Drug permeability in 16HBE14o- airway cell layers correlates with absorption from the isolated perfused rat lung

The permeability of the lung is critical in determining the disposition of inhaled drugs and the respiratory epithelium provides the main physical barrier to drug absorption. The 16HBE14o- human bronchial epithelial cell line has been developed recently as a model of the airway epithelium. In this study, the transport of 10 low molecular weight compounds was measured in the 16HBE14o- cell layers, with apical to basolateral (absorptive) apparent permeability coefficients (P(app)) ranging from 0.4 x 10(-6)cms(-1) for Tyr-D-Arg-Phe-Phe-NH(2) to 25.2x10(-6)cms(-1) for metoprolol. Permeability in 16HBE14o- cells was found to correlate with previously reported P(app) in Caco-2 cells and absorption rates in the isolated perfused rat lung (k(a,lung)) and the rat lung in vivo (k(a,in vivo)). Log linear relationships were established between P(app) in 16HBE14o- cells and P(app) in Caco-2 cells (r(2)=0.82), k(a,lung) (r(2)=0.78) and k(a,in vivo) (r(2)=0.68). The findings suggest that permeability in 16HBE14o- cells may be useful to predict the permeability of compounds in the lung, although no advantage of using the organ-specific cell line 16HBE14o- compared to Caco-2 cells was found in this study.

Bilayer graphene formed by passage of current through graphite: evidence for a three-dimensional structure

The passage of an electric current through graphite or few-layer graphene can result in a striking structural transformation, but there is disagreement about the precise nature of this process. Some workers have interpreted the phenomenon in terms of the sublimation and edge reconstruction of essentially flat graphitic structures. An alternative explanation is that the transformation actually involves a change from a flat to a three-dimensional structure. Here we describe detailed studies of carbon produced by the passage of a current through graphite which provide strong evidence that the transformed carbon is indeed three-dimensional. The evidence comes primarily from images obtained in the scanning transmission electron microscope using the technique of high-angle annular dark-field imaging, and from a detailed analysis of electron energy loss spectra. We discuss the possible mechanism of the transformation, and consider potential applications of “three-dimensional bilayer graphene”.

Influence of ground surface characteristics on the mean radiant temperature in urban areas

The effect of variations in land cover on mean radiant surface temperature (Tmrt) is explored through a simple scheme developed within the radiation model SOLWEIG. Outgoing longwave radiation is parameterised using surface temperature observations on a grass and an asphalt surface, whereas outgoing shortwave radiation is modelled through variations in albedo for the different surfaces. The influence of surface materials on Tmrt is small compared to the effects of shadowing. Nevertheless, altering ground surface materials could contribute to a reduction on Tmrt to reduce the radiant load during heat-wave episodes in locations where shadowing is not an option. Evaluation of the new scheme suggests that despite its simplicity it can simulate the outgoing fluxes well, especially during sunny conditions. However, it underestimates at night and in shadowed locations. One grass surface used to develop the parameterisation, with very different characteristics compared to an evaluation grass site, caused Tmrt to be underestimated. The implications of using high resolution (e.g. 15 minutes) temporal forcing data under partly cloudy conditions are demonstrated even for fairly proximal sites.

Uncertainties in tidally adjusted estimates of sea level rise flooding (bathtub model) for the Greater London

Sea-level rise (SLR) from global warming may have severe consequences for coastal cities, particularly when combined with predicted increases in the strength of tidal surges. Predicting the regional impact of SLR flooding is strongly dependent on the modelling approach and accuracy of topographic data. Here, the areas under risk of sea water flooding for London boroughs were quantified based on the projected SLR scenarios reported in Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) and UK climatic projections 2009 (UKCP09) using a tidally-adjusted bathtub modelling approach. Medium- to very high-resolution digital elevation models (DEMs) are used to evaluate inundation extents as well as uncertainties. Depending on the SLR scenario and DEMs used, it is estimated that 3%–8% of the area of Greater London could be inundated by 2100. The boroughs with the largest areas at risk of flooding are Newham, Southwark, and Greenwich. The differences in inundation areas estimated from a digital terrain model and a digital surface model are much greater than the root mean square error differences observed between the two data types, which may be attributed to processing levels. Flood models from SRTM data underestimate the inundation extent, so their results may not be reliable for constructing flood risk maps. This analysis provides a broad-scale estimate of the potential consequences of SLR and uncertainties in the DEM-based bathtub type flood inundation modelling for London boroughs.

Willingness-to-pay for a probabilistic flood forecast: a risk-based decision-making game

Probabilistic hydro-meteorological forecasts have over the last decades been used more frequently to communicate forecastuncertainty. This uncertainty is twofold, as it constitutes both an added value and a challenge for the forecaster and the user of the forecasts. Many authors have demonstrated the added (economic) value of probabilistic over deterministic forecasts across the water sector (e.g. flood protection, hydroelectric power management and navigation). However, the richness of the information is also a source of challenges for operational uses, due partially to the difficulty to transform the probability of occurrence of an event into a binary decision. This paper presents the results of a risk-based decision-making game on the topic of flood protection mitigation, called “How much are you prepared to pay for a forecast?”. The game was played at several workshops in 2015, which were attended by operational forecasters and academics working in the field of hydrometeorology. The aim of this game was to better understand the role of probabilistic forecasts in decision-making processes and their perceived value by decision-makers. Based on the participants’ willingness-to-pay for a forecast, the results of the game show that the value (or the usefulness) of a forecast depends on several factors, including the way users perceive the quality of their forecasts and link it to the perception of their own performances as decision-makers.