Oleanolic acid (OA) is reported to possess antihypertensive activity via the regulation of lipid metabolism; however, the mechanisms underlying lipid regulation by OA are yet to be fully elucidated. The aim of the present study was to evaluate the mechanisms via which OA regulates lipid metabolism in spontaneously hypertensive rats (SHRs) via ultra-performance liquid chromatography-quadrupole/Orbitrap-mass spectrometry (MS)-based lipidomics analysis. SHRs were treated with OA (1.08 mg/kg) for 4 weeks. The liver tissues were excised, homogenized in dichloromethane and centrifuged, and subsequently the supernatant layer was collected and concentrated under vacuum to dryness. The dichloromethane extract was subjected to MS analysis and database searching, and comparison of standards was performed to identify potential biomarkers. Partial least squares-discriminant analysis performed on the liver lipidome revealed a total of 14 endogenous metabolites that were significantly changed in the SHR model group (SH group) compared with Wistar Kyoto rats [normal control (NC group)], including glycerophospholipids, sphingolipids and glycerides. Heatmaps revealed that the liver lipid profiles in the OA group were clustered more closely compared with those observed in the NC group, indicating that the antihypertensive effect of OA was mediated via regulation of liver lipid metabolites. It was observed that the protein levels of secretory phospholipase A 2 (sPLA 2 ) and fatty acid synthase (FAS) were increased in the SH group compared with the NC group. In addition, the levels of lysophosphatidylcholine and triglycerides in the liver were elevated, whereas the levels of low-density lipoprotein cholesterol and high-density lipoprotein cholesterol were reduced in the SH group. Upon treatment with OA, the mRNA and protein levels of PLA 2 and FAS were observed to be downregulated. Collectively, the present study indicated that the antihypertensive activity of OA was mediated via downregulation of sPLA 2 and FAS in SHRs, and that treatment with OA resulted in significant improvements in blood pressure and associated abnormalities in the lipid metabolites.

High-quality traffic flow generation is the core module in building simulators for autonomous driving. However, the majority of available simulators are incapable of replicating traffic patterns that accurately reflect the various features of real-world data while also simulating human-like reactive responses to the tested autopilot driving strategies. Taking one step forward to addressing such a problem, we propose Realistic Interactive TrAffic flow (RITA) as an integrated component of existing driving simulators to provide high-quality traffic flow for the evaluation and optimization of the tested driving strategies. RITA is developed with fidelity, diversity, and controllability in consideration, and consists of two core modules called RITABackend and RITAKit. RITABackend is built to support vehicle-wise control and provide traffic generation models from real-world datasets, while RITAKit is developed with easy-to-use interfaces for controllable traffic generation via RITABackend. We demonstrate RITA's capacity to create diversified and high-fidelity traffic simulations in several highly interactive highway scenarios. The experimental findings demonstrate that our produced RITA traffic flows meet all three design goals, hence enhancing the completeness of driving strategy evaluation. Moreover, we showcase the possibility for further improvement of baseline strategies through online fine-tuning with RITA traffic flows.