Critical illness in COVID-19 is an extreme and clinically homogeneous disease phenotype that we have previously shown1 to be highly efficient for discovery of genetic associations2. Despite the advanced stage of illness at presentation, we have shown that host genetics in patients who are critically ill with COVID-19 can identify immunomodulatory therapies with strong beneficial effects in this group3. Here we analyse 24,202 cases of COVID-19 with critical illness comprising a combination of microarray genotype and whole-genome sequencing data from cases of critical illness in the international GenOMICC (11,440 cases) study, combined with other studies recruiting hospitalized patients with a strong focus on severe and critical disease: ISARIC4C (676 cases) and the SCOURGE consortium (5,934 cases). To put these results in the context of existing work, we conduct a meta-analysis of the new GenOMICC genome-wide association study (GWAS) results with previously published data. We find 49 genome-wide significant associations, of which 16 have not been reported previously. To investigate the therapeutic implications of these findings, we infer the structural consequences of protein-coding variants, and combine our GWAS results with gene expression data using a monocyte transcriptome-wide association study (TWAS) model, as well as gene and protein expression using Mendelian randomization. We identify potentially druggable targets in multiple systems, including inflammatory signalling (JAK1), monocyte–macrophage activation and endothelial permeability (PDE4A), immunometabolism (SLC2A5 and AK5), and host factors required for viral entry and replication (TMPRSS2 and RAB2A).
SUMMARYIn this paper, we discuss a numerical scheme for the Stokes equations in three dimensions. It uses an integral equation formulation and is accelerated by the new version of fast multipole method first introduced by Greengard and Rokhlin in 1997 (Acta Numerica 1997; 6:229-269). The code is parallelized to solve problems of extremely large size. The resulting numerical solver can be applied to Stokes flows in complex geometry and also serves as a building block for solving the Navier-Stokes equations of low to moderate Reynold's numbers.
China has been the forerunner of large-scale membrane bioreactor (MBR) application. Since the first large-scale MBR (≥10 000 m 3 $d -1 ) was put into operation in 2006, the engineering implementation of MBR in China has attained tremendous development. This paper outlines the commercial application of MBR since 2006 and provides a variety of engineering statistical data, covering the fields of municipal wastewater, industrial wastewater, and polluted surface water treatment. The total treatment capacity of MBRs reached 1 Â 10 6 m 3 $d -1 in 2010, and has currently exceeded 4.5 Â 10 6 m 3 $d -1 with~75% of which pertaining to municipal wastewater treatment. The anaerobic/anoxic/aerobic-MBR and its derivative processes have been the most popular in the large-scale municipal application, with the process features and typical ranges of parameters also presented in this paper. For the treatment of various types of industrial wastewater, the configurations of the MBR-based processes are delineated with representative engineering cases. In view of the significance of the cost issue, statistics of capital and operating costs are also provided, including cost structure and energy composition. With continuous stimulation from the environmental stress, political propulsion, and market demand in China, the total treatment capacity is expected to reach 7.5 Â 10 6 m 3 $d -1 by 2015 and a further expansion of the market is foreseeable in the next five years. However, MBR application is facing several challenges, such as the relatively high energy consumption. Judging MBR features and seeking suitable application areas should be of importance for the long-term development of this technology.
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
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.