COVID‐19 may lead to a sharp decline in blood oxygen, can cause sudden changes in the fetal intrauterine environment, and could possibly result in neonatal death.
Aluminum (Al)-induced apoptosis is considered as the major cause of its neurotoxicity. Folic acid possesses neuroprotective function by preventing neural cell apoptosis. microRNAs (miRNAs) are important regulators of gene expression participating in cellular processes. As a key component of the miR-17-92 cluster, miR-19 is implicated in regulating apoptotic process, while its role in the neuroprotective effect of folic acid has not been investigated. The present study aimed to investigate the potential involvement and function of miR-19 in the protective action of folic acid against Al-induced neural cell apoptosis. Human SH-SY5Y cells were treated with Al-maltolate (Al-malt) in the presence or absence of folic acid. Results showed that Al-malt-induced apoptosis of SH-SY5Y cells was effectively prevented by folic acid. Al-malt suppressed the expression of miR-19a/19b, along with alterations of miR-19 related apoptotic proteins including PTEN, p-AKT, p53, Bax, Bcl-2, caspase 9 and caspase 3; and these effects were ameliorated by folic acid. miR-19 inhibitor alone induced apoptosis of SH-SY5Y cells. Combination treatment of folic acid and miR-19 inhibitor diminished the neuroprotective effect of folic acid. These findings demonstrated that folic acid protected neuronal cells against Al-malt-induced apoptosis by preventing the downregulation of miR-19 and modulation of miR-19 related downstream PTEN/AKT/p53 pathway.
A switching variability index (SVI) constant false alarm rate (CFAR) detector is proposed for improving the detection performance of VI-CFAR detectors in multiple targets backgrounds. When the presence of non-homogeneity in CFAR reference windows is indicated by a VI-CFAR detector, a switching-CFAR detector is introduced to optimize the performance of the VI-CFAR detector in homogeneous, multiple targets and clutter edge backgrounds. The structure and parameters selection method of the SVI-CFAR detector is presented. Comparisons with classic CFAR detectors and recently proposed detectors are also given. Theoretical analysis and simulation results show that SVI-CFAR detector maintains the good performance of the VI-CFAR detector in homogeneous and clutter edge backgrounds, while greatly improving the capacity of anti-multi targets.
A constant false alarm rate (CFAR) target detector in non-homogenous backgrounds is proposed. Based on K-sample Anderson-Darling (AD) tests, the method re-arranges the reference cells by merging homogenous sub-blocks surrounding the cell under test (CUT) into a new reference window to estimate the background statistics. Double partition test, clutter edge refinement and outlier elimination are used as an anti-clutter processor in the proposed Modified AD (MAD) detector. Simulation results show that the proposed MAD test based detector outperforms cell-averaging (CA) CFAR, greatest of (GO) CFAR, smallest of (SO) CFAR, order-statistic (OS) CFAR, variability index (VI) CFAR, and CUT inclusive (CI) CFAR in most non-homogenous situations.
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