Toxicity of environmental and polystyrene plastic particles on the bivalve Corbicula fluminea: focus on the molecular responses.

Among aquatic organisms, filter feeders are particularly exposed to the ingestion of microplastics (MPs) and nanoplastics (NPs). The present study investigates the effect of environmental microplastics (ENV MPs) and nanoplastics (ENV NPs) generated from macro-sized plastic debris collected in the Garonne River (France), and polystyrene NPs (PS NPs) on the freshwater bivalve Corbicula fluminea. Organisms were exposed to plastic particles at three concentrations: 0.

Toxicity assessment of environmental MPs and NPs and polystyrene NPs on the bivalve Corbicula fluminea using a multi-marker approach.

Small plastic particles, microplastics (MPs) and nanoplastics (NPs) represent a major threat in aquatic environments. Freshwater organisms are exposed to MPs and NPs, particularly in industrial and urban areas. The present study aimed to compare the toxicity between polystyrene NPs (PS NPs) and environmental microplastics (ENV MPs) and nanoplastics (ENV NPs) generated from macro-sized debris collected in the Garonne River on the freshwater bivalve C.

Continuum from microplastics to nanoplastics: effects of size and source on the estuarine bivalve Scrobicularia plana.

Plastic has been largely detected in estuarine environments and represents major concern towards aquatic living organisms. The present study evaluates the impact of microplastics (MPs) and nanoplastics (NPs) under realistic exposure conditions. Scrobicularia plana individuals were exposed to low concentrations (0.

Spatialized epidemiological forecasting applied to Covid-19 pandemic at departmental scale in France.

In this paper, we present a spatialized extension of a SIR model that accounts for undetected infections and recoveries as well as the load on hospital services. The spatialized compartmental model we introduce is governed by a set of partial differential equations (PDEs) defined on a spatial domain with complex boundary. We propose to solve the set of PDEs defining our model by using a meshless numerical method based on a finite difference scheme in which the spatial operators are approximated by using radial basis functions.

Transport effect of COVID-19 pandemic in France.

An extension of the classical pandemic SIRD model is considered for the regional spread of COVID-19 in France under lockdown strategies. This compartment model divides the infected and the recovered individuals into undetected and detected compartments respectively. By fitting the extended model to the real detected data during the lockdown, an optimization algorithm is used to derive the optimal parameters, the initial condition and the epidemics start date of regions in France.

Application of a wavelet-Galerkin method to the forward problem resolution in fluorescence diffuse optical tomography.

Fluorescence diffuse optical tomography is a powerful tool for the investigation of molecular events in studies for new therapeutic developments. Here, the emphasis is put on the mathematical problem of tomography, which can be formulated in terms of an estimation of physical parameters appearing as a set of Partial Differential Equations (PDEs). The standard polynomial Finite Element Method (FEM) is a method of choice to solve the diffusion equation because it has no restriction in terms of neither the geometry nor the homogeneity of the system, but it is time consuming.

Model reduction using wavelet multiresolution technique applied to fluorescence diffuse optical tomography.

Fluorescence diffuse optical tomography is a powerful tool for the investigation of molecular events in studies for new therapeutic developments. Here, the stress is put on the mathematical problem of tomography, which can be formulated in terms of an estimation of physical parameters appearing as a set of partial differential equations and solved by the finite element method. This method is well known to be time consuming, and our principal objective is to reduce the model in order to speed up computation.

Model reduction by multiresolution method applied to fluorescence diffuse optical tomography.

This paper is devoted to the Fluorescence Diffuse Optical Tomography. This inverse problem relies on an iterative algorithm based on solutions of partial differential equations. The goal of the paper is to present a multiresolution technique applied to these equations, with the objective of computation complexity reduction.