The degenerin channels, epithelial sodium channels, and acid-sensing ion channels (DEG/ENaC/ASICs) play important roles in sensing mechanical stimuli, regulating salt homeostasis, or responding to acidification in the nervous system. They share a common topology with two transmembrane domains separated by a large extracellular domain and are believed to assemble as homomeric or heteromeric trimers into non-voltage gated, sodiumselective, and amiloride-sensitive ion channels. Amiloride is not the only drug that targets DEG/ENaC/ASICs, however, they are also emerging as a target of nonsteroidal antiinflammatory drugs (NSAIDs) as well as other classes of small molecules. C. elegans has about 30 genes encoding DEG/ENaC/ASIC subunits and thus offers an excellent opportunity to examine variations in sensitivity to small molecules and biophysical properties. Here, we analyzed a subset of the C. elegans DEG/ENaC/ASIC proteins in order to test the hypothesis that individual family members have distinct properties. Toward this goal, we expressed five C. elegans isoforms in Xenopus laevis oocytes (DEGT-1d, DEL-1d, UNC-8d, MEC-10d and MEC-4d) and measured current amplitude, selectivity among monovalent cations, sensitivity to amiloride and its analogs, and sensitivity to NSAIDs. Of these five proteins, only DEGT-1d, UNC-8d, and MEC-4d form homomeric channels. Unlike MEC-4d and UNC-8d, DEGT-1d channels were insensitive to amiloride and its analogs and more permeable to K + than to Na + . As reported for rat ASIC1a, NSAIDs inhibit DEGT-1d and UNC-8d. Unexpectedly, MEC-4d was strongly potentiated by NSAIDs, an effect that was decreased by mutations in the extracellular domain that affect inhibition of rat ASIC1a. Collectively, these findings reveal that not all DEG/ENaC/ASIC channels are amiloride-sensitive and sodium-selective and that NSAIDs can both inhibit and potentiate these channels.The degenerin channels, epithelial sodium channels, and acid-sensing ion channels (DEG/ENaC/ASICs) are present in most, if not all metazoans and expressed in diverse tissues, including the epithelia of several organs and in the central and peripheral nervous systems (Eastwood and Goodman, 2012; Kellenberger and Schild, 2002). These channels vary in how they are activated in vivo, although the activation mechanisms are not yet known for all family members. At least two DEG proteins are known to be mechanosensitive, ENaCs are constitutively active and can be regulated by shear stress, and ASICs are activated by proton binding (Eastwood and Goodman, 2012). The DEG and ENaC proteins were the initial members of this superfamily. The DEGs were identified in C. elegans by virtue of their role in mechanosensation and neuronal degeneration (Chalfie and Wolinsky, 1990; Driscoll and Chalfie, 1991; Huang and Chalfie, 1994). The ENaCs were identified via expression of rodent cRNAs in Xenopus oocytes followed by functional screening (Canessa et al., 1995). The proteins that form acid-sensing ion channels (ASICs) were also identified in the 1990s (Waldman...

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Although landslides occur over a broad range of lithologies, climatologies, hydrological regimes, and land use types (Kirschbaum et al., 2015), the majority are precipitation-triggered (Petley et al., 2005). However, for most precipitation-triggered landslides, other complex atmospheric, surface, and subsurface conditions also play a role in predisposing the slope to failure by increasing the effects of downgradient forces and/or reducing the strength of the underlying slope (Sidle & Ochiai, 2006;Terzaghi, 1950). Isolating the effect of precipitation from these confounding factors is thus essential both for enhancing fundamental understanding of landslides and for evaluating the impact of climate change on slope failure.A principal way that climate change is likely to impact landslide hazard is by intensifying precipitation

Estimating hydrological properties and quantifying their uncertainty from observed measurements is vital for groundwater exploration and exploitation decision-making processes. Bayesian inversion is now commonly applied to obtain posterior distributions (Tarantola, 2005). Two popular Bayesian inversion approaches are (a) the Markov chain Monte Carlo (MCMC) method, (b) the Monte Carlo ensemble method.Many Markov chain Monte Carlo (MCMC) methods (Brooks et al., 2011) have been well studied to solve Bayesian inversion problems in hydrology and other subsurface reservoirs: