MALDI-MS argininyl bufadienolide esters fingerprint from parotoid gland secretions of Rhinella arenarum : age, gender and seasonal variation

In many amphibians, the granular glands can be grouped in special regions forming macroglands. This is the case of toads, characterized by the presence of a pair of parotoid macroglands, strategically located to give protection by poison release in case of attacks. The product secreted consists of a wide variety of chemical compounds including proteins, peptides, biogenic amines, toxic steroidal bufadienolides, and various alkaloids, depending on the species. In this work, using Rhinella arenarum, we have performed, for the first time, the matrix assisted-ultraviolet laser desorption/ionization mass spectrometry and tandem mass spectrometry characterization of the components of the secretion used as crude material, just suspended in MeOH (or MeCN). The crude sample as a whole (whole suspension) was spotted on the matrix assisted-ultraviolet laser desorption plate for analysis. Electrospray ionization-Orbitrap was used for cross-checking experiments. The pattern of signals obtained at m/z ranges 600 to 800 and 1200 to 1600 could be assigned as the argininyl bufadienolide esters fingerprint characteristic of female and male. Variation patterns for gender (female, male), age (non-reproductive, reproductive), and season (non-reproductive, reproductive) are described.Fil: Petroselli, Gabriela. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Orgánica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones en Hidratos de Carbono. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones en Hidratos de Carbono; ArgentinaFil: Raices, Marilina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Biodiversidad y Biología Experimental; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; ArgentinaFil: Jungblut, Lucas David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Biodiversidad y Biología Experimental; ArgentinaFil: Pozzi, Andrea Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Biodiversidad y Biología Experimental y Aplicada. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Biodiversidad y Biología Experimental y Aplicada; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Biodiversidad y Biología Experimental; ArgentinaFil: Erra Balsells, Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones en Hidratos de Carbono. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones en Hidratos de Carbono; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Química Orgánica; Argentin

Analysis of the behavior of three digital elevation model correction methods on critical natural scenarios

Abstract Study region The methods explored in this study were tested in two study areas: Italy and Cuba. Study focus Virtually all Digital Elevation Models (DEM) contain flat areas or depression pixels that may be artifacts or actual landscape representations. These features must be removed before any further hydrological application can proceed. Diverse algorithms have been developed for the purpose of correcting these aspects, differing in how they handle the nature of the depressions, as well as the adopted mathematical procedures. In the present work, the behavior of a standard ( Fill ) and two advanced ( TOPAZ and PEM4PIT ) DEM correction methods on three critical natural scenarios is analyzed. Extensive flat areas, abrupt slope changes and large depressions − expressed in terms of: (1) geomorphological changes (elevation, affected area and slope); (2) flow velocity; (3) river network and width functions (WF) − are affected. New hydrological insights for the region Results confirm improved performance of the advanced methods over the standard method for each case study in Italy and Cuba. The analyzed parameters also show that correction processes are strongly influenced by the relief, the size of the predominating depressions and the neighbouring depressions. There is no one method among those compared which works optimally for every type of correction, and given that the majority of basins have diverse topographical conditions, a different approach to the corrections process and its computational procedures is likely needed

The influence of the net rainfall mixed Curve Number – Green Ampt procedure in flood hazard mapping: a case study in Central Italy

A net rainfall estimation procedure, referred to as Curve-Number For Green-Ampt (CN4GA), combining the Soil Conservation Service - Curve Number (SCS-CN) method and the Green and Ampt (GA) infiltration equation was recently developed, aiming to distribute at subdaily time resolution the information provided by the SCS-CN method. The initial abstraction and the total volume of rainfall provided by the SCS-CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation, whereas the GA infiltration model distributes the total volume of the rainfall excess provided by the SCS-CN method. In this study we evaluate the proposed procedure with reference to a real case comparing the flood mapping obtained applying the event-based approach for two different net rainfall scenarios: the proposed CN4GA and the common SCS-CN. Results underline that the net rainfall estimation step can affect the final flood mapping result

Optical sensing for stream flow observations: a review

Images are revolutionizing the way we sense and characterize the environment by offering higher spatial and temporal coverage in ungauged environments at competitive costs. In this review, we illustrate the major image-based approaches that have been lately adopted within the hydrological research community. Although many among such methodologies have been developed some decades ago, recent efforts have been devoted to their transition from laboratories to operational outdoor settings. Sample applications of image-based techniques include flow discharge estimation in riverine environments, clogging dynamics in irrigation systems, and flow diagnostics in engineering infrastructures. The potential of such image-based approaches towards fully remote observations is also illustrated through a simple experiment with an unmanned aerial vehicle

Riparian vegetation as a marker for bankfull and management dischargeevaluation: The case study of Rio Torbido river basin (central Italy)

Bankfull discharge estimation is a crucial step in river basin management. Such evaluation can be carried out using hydrological and hydraulic modelling to estimate flow-depths, flow velocities and flood prone areas related to a specific return period. However, different methodological approaches are described in the scientific literature. Such approaches are typically based either on the assumption that the bankfull discharge corresponds to a narrow range of return periods, or on the correlation to the river geomorphological or local descriptors, such as vegetation. In this study, we used high-resolution topographic data and a combined hydrological-hydraulic modelling approach in order to estimate bankfull discharge in the ungauged basin of Rio Torbido River (Central Italy). The field survey of plant species made it possible to investigate the link between the riparian areas and the bankfull discharge. Our results were in line with previous studies and showed a promising agreement between the results of the hydraulic modelling and the plant species present in the investigated river cross sections. The plant species position could be indeed used for a preliminary delineation of the riparian areas to be verified more deeply with the hydrological-hydraulic approach

Feature importance measures to dissect the role of sub-basins in shaping the catchment hydrological response: a proof of concept

Understanding the response of a catchment is a crucial problem in hydrology, with a variety of practical and theoretical implications. Dissecting the role of sub-basins is helpful both for advancing current knowledge of physical processes and for improving the implementation of simulation or forecast models. In this context, recent advancements in sensitivity analysis tools could be worthwhile for bringing out hidden dynamics otherwise not easy to distinguish in complex data driven investigations. In the present work seven feature importance measures are described and tested in a specific and simplified proof of concept case study. In practice, simulated runoff time series are generated for a watershed and its inner 15 sub-basins. A machine learning tool is calibrated using the sub-basins time series for forecasting the watershed runoff. Importance measures are applied on such synthetic hydrological scenario with the aim to investigate the role of each sub-basin in shaping the overall catchment response. This proof of concept offers a simplified representation of the complex dynamics of catchment response. The interesting result is that the discharge at the catchment outlet depends mainly on 3 sub-basins that are consistently identified by alternative sensitivity measures. The proposed approach can be extended to real applications, providing useful insights on the role of each sub-basin also analyzing more complex scenarios