{Reference Type}: Journal Article

{Author}: Laura Luft；Carsten Neumann；Matthias Freude；Niels Blaum；Florian Jeltsch

{Year}: 2014

{Title}: Hyperspectral modeling of ecological indicators – A new approach for monitoring former military training areas

{Tag}: 0

{Star}: 0

{Volume}: 46

{Issue}: 0

{Pages}: 264 - 285

{ISBN/ISSN}: 1470-160X

{Keywords}: Ecological health；Fauna；Flora；Hyperspectral remote sensing；Military conversion；Natura 2000 monitoring

{Abstract}: Military areas are valuable habitats and refuges for rare and endangered plants and animals. We developed a new approach applying innovative methods of hyperspectral remote sensing to bridge the existing gap between remote sensing technology and the demands of the nature conservation community. Remote sensing has already proven to be a valuable monitoring instrument. However, the approaches lack the consideration of the demands of applied nature conservation which includes the legal demands of the EU Habitat Directive. Following the idea of the Vital Signs Monitoring in the USA, we identified a subset of the highest priority monitoring indicators for our study area. We analyzed continuous spectral response curves and tested the measurability of N = 19 indicators on the basis of complexity levels aggregated from extensive vegetation assemblages. The spectral differentiability for the floristic as well as faunistic indicators revealed values up to 100% accuracy. We point out difficulties when it comes to distinguishing faunistic habitat requirements of several species adapted to dry open landscapes, which in this case results in Overall accuracy of 67, 87–95, and 35% in the error matrix. In summary, we provide an applicable and feasible method to facilitating monitoring military areas by hyperspectral remote sensing in the following.

{Database Provider}: Web of Sciencedirect

{Language}: English

{Reference Type}: Journal Article

{Author}: Gildomar L Valasques Junior；Flávia O de Lima；Elisangela F Boffo；Jener D   G Santos；Bruno C da Silva；Sandra A de Assis

{Year}: 2014

{Title}: Extraction optimization and antinociceptive activity of (1⟶3)-β-d-glucan from Rhodotorula mucilaginosa

{Tag}: 0

{Star}: 0

{Volume}: 105

{Issue}: 0

{Pages}: 293-299

{ISBN/ISSN}: 0144-8617

{Keywords}: Response surface methodology；β-d-glucan；Optimization；Rhodotorula mucilaginosa；Antinociceptive

{Abstract}:

β-d-glucans are polymers of d-glucose monomers found in the cell walls of many bacteria, plants, fungi and yeasts. A variety of β-d-glucans differing in structures have been isolated from various sources and their biological activity to be regulated by various structural factors, such as the primary structure, molecular weight, solubility, and conformation. This study investigated the effect of extraction time and temperature on the yield of β-d-glucan produced by Rhodotorula mucilaginosa. A statistical Doehlert design was applied to determine the important effects and interactions of these independent variables on the yield of β-d-glucan, the dependent variable. Significant models were obtained. The best yield was of 25% obtained after 128 min of extraction in a temperature of 72 °C. The polysaccharides were characterized as (1⟶3)-β-d-glucan by methods spectroscopic (FT-IR, 1HNMR and 13CNMR). In addition, the antinociceptive effect was evaluated using different experimental tests (acetic acid-induced writhing test, formalin test and tail immersion test). The (1⟶3)-β-d-glucan showed a potent peripheral antinociceptive effect, possibly by the inhibition of inflammatory mediators.

{Database Provider}: Web of Sciencedirect

{Language}: English

{Reference Type}: Journal Article

{Author}: Lucie Kubienová；David Kopečny；Martina Tylichová；Pierre Briozzo；Jana Skopalová；Marek Šebela；Milan Navrátil；Roselyne Tache；Lenka Luhová；Juan B Barroso；Marek Petřivalsky

{Year}: 2013

{Title}: Structural and functional characterization of a plant S-nitrosoglutathione reductase from Solanum lycopersicum

{Tag}: 0

{Star}: 0

{Volume}: 95

{Issue}: 4

{Pages}: 889 - 902

{ISBN/ISSN}: 0300-9084

{Keywords}: Alcohol dehydrogenase；S-(hydroxymethyl)glutathione；S-nitrosoglutathione reductase；S-nitrosothiols；Solanum lycopersicum；Tomato

{Abstract}:S-nitrosoglutathione reductase (GSNOR), also known as S-(hydroxymethyl)glutathione (HMGSH) dehydrogenase, belongs to the large alcohol dehydrogenase superfamily, namely to the class III ADHs. GSNOR catalyses the oxidation of HMGSH to S-formylglutathione using a catalytic zinc and NAD+ as a coenzyme. The enzyme also catalyses the NADH-dependent reduction of S-nitrosoglutathione (GSNO). In plants, GSNO has been suggested to serve as a nitric oxide (NO) reservoir locally or possibly as NO donor in distant cells and tissues. NO and NO-related molecules such as S-nitrosothiols (S-NOs) play a central role in the regulation of normal plant physiological processes and host defence. The enzyme thus participates in the cellular homeostasis of S-NOs and in the metabolism of reactive nitrogen species. Although GSNOR has recently been characterized from several organisms, this study represents the first detailed biochemical and structural characterization of a plant GSNOR, that from tomato (Solanum lycopersicum). SlGSNOR gene expression is higher in roots and stems compared to leaves of young plants. It is highly expressed in the pistil and stamens and in fruits during ripening. The enzyme is a dimer and preferentially catalyses reduction of GSNO while glutathione and S-methylglutathione behave as non-competitive inhibitors. Using NAD+, the enzyme oxidizes HMGSH and other alcohols such as cinnamylalcohol, geraniol and ω-hydroxyfatty acids. The crystal structures of the apoenzyme, of the enzyme in complex with NAD+ and in complex with NADH, solved up to 1.9  Å resolution, represent the first structures of a plant GSNOR. They confirm that the binding of the coenzyme is associated with the active site zinc movement and changes in its coordination. In comparison to the well characterized human GSNOR, plant GSNORs exhibit a difference in the composition of the anion-binding pocket, which negatively influences the affinity for the carboxyl group of ω-hydroxyfatty acids.

{Database Provider}: Web of Sciencedirect

{Language}: English