Human Identical Sequences of SARS-CoV-2 Promote Clinical Progression of COVID-19 by Upregulating Hyaluronan via NamiRNA-Enhancer Network

The COVID-19 pandemic is a widespread and deadly public health crisis. The pathogen SARS-CoV-2 replicates in the lower respiratory tract and causes fatal pneumonia. Although tremendous efforts have been put into investigating the pathogeny of SARS-CoV-2, the underlying mechanism of how SARS-CoV-2 interacts with its host is largely unexplored. Here, by comparing the genomic sequences of SARS-CoV-2 and human, we identified five fully conserved elements in SARS-CoV-2 genome, which were termed as "human identical sequences (HIS)". HIS are also recognized in both SARS-CoV and MERS-CoV genome. Meanwhile, HIS-SARS-CoV-2 are highly conserved in the primate. Mechanically, HIS-SARS-CoV-2, behaving as virus-derived miRNAs, directly target to the human genomic loci and further interact with host enhancers to activate the expression of adjacent and distant genes, including cytokines gene and angiotensin converting enzyme II (ACE2), a well-known cell entry receptor of SARS-CoV-2, and hyaluronan synthase 2 (HAS2), which further increases hyaluronan formation. Noteworthily, hyaluronan level in plasma of COVID-19 patients is tightly correlated with severity and high risk for acute respiratory distress syndrome (ARDS) and may act as a predictor for the progression of COVID-19. HIS antagomirs, which downregulate hyaluronan level effectively, and 4-Methylumbelliferone (MU), an inhibitor of hyaluronan synthesis, are potential drugs to relieve the ARDS related ground-glass pattern in lung for COVID-19 treatment. Our results revealed that unprecedented HIS elements of SARS-CoV-2 contribute to the cytokine storm and ARDS in COVID-19 patients. Thus, blocking HIS-involved activating processes or hyaluronan synthesis directly by 4-MU may be effective strategies to alleviate COVID-19 progression.

AP-IO: asynchronous pipeline I/O for hiding periodic output cost in CFD simulation.

Computational fluid dynamics (CFD) simulation often needs to periodically output intermediate results to files in the form of snapshots for visualization or restart, which seriously impacts the performance. In this paper, we present asynchronous pipeline I/O (AP-IO) optimization scheme for the periodically snapshot output on the basis of asynchronous I/O and CFD application characteristics. In AP-IO, dedicated background I/O processes or threads are in charge of handling the file write in pipeline mode, therefore the write overhead can be hidden with more calculation than classic asynchronous I/O. We design the framework of AP-IO and implement it in OpenFOAM, providing CFD users with a user-friendly interface. Experimental results on the Tianhe-2 supercomputer demonstrate that AP-IO can achieve a good optimization effect for the periodical snapshot output in CFD application, and the effect is especially better for massively parallel CFD simulations, which can reduce the total execution time up to about 40%.