Background: Paclitaxel is an effective chemotherapeutic agent for the treatment of cancer patients. Accumulating evidence suggests that circular RNAs (circRNAs) play critical roles in the occurrence and development of human cancers. However, there are few studies on interactions between paclitaxel and circRNAs in hepatocellular carcinoma (HCC). Materials and Methods: Cell counting kit-8 (CCK-8) assay and colony formation assay were conducted to determine cell proliferation. Cell apoptosis was assessed by flow cytometry. The expression levels of circRNA baculoviral IAP repeat-containing 6 (circ-BIRC6), microRNA-877-5p (miR-877-5p), and tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta (YWHAZ) were detected by quantitative real-time polymerase chain reaction (qRT-PCR). The mice xenograft model was established to investigate the roles of circ-BIRC6 and paclitaxel in vivo. The interaction between miR-877-5p and circ-BIRC6 or YWHAZ was predicted by bioinformatics analysis and verified by dual-luciferase reporter assay. Western blot assay was applied for measuring the protein expression of YWHAZ. Results: Paclitaxel suppressed HCC tumorigenesis through decreasing cell proliferation and accelerating apoptosis. Circ-BIRC6 and YWHAZ were upregulated, and miR-877-5p was downregulated in HCC tissues and cells. Paclitaxel treatment inhibited the expression of circ-BIRC6 and YWHAZ while promoted the expression of miR-877-5p. Circ-BIRC6 overexpression or miR-877-5p interference reversed the inhibitory effect of paclitaxel on HCC tumorigenesis. Moreover, miR-877-5p could specially bind to YWHAZ, and its knockdown abated the suppressive effect of circ-BIRC6 depletion on HCC tumorigenesis. Additionally, YWHAZ was identified as a direct target of miR-877-5p. Besides, circ-BIRC6 functioned as a molecular sponge of miR-877-5p to regulate YWHAZ expression. Conclusion: Paclitaxel limited HCC tumorigenesis via modulating circ-BIRC6/miR-877-5p/YWHAZ axis, providing a novel therapeutic approach for the treatment of HCC.
Integrity monitoring of global navigation satellite system (GNSS) is designed to protect against the extremely rare hazardous events characterized by the integrity risk with a very low probability. The traditional integrity risk evaluation is restricted by the non-Gaussian measurement errors and impractical time consumption simultaneously. Based on the extreme value theory, a generalized Pareto distribution (GPD)-based integrity risk evaluation method in the position domain is proposed to estimate the upper bound of integrity risk. In order to account for the GPD modelling error and estimation error, the conservatism of the proposed GPD-based integrity risk evaluation is obtained by imposing the model-driven and data-driven overbounding. The simulation results from four typical heavy-tailed distributions have shown that the conservative and tight bound of integrity risk results can be achieved. Furthermore, the real-world European geostationary navigation overlay service (EGNOS) measurements experiment has shown that the integrity risk evaluation result from the proposed method is at least one-order less than the traditional evaluation method, which is consistent with the official publication.
The periodic noise exists in BeiDou navigation satellite system (BDS) clock offsets. As a commonly used satellite clock prediction model, the spectral analysis model (SAM) typically detects and identifies the periodic terms by the Fast Fourier transform (FFT) according to long-term clock offset series. The FFT makes an aggregate assessment in frequency domain but cannot characterize the periodic noise in a time domain. Due to space environment changes, temperature variations, and various disturbances, the periodic noise is time-varying, and the spectral peaks vary over time, which will affect the prediction accuracy of the SAM. In this paper, we investigate the periodic noise and its variations present in BDS clock offsets, and improve the clock prediction model by considering the periodic variations. The periodic noise and its variations over time are analyzed and quantified by short time Fourier transform (STFT). The results show that both the amplitude and frequency of the main periodic term in BDS clock offsets vary with time. To minimize the impact of periodic variations on clock prediction, a time frequency analysis model (TFAM) based on STFT is constructed, in which the periodic term can be quantified and compensated accurately. The experiment results show that both the fitting and prediction accuracy of TFAM are better than SAM. Compared with SAM, the average improvement of the prediction accuracy using TFAM of the 6 h, 12 h, 18 h and 24 h is in the range of 6.4% to 10% for the GNSS Research Center of Wuhan University (WHU) clock offsets, and 11.1% to 14.4% for the Geo Forschungs Zentrum (GFZ) clock offsets. For the satellites C06, C14, and C32 with marked periodic variations, the prediction accuracy is improved by 26.7%, 16.2%, and 16.3% for WHU clock offsets, and 29.8%, 16.0%, 21.0%, and 9.0% of C06, C14, C28, and C32 for GFZ clock offsets.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.