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Epithelial sodium channels (ENaC) are part of a complex network of interacting biochemical pathways and as such are involved in several disease states. Dependent on site and type of mutation, gain- or loss-of-function generated symptoms occur which span from asymptomatic to life-threatening disorders such as Liddle syndrome, cystic fibrosis or generalized pseudohypoaldosteronism type 1. Variants of ENaC which are implicated in disease assist further understanding of their molecular mechanisms in order to create models for specific pharmacological targeting. Identification and characterization of ENaC modifiers not only furthers our basic understanding of how these regulatory processes interact, but also enables discovery of new therapeutic targets for the disease conditions caused by ENaC dysfunction. Numerous test compounds have revealed encouraging results in vitro and in animal models but less in clinical settings. The EMA- and FDA-designated orphan drug solnatide is currently being tested in phase 2 clinical trials in the setting of acute respiratory distress syndrome, and the NOX1/ NOX4 inhibitor setanaxib is undergoing clinical phase 2 and 3 trials for therapy of primary biliary cholangitis, liver stiffness, and carcinoma. The established ENaC blocker amiloride is mainly used as an add-on drug in the therapy of resistant hypertension and is being studied in ongoing clinical phase 3 and 4 trials for special applications. This review focuses on discussing some recent developments in the search for novel therapeutic agents.

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Behavioral Sciences, Free Full-Text

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Intertidal macroalgal habitats are major components of temperate coastal ecosystems. Their distribution was studied using field sampling and hyperspectral remote mapping on a rocky shore of Porspoder (western Brittany, France). Covers of both dominating macroalgae and the sessile fauna were characterized in situ at low tide in 24 sampling spots, according to four bathymetric levels. A zone of ca. 17,000 m2 was characterized using a drone equipped with a hyperspectral camera. Macroalgae were identified by image processing using two classification methods to assess the representativeness of spectral classes. Finally, a comparison of the remote imaging data to the field sampling data was conducted. Seven seaweed classes were distinguished by hyperspectral pictures, including five different species of Fucales. The maximum likelihood (MLC) and spectral angle mapper (SAM) were both trained using image-derived spectra. MLC was more accurate to classify the main dominating species (Overall Accuracy (OA) 95.1%) than SAM (OA 87.9%) at a site scale. However, at sampling points scale, the results depend on the bathymetric level. This study evidenced the efficiency and accuracy of hyperspectral remote sensing to evaluate the distribution of dominating intertidal seaweed species and the potential for a combined field/remote approach to assess the ecological state of macroalgal communities.

Remote Sensing, Free Full-Text

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The global customer experience management market size was valued at USD 10.65 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 15.4% from 2023 to 2030

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