237 research outputs found

    Influence on the cellular organization in central nervous system micromass cultures

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    The effects of lead on cellular neuronal development and organization have been studied. Rat embryo midbrain micromass cultures were exposed to lead acetate (0.1—5.0 ag/ml) for five days. Differentiation was indicated by the formation of neuronal foci in the cultures. Effects on cell growth and survival were estimated using a neutral red staining method. Lead was found to inhibit foci formation at concentrations (0.25 and 0.5 pg/ml) which did not affect cell survival. This selective effect on neuronal development was not found for three other heavy metal compounds: trimethyltin chloride, cadmium chloride and mercury chloride. In chicken embryo midbrain micromass cultures, foei formation was inhibited by even lower concentrations of lead (0.05-0.5 ug/ml), whereas neuronal cell aggregation in cell line micromass eocultures was unaffected by lead in concentrations up to 5.0 pg/ml. It is concluded that lead causes a disturbance in the neuronal developmentin embryonic central nervous system micromass cultures by a specific and selective effect on a property only expressed in embryonic cells

    Toxicity of mercury to hybridoma TA7 cells

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    Environmental mercury and mercury compound contamination has increased dramatically since the industrial revolution. This paper describes the toxic effects of mercury on a culture of hybridoma TA7 cells, which produce antibodies against the A-subunit of viskumin. Cells were cultivated on 96- well flat-bottomed plates with RPMI-1640 medium supplemented with 10% fetal calf serum at 37°C in 5% CO2/95% air. The cells were exposed to 0.1nM/l- 10ΌM/l Hg2(NO3)2·2H2O (mercury nitrate) during the exponential growth phase. Toxicity was assessed by using the colorimetric MTT (tetrazolium) assay after exposure for 48 hours. Cell growth and cell survival were evaluated by using percentage indices of cellular content in exposed cells when compared to non-exposed control cells. The concentrations of the no- effect level, the lowest observed effect level and the the highest toxic effect level were registered. The toxic effects of the mercury compound on the hybridoma cells occurred between 0.1ΌM/l and 10ΌM/l.Peer reviewe

    Report from the EPAA workshop: In vitro ADME in safety testing used by EPAA industry sectors

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    AbstractThere are now numerous in vitro and in silico ADME alternatives to in vivo assays but how do different industries incorporate them into their decision tree approaches for risk assessment, bearing in mind that the chemicals tested are intended for widely varying purposes? The extent of the use of animal tests is mainly driven by regulations or by the lack of a suitable in vitro model. Therefore, what considerations are needed for alternative models and how can they be improved so that they can be used as part of the risk assessment process? To address these issues, the European Partnership for Alternative Approaches to Animal Testing (EPAA) working group on prioritisation, promotion and implementation of the 3Rs research held a workshop in November, 2008 in Duesseldorf, Germany. Participants included different industry sectors such as pharmaceuticals, cosmetics, industrial- and agro-chemicals. This report describes the outcome of the discussions and recommendations (a) to reduce the number of animals used for determining the ADME properties of chemicals and (b) for considerations and actions regarding in vitro and in silico assays. These included: standardisation and promotion of in vitro assays so that they may become accepted by regulators; increased availability of industry in vivo kinetic data for a central database to increase the power of in silico predictions; expansion of the applicability domains of in vitro and in silico tools (which are not necessarily more applicable or even exclusive to one particular sector) and continued collaborations between regulators, academia and industry. A recommended immediate course of action was to establish an expert panel of users, developers and regulators to define the testing scope of models for different chemical classes. It was agreed by all participants that improvement and harmonization of alternative approaches is needed for all sectors and this will most effectively be achieved by stakeholders from different sectors sharing data

    Ljudgenerering frÄn radar signaler, för mÄlklassificering

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    Classification in radar application are often of great interest, since one does not only want to know where a target is, but also what type of target it is. This thesis focus on transforming the radar return from a target into a audio signal. So that the classification can be done by human perception, in this case human hearing. The aim of these classification methods is to be able to distinguish between two types of targets of roughly the same size, namely birds and smaller Unmanned Aerial Vehicles (UAV). It is possible with the radar to measure the targets velocity by using the Doppler effect. To be able to distinguish in which direction the target is moving are a so called I/Q representation of the radar return used, which is a complex representation of the signal. Using signal processing techniques, we extract radar signals generated from the target. By spectral transforms it is possible to generate real valued signals from the extracted target signals. It is required to extend these signals to be able to use them as audio signals, this is done with an extrapolation technique based on Autoregressive (AR) processes. The extrapolated signals are the signals used as the audio output, it is possible to perform the audio classification in most of the cases. This project is done in collaboration with Sebastian Edman [7], where different perspectives of radar classification has been investigated. As mentioned this thesis focus on transforming the radar return into an audio signal. While Edman in his thesis [7] making use of a machine learning approach to classify the targets from the generated audio signal.  Klassificering Àr ofta av stort intresse inom radarapplikation, eftersom man inte bara vill veta var ett mÄl befinner sig men ocksÄ vad för typ av mÄl det Àr. Denna uppsats fokuserar pÄ att omvandla radarekot frÄn ett mÄl till en ljudsignal. SÄ att klassificeringen kan ske med mÀnskliga sinnen, i detta fall hörseln. Syftet med dessa klassificeringsmetoder Àr att kunna klassificera tvÄ typer av mÄl med ungefÀr samma storlek, nÀmligen fÄglar och mindre obemannade flygfordon (UAV). Det Àr möjligt att med radarn mÀta mÄlets hastighet med hjÀlp av Doppler-effekten. För att kunna avgöra i vilken riktning mÄlet rör sig anvÀnds en I/Q-representation, som Àr en komplex representation av radar signalen. Med signalbehandling Àr det möjligt att extrahera radar signaler som mÄlet generar. Genom att anvÀnda spektrala transformationer Àr det möjligt att generera reellvÀrda signaler frÄn de extraherade mÄlsignalerna. Det Àr nödvÀndigt att förlÀnga dessa signaler för att kunna anvÀnda dem som ljudsignaler, detta görs med en extrapoleringsteknik baserad pÄ Autoregressiva (AR) -processer. De ljudsignaler som anvÀnds Àr dessa extrapolerade signalerna, det Àr i det flesta fall möjligt att utifrÄn ljudet genomföra klassificeringen. Detta projekt Àr utfört i samarbete med Sebastian Edman [7], dÀr olika inriktningar av radarklassificering har undersökts. Som nÀmnts ovan fokuserar denna uppsats pÄ att omvandl
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