Fant 9998 publikasjoner. Viser side 385 av 400:
2018
2019
2024
2006
2024
1999
Use of three-dimensional (3D) tissue equivalents in toxicology has been increasing over the last decade as novel preclinical test systems and as alternatives to animal testing. In the area of genetic toxicology, progress has been made with establishing robust protocols for skin, airway (lung) and liver tissue equivalents. In light of these advancements, a “Use of 3D Tissues in Genotoxicity Testing” working group (WG) met at the 7th IWGT meeting in Tokyo in November 2017 to discuss progress with these models and how they may fit into a genotoxicity testing strategy. The workshop demonstrated that skin models have reached an advanced state of validation following over 10 years of development, while liver and airway model-based genotoxicity assays show promise but are at an early stage of development. Further effort in liver and airway model-based assays is needed to address the lack of coverage of the three main endpoints of genotoxicity (mutagenicity, clastogenicity and aneugenicity), and information on metabolic competence. The IWGT WG believes that the 3D skin comet and micronucleus assays are now sufficiently validated to undergo an independent peer review of the validation study, followed by development of individual OECD Test Guidelines.
2020
2016
Use of satellite data for atmospheric pollution and greenhouse gas monitoring. A contribution to ACCENT-TROPOSAT-2, task group 3. ACCENT reports, 1.2007
2007
2009
<i>Background</i> - Concerns have been raised that extensive use of personal care products that contain endocrine disrupting compounds increase the risk of hormone sensitive cancers.<p> <p><i>Objective</i> - To assess the effect of skincare product use on the risk of pre- and postmenopausal breast cancer, estrogen receptor positive (ER+) and negative (ER-) breast cancer and cancer of the endometrium.<p> <p><i>Methods</i> - We used data from 106,978 participants in the population-based Norwegian Women and Cancer cohort. Participants were categorized into non-, light, moderate, frequent and heavy users of skincare products based on self-reported use of hand and facial cream and body lotion. Cancer incidence information from the Cancer Registry of Norway was linked to individual data through the unique identity number of Norwegian citizens. Multivariable Cox proportional hazard regression was used to assess the effect of skincare product use on the risk of cancer of the breast and endometrium. We used multiple imputation by chained equations to evaluate the effect of missing data on observed associations.<p> <p><i>Results</i> - We found no associations between use of skincare products and incidence of premenopausal breast cancer (frequent/heavy versus non−/light use: hazard ratio [HR] =1.10, 95% confidence interval [CI]: 0.92–1.32), postmenopausal breast cancer (heavy versus light use: HR = 0.87, 95% CI: 0.65–1.18, frequent versus light use: HR = 0.97, 95% CI: 0.88, 1.07) or endometrial cancer (frequent/heavy versus non−/light use: HR = 0.97, 95% CI: 0.79–1.20). Use of skincare products did not increase the risk of ER+ or ER- breast cancer and there was no difference in effect across ER status (0.58 ≤ <sub>pheterogeneity</sub> ≤ 0.99). The magnitude and direction of the effect estimates based on complete case analyses and multiple imputation were similar.<p> <p><i>Conclusion</i> Heavy use of skincare products, i.e. creaming the body up to two times per day during mid-life, did not increase the risk of cancer of the breast or endometrium.
2019
2008
2023
User's guide for the Gaussian type dispersion models CONCX and CONDEP. NILU TR
Rapporten inneholder en brukerbeskrivelse av de Gaussiske programmene CONCX og CONDEP, som beregner henholdsvis korttids- og langtidsverdier av konsentrasjoner for utslipp fra en eller flere skorsteiner. Rapporten inneholder en teoretisk del med bakgrunn for beregningene i tillegg til beregningseksempler.
1987
Using a citizen science approach to assess nanoplastics pollution in remote high-altitude glaciers
Nanoplastics are suspected to pollute every environment on Earth, including very remote areas reached via atmospheric transport. We approached the challenge of measuring environmental nanoplastics by combining high-sensitivity TD-PTR-MS (thermal desorption-proton transfer reaction-mass spectrometry) with trained mountaineers sampling high-altitude glaciers (“citizen science”). Particles < 1 μm were analysed for common polymers (polyethylene, polyethylene terephthalate, polypropylene, polyvinyl chloride, polystyrene and tire wear particles), revealing nanoplastic concentrations ranging 2–80 ng mL− 1 at five of 14 sites. The dominant polymer types found in this study were tire wear, polystyrene and polyethylene particles (41%, 28% and 12%, respectively). Lagrangian dispersion modelling was used to reconstruct possible sources of micro- and nanoplastic emissions for those observations, which appear to lie largely to the west of the Alps. France, Spain and Switzerland have the highest contributions to the modelled emissions. The citizen science approach was found to be feasible providing strict quality control measures are in place, and is an effective way to be able to collect data from remote and inaccessible regions across the world.
2025
Acoustic waves below the frequency limit of human hearing - infrasound - can travel for thousands of kilometres in the atmosphere. The global propagation signature of infrasound is highly sensitive to the wind structure of the stratosphere.
This work exploits processed continuous data from three high-latitude infrasound stations to characterize an aspect of the stratospheric polar vortex. Concretely, a mapping is developed which takes the infrasound data from these three stations as input and outputs an estimate of the polar cap zonal mean wind averaged over 60-90 degrees in latitude at the 1 hPa pressure level. This stratospheric diagnostic information is relevant to, for example, sudden stratospheric warming assessment and sub-seasonal prediction.
The considered acoustic data is within a low-frequency regime globally dominated by so-called microbarom infrasound, which is continuously radiated into the atmosphere due to nonlinear interaction between counter-propagating ocean surface waves.
We trained a stochastics-based machine learning model (delay-SDE-net) to map between a time series of five years (2014-2018) of processed infrasound data and the ERA5 (reanalysis-based) daily average polar cap wind at 1 hPa for the same period. The ERA5 data was hence treated as ground-truth. In the prediction, the delay-SDE-net utilizes time-lagged inputs and their dependencies, as well as the day of the year to account for seasonal differences. In the validation phase, the input was the 2019 and 2020 infrasound time series, and the model inference results in an estimate of the daily average polar cap wind time-series. This result was then compared to the ERA5 representation of the stratospheric diagnostic time-series for the same period.
The applied machine learning model is based on stochastics and allows for an interpretable approach to estimate the aleatoric and epistemic prediction uncertainties. It is found that the mapping, which is only informed of the trained model, the day of year, and the infrasound data from three stations, generates a 1 hPa polar cap average wind estimate with a prediction error standard deviation of around 10 m/s compared to ERA5.
Focus should be put on the winter months because this is when the coupling between the stratosphere and the troposphere can mostly influence the surface conditions and provide additional prediction skill, in particular during strong and weak stratospheric polar vortex regimes. The infrasound data is available in real-time, and we discuss how the developed approach can be extended to provide near real-time stratospheric polar vortex diagnostics.
2023
2018