A Rho family GTPase controls actin dynamics and tip growth via two counteracting downstream pathways in pollen tubes.

Tip growth in neuronal cells, plant cells, and fungal hyphae is known to require tip-localized Rho GTPase, calcium, and filamentous actin (F-actin), but how they interact with each other is unclear. The pollen tube is an exciting model to study spatiotemporal regulation of tip growth and F-actin dynamics. An Arabidopsis thaliana Rho family GTPase, ROP1, controls pollen tube growth by regulating apical F-actin dynamics. This paper shows that ROP1 activates two counteracting pathways involving the direct targets of tip-localized ROP1: RIC3 and RIC4. RIC4 promotes F-actin assembly, whereas RIC3 activates Ca(2+) signaling that leads to F-actin disassembly. Overproduction or depletion of either RIC4 or RIC3 causes tip growth defects that are rescued by overproduction or depletion of RIC3 or RIC4, respectively. Thus, ROP1 controls actin dynamics and tip growth through a check and balance between the two pathways. The dual and antagonistic roles of this GTPase may provide a unifying mechanism by which Rho modulates various processes dependent on actin dynamics in eukaryotic cells

MM# Modeling of Aldopentose Pyranose Rings

MM3 (version 1992, ϵ=3.0) was used to study the ring conformations of d-xylopyranose, d-lyxopyranose and d-arabinopyranose. The energy surfaces exhibit low-energy regions corresponding to chair and skew forms with high-energy barriers between these regions corresponding to envelope and half-chair forms. The lowest energy conformer is 4 C 1 for α- and β-xylopyranose and α- and β-lyxopyranose, and the lowest energy conformer is 1 C 4 for α- and β-arabinopyranose. Only α-lyxopyranose exhibits a secondary low-energy region (1 C 4) within 1 kcal/mol of its global minimum. Overall, the results are in good agreement with NMR and crystallographic results. For many of these molecules, skew conformations are found with relatively low energies (2.5 to 4 kcal/mol above lowest energy chair form). The 2 S O and 1 C 4conformers of crystalline benzoyl derivatives of xylopyranose are in secondary low-energy regions on the β-xylopyranose surface, within 3.8 kcal/mol of the global 4 C 1 minimum

Low Molecular Weight Organic Composition of Ethanol Stillage from Sugarcane Molasses, Citrus Waste, and Sweet Whey

Filtered stillage from the distillation of ethanol made by yeast fermentation of sugarcane molasses, citrus waste, and sweet whey was analyzed by gas chromatography/mass spectroscopy and by high-performance liquid chromatography. Nearly all of the major peaks representing low molecular weight organic components were identified. The major components in cane stillage were, in decreasing order of concentration, lactic acid, glycerol, ethanol, and acetic acid. In citrus stillage they were lactic acid, glycerol, myo-inositol, acetic acid, chiro-inositol, and proline. Finally, in whey stillage the major components were lactose, lactic acid, glycerol, acetic acid, glucose, arabinitol, and ribitol

Automatic detection and delineation of karst terrain depressions and its application in geomorphological mapping and morphometric analysis

Digital elevation models (DEM) are digital representations of topography that are especially suitable for numerical terrain analysis in earth sciences and engineering. One of the main quantitative uses of DEM is the automatic delineation of flow networks and watersheds in hydrology and geomorphology. In these applications (using both low-resolution and precision DEM) depressions hinder the inference of pathways and a lot of work has been done in designing algorithms that remove them so as to generate depression-free digital elevation models with no interruptions to flow. There are, however, geomorphological environments, such as karst terrains, in which depressions are singular elements, on scales ranging from centimetres to kilometres, which are of intrinsic interest. The detection of these depressions is of significant interest in geomorphologic mapping because the development of large depressions is normal in karst terrains: potholes, blind valleys, dolines, uvalas and poljes. The smallest depressions that can be detected depend on the spatial resolution (pixel size) of the DEM. For example, depressions from centimetres to a few metres, such as some types of karren, cannot be detected if the raster digital elevation model has a spatial resolution greater than, say, 5 m (i.e., square 5m pixel). In this work we describe a method for the automatic detection and delineation of terrain depressions. First, we apply a very efficient algorithm to remove pits from the DEM. The terrain depressions are then obtained by subtracting the depression-free DEM from the original DEM. The final product is a digital map of depressions that facilitates the calculation of morphometric features such as the geometry of the depressions, the mean depth of the depressions, the density of depressions across the study area and the relationship between depressions and other variables such as altitude. The method is illustrated by applying it to data from the Sierra de las Nieves karst massif in the province of Málaga in Southern Spain. This is a carbonate aquifer that is drained by three main springs and in which the depressions play an important role in the recharge of the aquifer. A doline density map, produced from a map of 324 detected dolines/uvalas, identifies three main recharge areas of the three springs. Other morphometric results related to the size and direction of the dolines are also presented. Finally the dolines can be incorporated into a geomorphology map

Automatic detection and delineation of karst terrain depressions and its application in geomorphological mapping and morphometric analysis

Digital elevation models (DEM) are digital representations of topography that are especially suitable for numerical terrain analysis in earth sciences and engineering. One of the main quantitative uses of DEM is the automatic delineation of flow networks and watersheds in hydrology and geomorphology. In these applications (using both low-resolution and precision DEM) depressions hinder the inference of pathways and a lot of work has been done in designing algorithms that remove them so as to generate depression-free digital elevation models with no interruptions to flow. There are, however, geomorphological environments, such as karst terrains, in which depressions are singular elements, on scales ranging from centimetres to kilometres, which are of intrinsic interest. The detection of these depressions is of significant interest in geomorphologic mapping because the development of large depressions is normal in karst terrains: potholes, blind valleys, dolines, uvalas and poljes. The smallest depressions that can be detected depend on the spatial resolution (pixel size) of the DEM. For example, depressions from centimetres to a few metres, such as some types of karren, cannot be detected if the raster digital elevation model has a spatial resolution greater than, say, 5 m (i.e., square 5m pixel). In this work we describe a method for the automatic detection and delineation of terrain depressions. First, we apply a very efficient algorithm to remove pits from the DEM. The terrain depressions are then obtained by subtracting the depression-free DEM from the original DEM. The final product is a digital map of depressions that facilitates the calculation of morphometric features such as the geometry of the depressions, the mean depth of the depressions, the density of depressions across the study area and the relationship between depressions and other variables such as altitude. The method is illustrated by applying it to data from the Sierra de las Nieves karst massif in the province of Málaga in Southern Spain. This is a carbonate aquifer that is drained by three main springs and in which the depressions play an important role in the recharge of the aquifer. A doline density map, produced from a map of 324 detected dolines/uvalas, identifies three main recharge areas of the three springs. Other morphometric results related to the size and direction of the dolines are also presented. Finally the dolines can be incorporated into a geomorphology map

Increasing knowledge of the transmissivity field of a detrital aquifer by geostatistical merging of different sources of information

Acknowledgements The work reported here was supported by research project PID2019-106435GB-I00 of the Ministerio de Ciencia e Innovación of Spain. We thank Philippe Renard and the two anonymous reviewers who provided constructive comments that have allowed us to improve the final version of this paper.Transmissivity is a significant hydrogeological parameter that affects the reliability of groundwater flow and transport models. This study demonstrates the improvement in the estimated transmissivity field of an unconfined detritic aquifer that can be obtained by using geostatistical methods to combine three types of data: hard transmissivity data obtained from pumping tests, soft transmissivity data obtained from lithological information from boreholes, and water head data. The piezometric data can be related to transmissivity by solving the hydrogeology inverse problem, i.e., including the observed water head to determine the unknown model parameters (log transmissivities). The geostatistical combination of all the available information is achieved by using three different geostatistical methodologies: ordinary kriging, ordinary co-kriging and inverse problem universal co-kriging. In addition, there are eight methodological cases to be compared according to which log-transmissivity data are considered as the primary variable in co-kriging and whether two or three variables are used in inverse-problem universal co-kriging. The results are validated by using the performance statistics of the direct modelling of the unconfined groundwater flow and comparing observed water heads with the modelled ones. Although the results show that the two sets of log-transmissivity data are incompatible, the set of log-transmissivity data from the lithofacies provides a good log-transmissivity image that can be improved by inverse modelling. The map provided by inverse-problem universal co-kriging provides the best results. Using three variables, rather than two in the inverse problem, gives worse results because of the incompatibility of the log-transmissivity data sets.Project PID2019-106435GB-I00 of the Ministerio de Ciencia e Innovación of SpainOpen Access funding provided thanks to the CRUE-CSIC agreement with Springer Natur

A Comprehensive Study of an Acid-Based Reversible H2-Br2 Fuel Cell System

The regenerative H2-Br2 fuel cell has been a subject of notable interest and is considered as one of the suitable candidates for large scale electrical energy storage. In this study, the preliminary performance of a H2-Br2 fuel cell using both conventional as well as novel materials (Nafion and electrospun composite membranes along with Pt and RhxSy electrocatalysts) is discussed. The performance of the H2-Br2 fuel cell obtained with a conventional Nafion membrane and Pt electrocatalyst was enhanced upon employing a double-layer Br2 electrode while raising the cell temperature to 45°C. The active area and wetting characteristics of Br2 electrodes were improved upon by either pre-treating with HBr or boiling them in de-ionized water. On the other hand, similar or better performances were obtained using dual fiber electrospun composite membranes (PFSA/PPSU) versus using Nafion membranes. The RhxSy electrocatalyst proved to be more stable in the presence of HBr/Br2 than pure Pt. However, the H2 oxidation activity on RhxSy is quite low compared to that of Pt. In conclusion, a stable H2 electrocatalyst that can match the hydrogen oxidation activity obtained with Pt and a membrane with low Br2/Br− permeability are essential to prolong the lifetime of a H2-Br2 fuel cell