Transient receptor potential canonical (TRPC) Ca 2+ -permeant channels, especially TRPC3, are increasingly implicated in cardiorenal diseases. We studied the possible role of fibroblast TRPC3 in the development of renal fibrosis. In vitro, a macromolecular complex formed by TRPC1/TRPC3/TRPC6 existed in isolated cultured rat renal fibroblasts. However, specific blockade of TRPC3 with the pharmacologic inhibitor pyr3 was sufficient to inhibit both angiotensin II-and 1-oleoyl-2-acetyl-sn-glycerol-induced Ca 2+ entry in these cells, which was detected by fura-2 Ca 2+ imaging. TRPC3 blockade or Ca 2+ removal inhibited fibroblast proliferation and myofibroblast differentiation by suppressing the phosphorylation of extracellular signalregulated kinase (ERK1/2). In addition, pyr3 inhibited fibrosis and inflammation-associated markers in a noncytotoxic manner. Furthermore, TRPC3 knockdown by siRNA confirmed these pharmacologic findings. In adult male Wistar rats or wild-type mice subjected to unilateral ureteral obstruction, TRPC3 expression increased in the fibroblasts of obstructed kidneys and was associated with increased Ca 2+ entry, ERK1/2 phosphorylation, and fibroblast proliferation. Both TRPC3 blockade in rats and TRPC3 knockout in mice inhibited ERK1/2 phosphorylation and fibroblast activation as well as myofibroblast differentiation and extracellular matrix remodeling in obstructed kidneys, thus ameliorating tubulointerstitial damage and renal fibrosis. In conclusion, TRPC3 channels are present in renal fibroblasts and control fibroblast proliferation, differentiation, and activation through Ca 2+ -mediated ERK signaling. TRPC3 channels might constitute important therapeutic targets for improving renal remodeling in kidney disease.

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The ADS-B is an air traffic monitoring technology based on broadcasting messages to transfer information in between aircraft as well as between aircraft and ground stations. It was created to increase the surveillance coverage as well as reduce the cost of operation relative to traditional radars. However the messages used to communicate under the ADS-B protocol are not encrypted and thus are prone to false data injection attacks which can, for example, modify the values of the messages' components. In this paper, a supervised deep learning strategy is designed to detect attacks that modify components of ADS-B messages such as altitude, ground speed, trajectory, latitude and longitude. A false data generator based on a domain specific language was used to attack ADS-B data and obtain a dataset containing both normal and anomalous data for supervised learning. The detection performance of two types of attacks were evaluated: gradual attacks and waypoints attacks which diverge aircraft trajectories to pass through specific waypoints. The experimental results show that the proposed supervised deep learning strategy is able to recall on average 99% of anomalies in ADS-B messages, mainly property modification attacks.