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TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2

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...

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Detalles Bibliográficos
Autores principales: Ji, Xiaoyang, Tan, Wenting, Zhang, Chunming, Zhai, Yubo, Hsueh, Yiching, Zhang, Zhonghai, Zhang, Chunli, Lu, Yanqiu, Duan, Bo, Tan, Guangming, Na, Renhua, Deng, Guohong, Niu, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7404951/
https://www.ncbi.nlm.nih.gov/pubmed/32657473
http://dx.doi.org/10.1002/ddr.21717
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author Ji, Xiaoyang
Tan, Wenting
Zhang, Chunming
Zhai, Yubo
Hsueh, Yiching
Zhang, Zhonghai
Zhang, Chunli
Lu, Yanqiu
Duan, Bo
Tan, Guangming
Na, Renhua
Deng, Guohong
Niu, Gang
author_facet Ji, Xiaoyang
Tan, Wenting
Zhang, Chunming
Zhai, Yubo
Hsueh, Yiching
Zhang, Zhonghai
Zhang, Chunli
Lu, Yanqiu
Duan, Bo
Tan, Guangming
Na, Renhua
Deng, Guohong
Niu, Gang
author_sort Ji, Xiaoyang
collection PubMed
description 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.
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spelling pubmed-74049512020-08-05 TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2 Ji, Xiaoyang Tan, Wenting Zhang, Chunming Zhai, Yubo Hsueh, Yiching Zhang, Zhonghai Zhang, Chunli Lu, Yanqiu Duan, Bo Tan, Guangming Na, Renhua Deng, Guohong Niu, Gang Drug Dev Res Research Articles 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. John Wiley & Sons, Inc. 2020-07-13 2020-12 /pmc/articles/PMC7404951/ /pubmed/32657473 http://dx.doi.org/10.1002/ddr.21717 Text en © 2020 The Authors. Drug Development Research published by Wiley Periodicals, LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Ji, Xiaoyang
Tan, Wenting
Zhang, Chunming
Zhai, Yubo
Hsueh, Yiching
Zhang, Zhonghai
Zhang, Chunli
Lu, Yanqiu
Duan, Bo
Tan, Guangming
Na, Renhua
Deng, Guohong
Niu, Gang
TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2
title TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2
title_full TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2
title_fullStr TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2
title_full_unstemmed TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2
title_short TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2
title_sort twirls, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ace2
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7404951/
https://www.ncbi.nlm.nih.gov/pubmed/32657473
http://dx.doi.org/10.1002/ddr.21717
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