JOURNAL ARTICLE

ON-BOARD CHANGE DETECTION WITH NEURAL NETWORKS

Abstract

The metabolic syndrome could be induced by high fat diet, leading to cardiovascular diseases, such as myocardial damage. Inflammation response and oxidative stress have been reported to be involved in high fat-induced heart injury, and the molecular mechanism is not fully understood. The NOD-like protein family member, NLRC5, could interact with IKKα to inhibit IKK complex activation. In our study, high fat diet-feeding mice showed cardiac fibrosis, inflammation and oxidative stress through collagen accumulation, TLR4/NF-κB and MAPKs signaling pathways activation. NLRC5 knockout mice fed with high fat showed accelerated fibrosis and inflammation response by promoting α-SMA, Collagen I, Collagen III, TLR4/MyD88, phosphorylated IKKα, IκBα and NF-κB expression. And no effect on oxidative stress was observed in wild type and NLRC5-deficiency samples in in vivo studies. Moreover, NLRC5-knockout and -knockdown cardiac muscle cells challenged with LPS also exhibited aggravated fibrosis levels and inflammatory response without any influences on ROS production in in vitro studies. In conclusion, the findings indicated that NLRC5 showed important effects on high fat-induced heart injury via fibrosis and inflammation modulation, providing an essential target for improving myocardial damage induced by high fat diet.

Keywords:
Artificial neural network Computer science Artificial intelligence Set (abstract data type) On board Data set Change detection Data mining Component (thermodynamics) Pattern recognition (psychology) Machine learning Remote sensing

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Citation History

Topics

Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Neural Networks and Applications
Physical Sciences →  Computer Science →  Artificial Intelligence
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence

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