TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2 (vol 81, pg 1004, 2020)

doi:10.1002/ddr.21817

	TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2 (vol 81, pg 1004, 2020)
	Niu, Gang 1,2,3,4,5,6
	2021-04-02
发表期刊	DRUG DEVELOPMENT RESEARCH
ISSN	0272-4391
页码	1
摘要	Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the "SARS-CoV-2" should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying viruses and hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly if our scientific understanding is also limited, which further lowers the information processing efficiency. We present TWIRLS (Topic-wise inference engine of massive biomedical literatures), a method that can deal with various scientific problems, such as liver cancer, acute myeloid leukemia, and so forth, which can automatically acquire, organize, and classify information. Additionally, this information can be combined with independent functional data sources to build an inference system via a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. Using TWIRLS, we automatically analyzed more than three million words in more than 14,000 literature articles in only 4 hr. We found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in host pathological changes on binding to the coronavirus after infection. On triggering functional changes in ACE2/AT2R, the cytokine homeostasis regulation axis becomes imbalanced via the Renin-Angiotensin System and IP-10, leading to a cytokine storm. Through a preliminary analysis of blood indices of COVID-19 patients with a history of hypertension, we found that non-ARB (Angiotensin II receptor blockers) users had more symptoms of severe illness than ARB users. This suggests ARBs could potentially be used to treat acute lung injury caused by coronavirus infection.
关键词	coronavirus cytokine storm literature mining renin angiotensin system topic inference
DOI	10.1002/ddr.21817
收录类别	SCI
语种	英语
资助项目	Public Library Association Youth Talent Project[17QNP010] ; Chongqing Health Commission COVID-19 Project[2020NCPZX01] ; Shenzhen Science and Technology Planning Project[JCYJ20170817095211560]
WOS研究方向	Pharmacology & Pharmacy
WOS类目	Chemistry, Medicinal ; Pharmacology & Pharmacy
WOS记录号	WOS:000636141800001
出版者	WILEY
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/16820
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Niu, Gang
作者单位	1.Joint Turing Darwin Lab Phil Rivers Technol Ltd, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China 3.Phil Rivers Technol Ltd, Dept Computat Biol, Beijing, Peoples R China 4.Chinese Acad Sci, West Inst Comp Technol, Chongqing, Peoples R China 5.Shenzhen Univ, Nanophoton Res Ctr, Shenzhen Key Lab Microscale Opt Informat Technol, Shenzhen, Guangdong, Peoples R China 6.Shenzhen Univ, Inst Microscale Optoelect, Shenzhen, Guangdong, Peoples R China
推荐引用方式 GB/T 7714	Niu, Gang. TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2 (vol 81, pg 1004, 2020)[J]. DRUG DEVELOPMENT RESEARCH,2021:1.
APA	Niu, Gang.(2021).TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2 (vol 81, pg 1004, 2020).DRUG DEVELOPMENT RESEARCH,1.
MLA	Niu, Gang."TWIRLS, a knowledge-mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2 (vol 81, pg 1004, 2020)".DRUG DEVELOPMENT RESEARCH (2021):1.