Storage proteins and cell wall mobilisation in seeds of Sesbania virgata (Cav.) Pers. (Leguminosae)

The endosperm of seeds of Sesbania virgata (Cav.) Pers. accumulates galactomannan as a cell wall storage polysaccharide. It is hydrolysed by three enzymes, one of them being alpha-galactosidase. A great amount of protein bodies is found in the cytoplasm of endospermic cells, which are thought to play the major role as a nitrogen reserve in this seed. The present work aimed at understanding how the production of enzymes that degrade storage compounds is controlled. We performed experiments with addition of inhibitors of transcription (actinomycin-d and alpha-amanitin) and translation (cycloheximide) during and after germination. In order to follow the performance of storage mobilisation, we measured fresh mass, protein contents and alpha-galactosidase activity. All the inhibitors tested had little effect on seed germination and seedling development. Actinomycin-d and cycloheximide provoked a slight inhibition of the storage protein degradation and concomitantly lead to an elevation of the alpha-galactosidase activity. Although alpha-amanitin showed some effect on seedling development at latter stages, it presented the former effect and did not change galactomannan degradation performance. Our data suggest that some of the proteases may be synthesised de novo, whereas alpha-galactosidase seems to be present in the endosperm cells probably as an inactive polypeptide in the protein bodies, being probably activated by proteolysis when the latter organelle is disassembled. These evidences suggest the existence of a connection between storage proteins and carbohydrates mobilisation in seeds of S. virgata, which would play a role by assuring a balanced afflux of the carbon and nitrogen to the seedling development.

Brumadoite, a new copper tellurate hydrate, from Brumado, Bahia, Brazil

Brumadoite, ideally Cu(2)Te(6+)O(4)(OH)(4)center dot 5H(2)O, is a new mineral from Pedra Preta mine, Serra das Eguas, Brumado, Bahia, Brazil. It occurs as microcrystalline aggregates both on and, rarely, pseudomorphous after coarse-grained magnesite, associated with mottramite and quartz. Crystals are platy, subhedral, 1-2 mu m in size. Brumadoite is blue (near RHS 114B), has a pale blue streak and a vitreous lustre. It is transparent to translucent and does not fluoresce. The empirical formula is (Cu(2.90)Pb(0.04)Ca(0.01))(Sigma 2.95) (Te(0.93)(6+)Si(0.05))(Sigma 0.98)O(3.92)(OH)(3.84)center dot 5.24H(2)O. Infrared spectra clearly show both (OH) and H(2)O. Microchemical spot tests using a KI Solution show that brumadoite has tellurium in the 6(+) state. The mineral is monoclinic, P2(1)/m or P2(1). Unit-cell parameters refined from X-ray powder data are a 8.629(2) angstrom, b 5.805(2) angstrom, c 7.654(2) angstrom, beta 103.17(2)degrees, V 373.3(2) angstrom(3), Z = 2. The eight strongest X-ray powder-diffraction lines [d in angstrom, (l),(hkl)] are: 8.432,(100),(100); 3.162,(66),((2) over bar 02); 2.385,(27),(220); 2.291,((1) over bar 12),(22); 1.916,(11),(312); 1.666,(14),((4) over bar 22,114); 1.452,(10), (323, 040); 1.450,(10),(422,403). The name is for the type locality, Brumado, Bahia, Brazil. The new mineral species has been approved by the CNMNC (IMA 2008-028).

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.