The uses of Atuna racemosa Raf. (Chrysobalanaceae) in Samoa

An ethnobotanical study was made of the uses of Atuna racemosa subsp. racemosa (Chrysobalanaceae) in Samoa. The main use is of the cotyledons to extract an anti-inflammatory massage oil and a putty to caulk boats. Minor uses as a medicinal and of the wood are reported and a survey of herbarium material shows that the fruit of Atuna is widely used throughout the Pacific region.

Regulation of Ras.GTP loading and Ras-Raf association in neonatal rat ventricular myocytes by G protein-coupled receptor agonists and phorbol ester. Activation of the extracellular signal-regulated kinase cascade by phorbol ester is mediated by Ras.

The small G protein Ras has been implicated in hypertrophy of cardiac myocytes. We therefore examined the activation (GTP loading) of Ras by the following hypertrophic agonists: phorbol 12-myristate 13-acetate (PMA), endothelin-1 (ET-1), and phenylephrine (PE). All three increased Ras.GTP loading by 10-15-fold (maximal in 1-2 min), as did bradykinin. Other G protein-coupled receptor agonists (e.g. angiotensin II, carbachol, isoproterenol) were less effective. Activation of Ras by PMA, ET-1, or PE was reduced by inhibition of protein kinase C (PKC), and that induced by ET-1 or PE was partly sensitive to pertussis toxin. 8-(4-Chlorophenylthio)-cAMP (CPT-cAMP) did not inhibit Ras.GTP loading by PMA, ET-1, or PE. The association of Ras with c-Raf protein was increased by PMA, ET-1, or PE, and this was inhibited by CPT-cAMP. However, only PMA and ET-1 increased Ras-associated mitogen-activated protein kinase kinase 1-activating activity, and this was decreased by PKC inhibition, pertussis toxin, and CPT-cAMP. PMA caused the rapid appearance of phosphorylated (activated) extracellular signal-regulated kinase in the nucleus, which was inhibited by a microinjected neutralizing anti-Ras antibody. We conclude that PKC- and Gi-dependent mechanisms mediate the activation of Ras in myocytes and that Ras activation is required for stimulation of extracellular signal-regulated kinase by PMA.

Using TerraSAR-X data for improved urban flood model validation.

Urban flood inundation models require considerable data for their parameterisation, calibration and validation. TerraSAR-X should be suitable for urban flood detection because of its high resolution in stripmap/spotlight modes. The paper describes ongoing work on a project to assess how well TerraSAR-X can detect flooded regions in urban areas, and how well these can constrain the parameters of an urban flood model. The study uses a TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK , in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with LiDAR data to estimate regions of the image in which water would not be visible due to shadow or layover caused by buildings and vegetation. An algorithm for the delineation of flood water in urban areas is described, together with its validation using the aerial photographs.

Flood detection in urban areas using TerraSAR-X

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X Synthetic Aperture Radar (SAR) data to detect flooded regions in urban areas is described. The study uses a TerraSAR-X image of a 1 in 150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SAR End-To-End simulator (SETES) was used in conjunction with airborne scanning laser altimetry (LiDAR) data to estimate regions of the image in which water would not be visible due to shadow or layover caused by buildings and taller vegetation. A semi-automatic algorithm for the detection of floodwater in urban areas is described, together with its validation using the aerial photographs. 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. The algorithm is aimed at producing urban flood extents with which to calibrate and validate urban flood inundation models, and these findings indicate that TerraSAR-X is capable of providing useful data for this purpose.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

The stimulation of mitogenic signaling pathways by N-POMC peptides

The N-terminal fragment of pro-opiomelancortin (POMC) has been shown previously to act as an adrenal mitogen. However, little is known about the molecular mechanisms by which mitogenesis is stimulated, although it has been shown that N-POMC1-28 Stimulates the ERK pathway in human H295R cells. We have investigated signaling stimulated by N-POMC1-28 and N-POMC1-49 in the mouse Y1 cell line and found that both peptides stimulate ERK phosphorylation with maximal stimulation being achieved within 5 min. Similar results were observed for both MEK and c-Raf phosphorylation, although N-POMC1-49 stimulated the phosphorylation of Akt more robustly than N-POMC1-28. We also investigated the expression of tyrosine kinase receptors in adrenal cells. PCR utilizing degenerate primers was performed on cDNA from both Y1 cells and rat adrenal tissue. Sequencing of 114 clones from each cDNA population revealed the expression of a number of receptors, several of which have not been described previously in the adrenal. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Simple sequence repeats reveal uneven distribution of genetic diversity in chloroplast genomes of Brassica oleracea L. and (n=9) wild relatives

Diversity in the chloroplast genome of 171 accessions representing the Brassica 'C' (n = 9) genome, including domesticated and wild B. oleracea and nine inter-fertile related wild species, was investigated using six chloroplast SSR (microsatellite) markers. The lack of diversity detected among 105 cultivated and wild accessions of B. oleracea contrasted starkly with that found within its wild relatives. The vast majority of B. oleracea accessions shared a single haplotype, whereas as many as six haplotypes were detected in two wild species, B. villosa Biv. and B. cretica Lam.. The SSRs proved to be highly polymorphic across haplotypes, with calculated genetic diversity values (H) of 0.23-0.87. In total, 23 different haplotypes were detected in C genome species, with an additional five haplotypes detected in B. rapa L. (A genome n = 10) and another in B. nigra L. (B genome, n = 8). The low chloroplast diversity of B. oleracea is not suggestive of multiple domestication events. The predominant B. oleracea haplotype was also common in B. incana Ten. and present in low frequencies in B. villosa, B. macrocarpa Guss, B. rupestris Raf. and B. cretica. The chloroplast SSRs reveal a wealth of diversity within wild Brassica species that will facilitate further evolutionary and phylogeographic studies of this important crop genus.

Localisation studies of cell-wall degrading enzymes in soybean

Postembedding immunoelectron microscopy has been used to investigate the diffusibility of an endo-beta-1,4-glucanase and a xylanase from A. niger in soybean. The results showed more specific localisation of the enzymes into the protein and lipid bodies of soybean cells. This was against our hypothesis that suggested that the enzymes should be localised in the cell wall.

Peroxy radical partitioning during the AMMA radical intercomparison exercise

Peroxy radicals were measured onboard two scientific aircrafts during the AMMA (African Monsoon Multidisciplinary Analysis) campaign in summer 2006. This paper reports results from the flight on 16 August 2006 during which measurements of HO2 by laser induced fluorescence spectroscopy at low pressure (LIF-FAGE) and total peroxy radicals (RO2* = HO2+ΣRO2, R = organic chain) by two similar instruments based on the peroxy radical chemical amplification (PeRCA) technique were subject of a blind intercomparison. The German DLR-Falcon and the British FAAM-BAe-146 flew wing tip to wing tip for about 30 min making concurrent measurements on 2 horizontal level runs at 697 and 485 hPa over the same geographical area in Burkina Faso. A full set of supporting measurements comprising photolysis frequencies, and relevant trace gases like CO, NO, NO2, NOy, O3 and a wider range of VOCs were collected simultaneously. Results are discussed on the basis of the characteristics and limitations of the different instruments used. Generally, no data bias are identified and the RO2* data available agree quite reasonably within the instrumental errors. The [RO2*]/[HO2] ratios, which vary between 1:1 and 3:1, as well as the peroxy radical variability, concur with variations in photolysis rates and in other potential radical precursors. Model results provide additional information about dominant radical formation and loss processes.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.

Crosstalk with insulin and dependence on PI3K/Akt/mTOR rather than MAPK pathways in upregulation of basal growth following long-term oestrogen deprivation in three human breast cancer cell lines

Background: MCF-7, T-47-D, ZR-75-1 human breast cancer cell lines are dependent on oestrogen for growth but can adapt to grow during long-term oestrogen deprivation. This serves as a model for identification of therapeutic targets in endocrine-resistant breast cancer. Methods: An overlooked complication of this model is that it involves more than non-addition of oestrogen, and inadequate attention has been given to separating molecular events associated with each of the culture manipulations. Results: Insulin and oestradiol were shown to protect MCF-7 cells against upregulation of basal growth, demonstrating a crosstalk in the growth adaptation process. Increased phosphorylation of p44/42MAPK and c-Raf reflected removal of insulin from the medium and proliferation of all three cell lines was inhibited to a lesser extent by PD98059 and U0126 following long-term oestrogen/insulin withdrawal, demonstrating a reduced dependence on the MAPK pathway. By contrast, long-term oestrogen/insulin deprivation did not alter levels of phosphorylated Akt and did not alter the dose-response of growth inhibition with LY294002 in any of the three cell lines. The IGF1R inhibitor picropodophyllin inhibited growth of all MCF-7 cells but only in the long-term oestrogen/insulin-deprived cells was this paralleled by reduction in phosphorylated p70S6K, a downstream target of mTOR. Long-term oestrogen/insulin-deprived MCF-7 cells had higher levels of phosphorylated p70S6K and developed increased sensitivity to growth inhibition by rapamycin. Conclusions: The greater sensitivity to growth inhibition by rapamycin in all three cell lines following long-term oestrogen/insulin deprivation suggests rapamycin-based therapies might be more effective in breast cancers with acquired oestrogen resistance. Keywords Akt, breast cancer cells, endocrine resistance, insulin, MAPK, MCF-7 cells, mTOR, oestrogen, oestrogen-deprived, PI3K, picropodophyllin, rapamycin, T-47-D cells, ZR-75-1 cells

Path planning of robots in noisy workspaces using learning automata

The problem of a manipulator operating in a noisy workspace and required to move from an initial fixed position P0 to a final position Pf is considered. However, Pf is corrupted by noise, giving rise to Pˆf, which may be obtained by sensors. The use of learning automata is proposed to tackle this problem. An automaton is placed at each joint of the manipulator which moves according to the action chosen by the automaton (forward, backward, stationary) at each instant. The simultaneous reward or penalty of the automata enables avoiding any inverse kinematics computations that would be necessary if the distance of each joint from the final position had to be calculated. Three variable-structure learning algorithms are used, i.e., the discretized linear reward-penalty (DLR-P, the linear reward-penalty (LR-P ) and a nonlinear scheme. Each algorithm is separately tested with two (forward, backward) and three forward, backward, stationary) actions.

Trajectory planning of a robot using learning algorithms

The authors consider the problem of a robot manipulator operating in a noisy workspace. The manipulator is required to move from an initial position P(i) to a final position P(f). P(i) is assumed to be completely defined. However, P(f) is obtained by a sensing operation and is assumed to be fixed but unknown. The authors approach to this problem involves the use of three learning algorithms, the discretized linear reward-penalty (DLR-P) automaton, the linear reward-penalty (LR-P) automaton and a nonlinear reinforcement scheme. An automaton is placed at each joint of the robot and by acting as a decision maker, plans the trajectory based on noisy measurements of P(f).

Validation of the FALL3D ash dispersion model using observations of the 2010 Eyjafjallajökull volcanic ash clouds

During April-May 2010 volcanic ash clouds from the Icelandic Eyjafjallajökull volcano reached Europe causing an unprecedented disruption of the EUR/NAT region airspace. Civil aviation authorities banned all flight operations because of the threat posed by volcanic ash to modern turbine aircraft. New quantitative airborne ash mass concentration thresholds, still under discussion, were adopted for discerning regions contaminated by ash. This has implications for ash dispersal models routinely used to forecast the evolution of ash clouds. In this new context, quantitative model validation and assessment of the accuracies of current state-of-the-art models is of paramount importance. The passage of volcanic ash clouds over central Europe, a territory hosting a dense network of meteorological and air quality observatories, generated a quantity of observations unusual for volcanic clouds. From the ground, the cloud was observed by aerosol lidars, lidar ceilometers, sun photometers, other remote-sensing instru- ments and in-situ collectors. From the air, sondes and multiple aircraft measurements also took extremely valuable in-situ and remote-sensing measurements. These measurements constitute an excellent database for model validation. Here we validate the FALL3D ash dispersal model by comparing model results with ground and airplane-based measurements obtained during the initial 14e23 April 2010 Eyjafjallajökull explosive phase. We run the model at high spatial resolution using as input hourly- averaged observed heights of the eruption column and the total grain size distribution reconstructed from field observations. Model results are then compared against remote ground-based and in-situ aircraft-based measurements, including lidar ceilometers from the German Meteorological Service, aerosol lidars and sun photometers from EARLINET and AERONET networks, and flight missions of the German DLR Falcon aircraft. We find good quantitative agreement, with an error similar to the spread in the observations (however depending on the method used to estimate mass eruption rate) for both airborne and ground mass concentration. Such verification results help us understand and constrain the accuracy and reliability of ash transport models and it is of enormous relevance for designing future operational mitigation strategies at Volcanic Ash Advisory Centers.