices on quasiparticle transport in cuprate superconductors was investigated by measuring the low temperature thermal conductivity of YBa_2Cu_3O_6.9 in magnetic fields up to 8 T. The residual linear term (as T \to 0) is found to increase with field, directly reflecting the occupation of extended quasiparticle states. A study for different Zn impurity concentrations reveals a good agreement with recent calculations for a d-wave superconductor, thereby shedding light on the nature of scattering by both impurities and vortices. It also provides a quantitative measure of the gap near the nodes.Comment: 4 pages, 2 included eps figures, significant new analysis wrt other experiments, to appear in Phys Rev Lett 29 March 199

MIL-91(Ti), a small pore metal-organic framework which fulfils several criteria : an upscaled green synthesis, excellent water stability, high CO2 selectivity and fast CO2 transport

The research leading to these results has received funding from the European Community Seventh Framework Program (FP7/2007-2013) [grant agreement number 608490] (project M4CO2) and from the ANR ‘CHESDENS’ (ANR-13-SEED-0001-01).A multidisciplinary approach combining advanced experimental and modelling tools was undertaken to characterize the promises of a small-pore type Ti-based metal-organic framework, MIL-91(Ti) for CO2 capture. This material was prepared using two synthesis strategies, i.e. under hydrothermal conditions and under reflux, and its single component adsorption behaviour with respect to CO2, CH4 and N2 was first revealed by gravimetry measurements. This hydrophilic and highly water stable MOF is characterized by a relatively high CO2 adsorption enthalpy. Molecular simulations combined with in situ powder X-ray diffraction evidenced that this is due to the combined interaction of this probe with N-H and P-O groups in the phosphonate linker. High CO2 selectivities in the presence of either N2 or CH4 were also predicted and confirmed by co-adsorption measurements. The possibility to prepare this sample under reflux represents an environmentally friendly route which can easily be upscaled. This green synthesis route, excellent water stability, high selectivities and relatively fast transport kinetics of CO2 are significant points rendering this sample of utmost interest for CO2 capture.PostprintPostprintPeer reviewe

Open Science principles for accelerating trait-based science across the Tree of Life.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges

Abiotic formation of methyl iodide on synthetic birnessite: A mechanistic study

Methyl iodide is a well-known volatile halogenated organic compound that contributes to the iodine content in the troposphere, potentially resulting in damage to the ozone layer. Most methyl iodide sources derive from biological activity in oceans and soils with very few abiotic mechanisms proposed in the literature. In this study we report that synthetic manganese oxide (birnessite δ-MnO2) can catalyze the formation of methyl iodide in the presence of natural organic matter (NOM) and iodide. Methyl iodide formation was only observed at acidic pH (4–5) where iodide is oxidized to iodine and NOM is adsorbed on δ-MnO2. The effect of δ-MnO2, iodide and NOM concentrations, nature of NOM and ionic strength was investigated. High concentrations of methyl iodide were formed in experiments conducted with the model compound pyruvate. The Lewis acid property of δ-MnO2 leads to a polarization of the iodine molecule, and catalyzes the reaction with natural organic matter. As manganese oxides are strong oxidants and are ubiquitous in the environment, this mechanism could significantly contribute to the global atmospheric input of iodine

Genetic Structure of Plasmodium falciparum and Elimination of Malaria, Comoros Archipelago

Elimination interventions should be implemented simultaneously throughout the entire archipelago

Recent advances toward the sustainable management of invasive Xylosandrus ambrosia beetles

We provide an overview of both traditional and innovative control tools for management of three Xylosandrus ambrosia beetles (Coleoptera: Curculionidae: Scolytinae), invasive species with a history of damage in forests, nurseries, orchards and urban areas. Xylosandrus compactus, X. crassiusculus and X. germanus are native to Asia, and currently established in several countries around the globe. Adult females bore galleries into the plant xylem inoculating mutualistic ambrosia fungi that serve as food source for the developing progeny. Tunneling activity results in chewed wood extrusion from entry holes, sap outflow, foliage wilting followed by canopy dieback, and branch and trunk necrosis. Maintaining plant health by reducing physiological stress is the first recommendation for long-term control. Baited traps, ethanol-treated bolts, trap logs and trap trees of selected species can be used to monitor Xylosandrus species. Conventional pest control methods are mostly ineffective against Xylosandrus beetles because of the pests’ broad host range and rapid spread. Due to challenges with conventional control, more innovative control approaches are being tested, such as the optimization of the push–pull strategy based on specific attractant and repellent combinations, or the use of insecticide-treated netting. Biological control based on the release of entomopathogenic and mycoparasitic fungi, as well as the use of antagonistic bacteria, has yielded promising results. However, these technologies still require validation in real field conditions. Overall, we suggest that management efforts should primarily focus on reducing plant stress and potentially be combined with a multi-faceted approach for controlling Xylosandrus damage

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Construction of 3D MR image-based computer models of pathologic hearts, augmented with histology and optical fluorescence imaging to characterize action potential propagation

International audienceCardiac computer models can help us understand and predict the propagation of excitation waves (i.e., action potential, AP) in healthy and pathologic hearts. Our broad aim is to develop accurate 3D MR image-based computer models of electrophysiology in large hearts (translatable to clinical applications) and to validate them experimentally. The specific goals of this paper were to match models with maps of the propagation of optical AP on the epicardial surface using large porcine hearts with scars, estimating several parameters relevant to macroscopic reaction-diffusion electrophysiological models. We used voltage-sensitive dyes to image AP in large porcine hearts with scars (3 specimens had chronic myocardial infarct, and 3 had radiofrequency RF acute scars). We first analyzed the main AP waves' characteristics: duration (APD) and propagation under controlled pacing locations and frequencies as recorded from 2D optical images. We further built 3D MR image-based computer models that have information derived from the optical measures, as well as morphologic MRI data (i.e., myocardial anatomy, fiber directions and scar definition). The scar morphology from MR images was validated against corresponding whole-mount histology. We also compared the measured 3D isochronal maps of depolarization to simulated isochrones (the latter replicating precisely the experimental conditions), performing model customization and 3D volumetric adjustments of the local conductivity. Our results demonstrated that mean APD in the border zone (BZ) of the infarct scars was reduced by ~13% (compared to ~318 ms measured in normal zone, NZ), but APD did not change significantly in the thin BZ of the ablation scars. A generic value for velocity ratio (1:2.7) in healthy myocardial tissue was derived from measured values of transverse and longitudinal conduction velocities relative to fibers direction (22cm/s and 60cm/s, respectively). The model customization and 3D volumetric adjustment reduced the differences between measurements and simulations; for example, from one pacing location, the adjustment reduced the absolute error in local depolarization times by a factor of 5 (i.e., from 58 ms to 11 ms) in the infarcted heart, and by a factor of 6 (i.e., from 60 ms to 9 ms) in the heart with the RF scar. Moreover, the sensitivity of adjusted conductivity maps to different pacing locations was tested, and the errors in activation times were found to be of approximately 10-12 ms independent of pacing location used to adjust model parameters, suggesting that any location can be used for model predictions