Cannabidiol displays antiepileptiform and antiseizure properties in vitro and in vivo

Plant-derived cannabinoids (phytocannabinoids) are compounds with emerging therapeutic potential. Early studies suggested that cannabidiol (CBD) has anticonvulsant properties in animal models and reduced seizure frequency in limited human trials. Here, we examine the anti-epileptiform and anti-seizure potential of CBD using in vitro electrophysiology and an in vivo animal seizure model, respectively. CBD (0.01-100 muM) effects were assessed in vitro using the Mg(2+)-free and 4-aminopyridine (4-AP) models of status epilepticus-like epileptiform activity in hippocampal brain slices via multi-electrode array (MEA) recordings. In the Mg(2+)-free model, CBD decreased epileptiform local field potential (LFP) burst amplitude (in CA1 and dentate gyrus (DG) regions) and burst duration (in all regions) and increased burst frequency (in all regions). In the 4-AP model, CBD decreased LFP burst amplitude (in CA1, only at 100 muM CBD), burst duration (in CA3 and DG), and burst frequency (in all regions). CBD (1, 10 and 100 mg/kg) effects were also examined in vivo using the pentylenetetrazole (PTZ) model of generalised seizures. CBD (100 mg/kg) exerted clear anticonvulsant effects with significant decreases in incidence of severe seizures and mortality in comparison to vehicle-treated animals. Finally, CBD acted with only low affinity at cannabinoid CB(1) receptors and displayed no agonist activity in [(35)S]GTPgammaS assays in cortical membranes. These findings suggest that CBD acts to inhibit epileptiform activity in vitro and seizure severity in vivo. Thus, we demonstrate the potential of CBD as a novel anti-epileptic drug (AED) in the unmet clinical need associated with generalised seizures.

Spatial covariation of Azotobacter abundance and soil properties: A case study using the wavelet transform

The soil microflora is very heterogeneous in its spatial distribution. The origins of this heterogeneity and its significance for soil function are not well understood. A problem for understanding spatial variation better is the assumption of statistical stationarity that is made in most of the statistical methods used to assess it. These assumptions are made explicit in geostatistical methods that have been increasingly used by soil biologists in recent years. Geostatistical methods are powerful, particularly for local prediction, but they require the assumption that the variability of a property of interest is spatially uniform, which is not always plausible given what is known about the complexity of the soil microflora and the soil environment. We have used the wavelet transform, a relatively new innovation in mathematical analysis, to investigate the spatial variation of abundance of Azotobacter in the soil of a typical agricultural landscape. The wavelet transform entails no assumptions of stationarity and is well suited to the analysis of variables that show intermittent or transient features at different spatial scales. In this study, we computed cross-variograms of Azotobacter abundance with the pH, water content and loss on ignition of the soil. These revealed scale-dependent covariation in all cases. The wavelet transform also showed that the correlation of Azotobacter abundance with all three soil properties depended on spatial scale, the correlation generally increased with spatial scale and was only significantly different from zero at some scales. However, the wavelet analysis also allowed us to show how the correlation changed across the landscape. For example, at one scale Azotobacter abundance was strongly correlated with pH in part of the transect, and not with soil water content, but this was reversed elsewhere on the transect. The results show how scale-dependent variation of potentially limiting environmental factors can induce a complex spatial pattern of abundance in a soil organism. The geostatistical methods that we used here make assumptions that are not consistent with the spatial changes in the covariation of these properties that our wavelet analysis has shown. This suggests that the wavelet transform is a powerful tool for future investigation of the spatial structure and function of soil biota. (c) 2006 Elsevier Ltd. All rights reserved.

Plant roots release phospholipid surfactants that modify the physical and chemical properties of soil

Plant root mucilages contain powerful surfactants that will alter the interaction of soil solids with water and ions, and the rates of microbial processes. The lipid composition of maize, lupin and wheat root mucilages was analysed by thin layer chromatography and gas chromatography-mass spectrometry. A commercially available phosphatidylcholine (lecithin), chemically similar to the phospholipid surfactants identified in the mucilages, was then used to evaluate its effects on selected soil properties. The lipids found in the mucilages were principally phosphatidylcholines, composed mainly of saturated fatty acids, in contrast to the lipids extracted from root tissues. In soil at low tension, lecithin reduced the water content at any particular tension by as much as 10 and 50% in soil and acid-washed sand, respectively. Lecithin decreased the amount of phosphate adsorption in soil and increased the phosphate concentration in solution by 10%. The surfactant also reduced net rates of ammonium consumption and nitrate production in soil. These experiments provide the first evidence we are aware of that plant-released surfactants will significantly modify the biophysical environment of the rhizosphere.

Independent evaluation of the ability of spaceborne radar and lidar to retrieve the microphysical and radiative properties of ice clouds

The combination of radar and lidar in space offers the unique potential to retrieve vertical profiles of ice water content and particle size globally, and two algorithms developed recently claim to have overcome the principal difficulty with this approach-that of correcting the lidar signal for extinction. In this paper "blind tests" of these algorithms are carried out, using realistic 94-GHz radar and 355-nm lidar backscatter profiles simulated from aircraft-measured size spectra, and including the effects of molecular scattering, multiple scattering, and instrument noise. Radiation calculations are performed on the true and retrieved microphysical profiles to estimate the accuracy with which radiative flux profiles could be inferred remotely. It is found that the visible extinction profile can be retrieved independent of assumptions on the nature of the size distribution, the habit of the particles, the mean extinction-to-backscatter ratio, or errors in instrument calibration. Local errors in retrieved extinction can occur in proportion to local fluctuations in the extinction-to-backscatter ratio, but down to 400 m above the height of the lowest lidar return, optical depth is typically retrieved to better than 0.2. Retrieval uncertainties are greater at the far end of the profile, and errors in total optical depth can exceed 1, which changes the shortwave radiative effect of the cloud by around 20%. Longwave fluxes are much less sensitive to errors in total optical depth, and may generally be calculated to better than 2 W m(-2) throughout the profile. It is important for retrieval algorithms to account for the effects of lidar multiple scattering, because if this is neglected, then optical depth is underestimated by approximately 35%, resulting in cloud radiative effects being underestimated by around 30% in the shortwave and 15% in the longwave. Unlike the extinction coefficient, the inferred ice water content and particle size can vary by 30%, depending on the assumed mass-size relationship (a problem common to all remote retrieval algorithms). However, radiative fluxes are almost completely determined by the extinction profile, and if this is correct, then errors in these other parameters have only a small effect in the shortwave (around 6%, compared to that of clear sky) and a negligible effect in the longwave.

Characteristic magnetic field and speed properties of interplanetary coronal mass ejections and their sheath regions

Prediction of the solar wind conditions in near-Earth space, arising from both quasi-steady and transient structures, is essential for space weather forecasting. To achieve forecast lead times of a day or more, such predictions must be made on the basis of remote solar observations. A number of empirical prediction schemes have been proposed to forecast the transit time and speed of coronal mass ejections (CMEs) at 1 AU. However, the current lack of magnetic field measurements in the corona severely limits our ability to forecast the 1 AU magnetic field strengths resulting from interplanetary CMEs (ICMEs). In this study we investigate the relation between the characteristic magnetic field strengths and speeds of both magnetic cloud and noncloud ICMEs at 1 AU. Correlation between field and speed is found to be significant only in the sheath region ahead of magnetic clouds, not within the clouds themselves. The lack of such a relation in the sheaths ahead of noncloud ICMEs is consistent with such ICMEs being skimming encounters of magnetic clouds, though other explanations are also put forward. Linear fits to the radial speed profiles of ejecta reveal that faster-traveling ICMEs are also expanding more at 1 AU. We combine these empirical relations to form a prediction scheme for the magnetic field strength in the sheaths ahead of magnetic clouds and also suggest a method for predicting the radial speed profile through an ICME on the basis of upstream measurements.

Effect of growth time on the surface and adhesion properties of Lactobacillus rhamnosus GG

Aims: To investigate the changes in the surface properties of Lactobacillus rhamnosus GG during growth, and relate them with the ability of the Lactobacillus cells to adhere to Caco-2 cells. Methods and Results: Lactobacillus rhamnosus GG was grown in complex medium, and cell samples taken at four time points and freeze dried. Untreated and trypsin treated freeze dried samples were analysed for their composition using SDS-PAGE analysis and Fourier transform infrared spectroscopy (FTIR), hydrophobicity and zeta potential, and for their ability to adhere to Caco-2 cells. The results suggested that in the case of early exponential phase samples (4 and 8 h), the net surface properties, i.e. hydrophobicity and charge, were determined to a large extent by anionic hydrophilic components, whereas in the case of stationary phase samples (13 and 26 h), hydrophobic proteins seemed to play the biggest role. Considerable differences were also observed between the ability of the different samples to adhere to Caco-2 cells; maximum adhesion was observed for the early stationary phase sample (13 h). The results suggested that the adhesion to Caco-2 cells was influenced by both proteins and non-proteinaceous compounds present on the surface of the Lactobacillus cells. Conclusion: The surface properties of Lact. rhamnosus GG changed during growth, which in return affected the ability of the Lactobacillus cells to adhere to Caco-2 cells. Significance and Impact of the Study: The levels of adhesion of Lactobacillus cells to Caco-2 cells were influenced by the growth time and reflected changes on the bacterial surface. This study provides critical information on the physicochemical factors that influence bacterial adhesion to intestinal cells.

Growth rate and physical properties of Erythrina variegata with regard to dry matter production

Erythrina variegata grown from seeds showed a great deal of variation with respect to height, diameter, density of wood and dry matter production. Statistical analysis showed that the density of wood produced by any plant was not related to its growth rate, but dry matter production was associated with plant growth rate (height and diameter) that could lead to overall increased dry matter or biomass production.