Formononetin (FMNT), a flavonoid identified from the Chinese herb Astragalus membranaceus, possesses anti-inflammatory or anti-oxidative properties in different human diseases. This study aims to comprehensively elucidate the function of FMNT in atherosclerosis and its underlying mechanisms. Online public databases were used to identify the drug-disease targets. Proteinprotein interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were applied to explore the potential targets and signaling pathways involved in FMNT against atherosclerosis. Human umbilical vein endothelial cells (HUVECs) were exposed to oxidized low-density lipoprotein (ox-LDL) to construct an atherosclerosis cell model in vitro. Endothelial cell function was assessed via examining cell proliferation, inflammatory factors, oxidative markers, reactive oxygen species (ROS), and apoptosis. Western blot was performed to detect the expression of cyclooxygenase-2 (COX-2), endothelial nitric oxide synthase (eNOS), cleaved caspase-3, and peroxisome proliferator-activated receptor-γ (PPAR-γ). A total of 39 overlapping target genes of FMNT and atherosclerosis were identified. Through the PPI network analysis, 14 hub genes were screened and found to be closely relevant to inflammation, oxidative stress, and apoptosis. Results of KEGG pathway assays indicated that lots of targets were enriched in PPAR signaling. Functionally, FMNT could protect against ox-LDL-induced inflammatory reaction, oxidative stress, and apoptosis in HUVECs. Moreover, FMNT attenuated ox-LDL-mediated inactivation of PPAR-γ signaling. GW9662, a PPAR-γ antagonist, reversed the inhibitory effect of FMNT on ox-LDL-induced endothelial injury. In conclusion, FMNT alleviates ox-LDL-induced endothelial injury in HUVECs by stimulating PPAR-γ signaling, providing a theoretical basis for employing FMNT as a potential drug to combat atherosclerosis.

Corner and junction detection is an important preprocessing step in image registration, data fusion, object recognition, and many other tasks. This work deals with corner and junction detection of characteristic features of the structure resulting from cross-pattern projection. The ultimate aim is to adapt the positions and orientation of the crosspattern projections to what has been observed. The use of this projected light pattern in the framework of active vision allows us to identify certain points of interest on 3-D objects, to directly acquire a synthesis, which thus permits simplified detection, measurement, recognition, or tracking. We present detection methods for corners and junctions in the context of Hough transform detection.