A stable fish reporter cell line to study estrogen receptor transactivation by environmental (xeno)estrogens.

International audienceCross-species differences between human and fish estrogen receptor (ER) binding by environmental chemicals have been reported. To study ER transactivation in a fish cellular context, we stably co-transfected the PLHC-1 fish hepatoma cell line with a rainbow trout estrogen receptor (rtER) and the luciferase reporter gene driven by an estrogen response element (ERE). This new cell model, called PELN-rtER (for PLHC-1-ERE-Luciferase-Neomycin), responded to 17beta-estradiol (E2) in a both concentration- and temperature-dependent manner, as well as to environmental ER ligands from different chemical classes: natural and synthetic estrogens, zearalenone metabolites, genistein, alkyphenoles and benzophenone derivatives. The comparison with other in vitro models, i.e. human reporter cell lines (HELN-rtER, MELN) and vitellogenin induction in primary cultures of rainbow trout hepatocytes, showed an overall higher sensitivity of the human cells for a majority of ligands, except for benzophenone derivatives which were active at similar or lower concentrations in fish cells, suggesting species-specificity for these substances. Correlation analyses suggest that the fish cell line is closer to the trout hepatocyte than to the human cell context, and could serve as a relevant mechanistic tool to study ER activation in fish hepatic cellular context

Palladium-Catalyzed Synthesis of α-Carbonyl-α′-(hetero)aryl Sulfoxonium Ylides:Scope and Insight into the Mechanism

Despite recent advances, a general method for the synthesis of α-carbonyl-α′-(hetero)aryl sulfoxonium ylides is needed to benefit more greatly from the potential safety advantages offered by these compounds over the parent diazo compounds. Herein, we report the palladium-catalyzed cross-coupling of aryl bromides and triflates with α-carbonyl sulfoxonium ylides. We also report the use of this method for the modification of an active pharmaceutical ingredient and for the synthesis of a key precursor of antagonists of the neurokinin-1 receptor. In addition, the mechanism of the reaction was inferred from several observations. Thus, the oxidative addition complex [(XPhos)PhPdBr] and its dimer were observed by 31P{1H} NMR, and these complexes were shown to be catalytically and kinetically competent. Moreover, a complex resulting from the transmetalation of [(XPhos)ArPdBr] (Ar = p-CF3–C6H4) with a model sulfoxonium ylide was observed by mass spectrometry. Finally, the partial rate law suggests that the transmetalation and the subsequent deprotonation are rate-determining in the catalytic cycle

Social acceptance of renewable energy: Some examples from Europe and Developing Africa

Current energy systems are in most instances not fully working sustainably. The provision and use of energy only consider limited resources, risk potential or financial constraints on a limited scale. Furthermore, the knowledge and benefits are only available for a minor group of the population or are outright neglected. The availability of different resources for energy purposes determines economic development, as well as the status of the society and the environment. The access to energy grids has an impact on socio-economic living standards of communities. This not fully developed system is causing climate change with all its related outcomes. This investigation takes into consideration different views on renewable energy systems — such as international discussions about biomass use for energy production, “fuel versus food”, biogas use — and attempts to compare major prospects of social acceptance of renewable energy in Europe and Africa. Can all obstacles to the use of renewable energy be so profound that the overall strategy of reducing anthropogenic causes of climate change be seriously affected

Coastal sea level monitoring in the Mediterranean and Black seas

Employed for over a century, the traditional way of monitoring sea level variability by tide gauges – in combination with modern observational techniques like satellite altimetry – is an inevitable ingredient in sea level studies over the climate scales and in coastal seas. The development of the instrumentation, remote data acquisition, processing, and archiving in the last decades has allowed the extension of the applications to a variety of users and coastal hazard managers. The Mediterranean and Black seas are examples of such a transition – while having a long tradition of sea level observations with several records spanning over a century, the number of modern tide gauge stations is growing rapidly, with data available both in real time and as a research product at different time resolutions. As no comprehensive survey of the tide gauge networks has been carried out recently in these basins, the aim of this paper is to map the existing coastal sea level monitoring infrastructures and the respective data availability. The survey encompasses a description of major monitoring networks in the Mediterranean and Black seas and their characteristics, including the type of sea level sensors, measuring resolutions, data availability, and existence of ancillary measurements, altogether collecting information about 240 presently operational tide gauge stations. The availability of the Mediterranean and Black seas sea level data in the global and European sea level repositories has been also screened and classified following their sampling interval and level of quality check, pointing to the necessity of harmonization of the data available with different metadata and series in different repositories. Finally, an assessment of the networks' capabilities for their use in different sea level applications has been done, with recommendations that might mitigate the bottlenecks and ensure further development of the networks in a coordinated way, a critical need in the era of human-induced climate changes and sea level rise.En prens

An Introduction to EEG Source Analysis with an illustration of a study on Error-Related Potentials

International audienceOver the last twenty years blind source separation (BSS) has become a fundamental signal processing tool in the study of human electroencephalography (EEG), other biological data, as well as in many other signal processing domains such as speech, images, geophysics and wireless communication (Comon and Jutten, 2010). Without relying on head modeling BSS aims at estimating both the waveform and the scalp spatial pattern of the intracranial dipolar current responsible of the observed EEG, increasing the sensitivity and specificity of the signal received from the electrodes on the scalp. This chapter begins with a short review of brain volume conduction theory, demonstrating that BSS modeling is grounded on current physiological knowledge. We then illustrate a general BSS scheme requiring the estimation of second-order statistics (SOS) only. A simple and efficient implementation based on the approximate joint diagonalization of covariance matrices (AJDC) is described. The method operates in the same way in the time or frequency domain (or both at the same time) and is capable of modeling explicitly physiological and experimental source of variations with remarkable flexibility. Finally, we provide a specific example illustrating the analysis of a new experimental study on error-related potentials

An improved time–frequency noise reduction method using a psycho-acoustic Mel model

This paper addresses the problem of noise reduction in non-stationary signals. The paper first describes a human physiology based time?frequency (TF) representation (HPTF) using Mel filterbanks. It is then used to improve a noise reduction algorithm that does not require any a priori information about the signal of interest and the noise. This algorithm is efficiently implemented using an original wavelet shrinkage method. The overall method results in an original TF denoising procedure that yields a denoised HPTF (DHPTF). From this representation, one can reconstruct a denoised time-domain signal and therefore define a new improved noise reduction algorithm, whose performance is evaluated and compared with other state-of-the-art methods. The performance assessment uses several criteria: (1) signal-to-noise-ratio (SNR), (2) segmental SNR (SSNR) and (3) mean square error (MSE). The results indicate an improvement of up to 4.72 dB with respect to (w.r.t.) SNR, 2.79 dB w.r.t. SSNR and 4.72 dB w.r.t. MSE for a speech database signals corrupted with four different noises. In addition, other applications such as EEG signal enhancement show promising results. ? 2018 Elsevier Inc.Part of this work was supported by QNRF grant NPRP 6-885-2-364 (Lead Principal Investigator: Prof Boashash).Scopu