Expression of Tas1 Taste Receptors in Mammalian Spermatozoa: Functional Role of Tas1r1 in Regulating Basal Ca2+ and cAMP Concentrations in Spermatozoa

Background: During their transit through the female genital tract, sperm have to recognize and discriminate numerous chemical compounds. However, our current knowledge of the molecular identity of appropriate chemosensory receptor proteins in sperm is still rudimentary. Considering that members of the Tas1r family of taste receptors are able to discriminate between a broad diversity of hydrophilic chemosensory substances, the expression of taste receptors in mammalian spermatozoa was examined. Methodology/Principal Findings: The present manuscript documents that Tas1r1 and Tas1r3, which form the functional receptor for monosodium glutamate (umami) in taste buds on the tongue, are expressed in murine and human spermatozoa, where their localization is restricted to distinct segments of the flagellum and the acrosomal cap of the sperm head. Employing a Tas1r1-deficient mCherry reporter mouse strain, we found that Tas1r1 gene deletion resulted in spermatogenic abnormalities. In addition, a significant increase in spontaneous acrosomal reaction was observed in Tas1r1 null mutant sperm whereas acrosomal secretion triggered by isolated zona pellucida or the Ca2+ ionophore A23187 was not different from wild-type spermatozoa. Remarkably, cytosolic Ca2+ levels in freshly isolated Tas1r1-deficient sperm were significantly higher compared to wild-type cells. Moreover, a significantly higher basal cAMP concentration was detected in freshly isolated Tas1r1-deficient epididymal spermatozoa, whereas upon inhibition of phosphodiesterase or sperm capacitation, the amount of cAMP was not different between both genotypes. Conclusions/Significance: Since Ca2+ and cAMP control fundamental processes during the sequential process of fertilization, we propose that the identified taste receptors and coupled signaling cascades keep sperm in a chronically quiescent state until they arrive in the vicinity of the egg - either by constitutive receptor activity and/or by tonic receptor activation by gradients of diverse chemical compounds in different compartments of the female reproductive tract

Automated identification of potential snow avalanche release areas based on digital elevation models

The identification of snow avalanche release areas is a very difficult task. The release mechanism of snow avalanches depends on many different terrain, meteorological, snowpack and triggering parameters and their interactions, which are very difficult to assess. In many alpine regions such as the Indian Himalaya, nearly no information on avalanche release areas exists mainly due to the very rough and poorly accessible terrain, the vast size of the region and the lack of avalanche records. However avalanche release information is urgently required for numerical simulation of avalanche events to plan mitigation measures, for hazard mapping and to secure important roads. The Rohtang tunnel access road near Manali, Himachal Pradesh, India, is such an example. By far the most reliable way to identify avalanche release areas is using historic avalanche records and field investigations accomplished by avalanche experts in the formation zones. But both methods are not feasible for this area due to the rough terrain, its vast extent and lack of time. Therefore, we develop an operational, easy-to-use automated potential release area (PRA) detection tool in Python/ArcGIS which uses high spatial resolution digital elevation models (DEMs) and forest cover information derived from airborne remote sensing instruments as input. Such instruments can acquire spatially continuous data even over inaccessible terrain and cover large areas. We validate our tool using a database of historic avalanches acquired over 56 yr in the neighborhood of Davos, Switzerland, and apply this method for the avalanche tracks along the Rohtang tunnel access road. This tool, used by avalanche experts, delivers valuable input to identify focus areas for more-detailed investigations on avalanche release areas in remote regions such as the Indian Himalaya and is a precondition for large-scale avalanche hazard mapping

Influence of snow depth distribution on surface roughness in alpine terrain: A multi-scale approach

In alpine terrain, the snow-covered winter surface deviates from its underlying summer terrain due to the progressive smoothing caused by snow accumulation. Terrain smoothing is believed to be an important factor in avalanche formation and avalanche dynamics, and it affects surface heat transfer, energy balance as well as snow depth distribution. To assess the effect of snow on terrain, we use an adequate roughness definition. We developed a method to quantify terrain smoothing by combining roughness calculations of snow surfaces and their corresponding underlying terrain with snow depth measurements. To this end, elevation models of winter and summer terrain in three selected alpine basins in the Swiss Alps characterized by low, medium and high terrain roughness were derived from high-resolution measurements performed by airborne and terrestrial lidar. The preliminary results in the selected basins reveal that, at basin scale, terrain smoothing depends not only on mean snow depth in the basin but also on its variability. The multi-temporal analysis over three winter seasons in one basin suggests that terrain smoothing can be modelled as a function of mean snow depth and its standard deviation using a power law. However, a relationship between terrain smoothing and snow depth was not found at pixel scale. Further, we show that snow surface roughness is to some extent persistent, even in-between winter seasons. Those persistent patterns might be very useful to improve the representation of a winter terrain without modelling of the snow cover distribution. This can for example improve avalanche release area definition and, in the long term, natural hazard management strategies

Slab avalanche release area estimation: a new GIS tool

Location and extent of avalanche starting zones are of crucial importance to correctly estimate the potential danger that avalanches pose to roads, railways or other infrastructure. Presently, release area assessment is based on terrain analysis combined with expert judgment. Tools for the automatic definition of release areas are scarce and exclusively based on parameters derived from summer topography, such as slope and curvature. This leads to several limitations concerning the performance of such algorithms. Foremost, they neglect the smoothing effect of the snow cover on terrain morphology. Winter terrain often considerably deviates from its underlying summer terrain, thus changing potential release area size and location of surface slab avalanches. Hence, we present a new GIS based tool which estimates potential release areas by association of traditional contributory variables, such as slope and forest cover with variables particularly related to snow cover influence on topography. We introduce a scale dependent roughness parameter and a wind shelter parameter accounting for varying winter topography and snow deposition patterns with increasing snow depth. Further, uncertainty in the definition of the parameters is accounted for by using a fuzzy logic classification approach. This approach is especially useful for defining release area scenarios e.g. depending on snow depth, which is not possible with existing tools

Potential slab avalanche release area identification from estimated winter terrain: a multi-scale, fuzzy logic approach

Avalanche hazard assessment requires a very precise estimation of the release area, which still depends, to a large extent, on expert judgement of avalanche specialists. Therefore, a new algorithm for automated identification of potential avalanche release areas was developed. It overcomes some of the limitations of previous tools, which are currently not often applied in hazard mitigation practice. By introducing a multi-scale roughness parameter, fine-scale topography and its attenuation under snow influence is captured. This allows the assessment of snow influence on terrain morphology and, consequently, potential release area size and location. The integration of a wind shelter index enables the user to define release area scenarios as a function of the prevailing wind direction or single storm events. A case study illustrates the practical usefulness of this approach for the definition of release area scenarios under varying snow cover and wind conditions. A validation with historical data demonstrated an improved estimation of avalanche release areas. Our method outperforms a slope-based approach, in particular for more frequent avalanches; however, the application of the algorithm as a forecasting tool remains limited, as snowpack stability is not integrated. Future research activity should therefore focus on the coupling of the algorithm with snowpack conditions