Loading…

Comprehensive analysis of lncRNA‐TF crosstalks and identification of prognostic regulatory feedback loops of glioblastoma using lncRNA/TF‐mediated ceRNA network

Glioblastoma (GBM) has become the most aggressive primary brain tumor in the world. Patients with GBM usually have a poor prognosis. The median survival times of GBM patients retain less than 2 years. Thus, it is urgent to investigate the molecular mechanism of GBM. Recently, studies have demonstrat...

Full description

Saved in:
Bibliographic Details
Published in:Journal of cellular biochemistry 2020-01, Vol.121 (1), p.755-767
Main Authors: Ji, Yang, Gu, Yaqin, Hong, Shuai, Yu, Bo, Zhang, Jian‐Hua, Liu, Jin‐Na
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3
cites cdi_FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3
container_end_page 767
container_issue 1
container_start_page 755
container_title Journal of cellular biochemistry
container_volume 121
creator Ji, Yang
Gu, Yaqin
Hong, Shuai
Yu, Bo
Zhang, Jian‐Hua
Liu, Jin‐Na
description Glioblastoma (GBM) has become the most aggressive primary brain tumor in the world. Patients with GBM usually have a poor prognosis. The median survival times of GBM patients retain less than 2 years. Thus, it is urgent to investigate the molecular mechanism of GBM. Recently, studies have demonstrated that transcription factors (TFs) participate in cancer pathology by regulating long noncoding RNAs (lncRNAs). However, the functional and regulatory roles of TF‐lncRNA crosstalks are still unclear. In this study, we constructed a global lncRNA‐TF network (GLTN) based on competing endogenous RNA. As a result, some topological features of GLTN were identified. A known GBM lncRNA MCM3AP‐AS1 showed multiple central topological features in GLTN. Furthermore, we identified hub genes and extracted the hub‐hub pairs from GLTN to form a hub associated lncRNA‐TF network (HALTN). Results showed that a risk model combined with multiple hubs had a significant effect on prognosis. Additionally, we performed module searching and two functional modules from HALTN were identified, which were confirmed as risk factors of GBM. More importantly, we also identified some core lncRNA‐TF crosstalks that might form feedback loops to control the biological processes in GBM. Our results demonstrated that the synergistic, competitive lncRNA‐TF crosstalks played an important role in pathological processes of GBM, and had strong effect on prognosis. All these results can help us to uncover the molecular mechanism and provide a new therapeutic target for GBM. 1. A global view of long noncoding RNA transcription factor (lncRNA‐TF) crosstalks was constructed for glioblastoma (GBM) investigation. 2. Integration of competing endogenous RNA (ceRNA) crosstalks and TF‐DNA binding, some core lncRNA‐TF feedback loops with strong prognostic effect were identified.
doi_str_mv 10.1002/jcb.29321
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2283988478</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2317528963</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3</originalsourceid><addsrcrecordid>eNp10cuO0zAUBmALgZgysOAFkCU2sMjUl6S2l0NFuWgEEirryHGOi1snLrbDqDsegYfgyXgSPG1hgcTKkvXpP_b5EXpKyRUlhM23prtiijN6D80oUaKqF3V9H82I4KRinLIL9CilLSFEFfUQXXBaC8kYn6GfyzDsI3yBMblvgPWo_SG5hIPFfjSfPlz_-v5jvcImhpSy9rtUSI9dD2N21hmdXRjv8D6GzRhSdgZH2Exe5xAP2AL0nTY77EPYH0M33oXO65TDoPGU3Lg5z5mvV2XUAL3TGXpsoNzhEfJtiLvH6IHVPsGT83mJPq9er5dvq5uPb94tr28qw6WkFWsYbbRsJAildM2EArvoTd0L4NRyVh6jGgoKuoYwrQSRYLUAaQkwKWvLL9GLU275zdcJUm4Hlwx4r0cIU2oZk1wVKWShz_-h2zDFsr2iOBUNk2rBi3p5Usf9RbDtPrpBx0NLSXtXXVuqa4_VFfvsnDh1ZQ1_5Z-uCpifwK3zcPh_Uvt--eoU-Rs-s6by</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2317528963</pqid></control><display><type>article</type><title>Comprehensive analysis of lncRNA‐TF crosstalks and identification of prognostic regulatory feedback loops of glioblastoma using lncRNA/TF‐mediated ceRNA network</title><source>Wiley</source><creator>Ji, Yang ; Gu, Yaqin ; Hong, Shuai ; Yu, Bo ; Zhang, Jian‐Hua ; Liu, Jin‐Na</creator><creatorcontrib>Ji, Yang ; Gu, Yaqin ; Hong, Shuai ; Yu, Bo ; Zhang, Jian‐Hua ; Liu, Jin‐Na</creatorcontrib><description>Glioblastoma (GBM) has become the most aggressive primary brain tumor in the world. Patients with GBM usually have a poor prognosis. The median survival times of GBM patients retain less than 2 years. Thus, it is urgent to investigate the molecular mechanism of GBM. Recently, studies have demonstrated that transcription factors (TFs) participate in cancer pathology by regulating long noncoding RNAs (lncRNAs). However, the functional and regulatory roles of TF‐lncRNA crosstalks are still unclear. In this study, we constructed a global lncRNA‐TF network (GLTN) based on competing endogenous RNA. As a result, some topological features of GLTN were identified. A known GBM lncRNA MCM3AP‐AS1 showed multiple central topological features in GLTN. Furthermore, we identified hub genes and extracted the hub‐hub pairs from GLTN to form a hub associated lncRNA‐TF network (HALTN). Results showed that a risk model combined with multiple hubs had a significant effect on prognosis. Additionally, we performed module searching and two functional modules from HALTN were identified, which were confirmed as risk factors of GBM. More importantly, we also identified some core lncRNA‐TF crosstalks that might form feedback loops to control the biological processes in GBM. Our results demonstrated that the synergistic, competitive lncRNA‐TF crosstalks played an important role in pathological processes of GBM, and had strong effect on prognosis. All these results can help us to uncover the molecular mechanism and provide a new therapeutic target for GBM. 1. A global view of long noncoding RNA transcription factor (lncRNA‐TF) crosstalks was constructed for glioblastoma (GBM) investigation. 2. Integration of competing endogenous RNA (ceRNA) crosstalks and TF‐DNA binding, some core lncRNA‐TF feedback loops with strong prognostic effect were identified.</description><identifier>ISSN: 0730-2312</identifier><identifier>EISSN: 1097-4644</identifier><identifier>DOI: 10.1002/jcb.29321</identifier><identifier>PMID: 31478223</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Biological activity ; Biomarkers, Tumor - genetics ; Biomarkers, Tumor - metabolism ; Brain cancer ; Brain tumors ; ceRNA networks ; Control theory ; core lncRNA‐TF crosstalks ; Feature extraction ; Feedback ; Feedback loops ; Feedback, Physiological ; Gene Expression Profiling ; Gene Expression Regulation, Neoplastic ; Gene Regulatory Networks ; Glioblastoma ; Glioblastoma - genetics ; Glioblastoma - metabolism ; Glioblastoma - pathology ; Humans ; Medical prognosis ; MicroRNAs - genetics ; MicroRNAs - metabolism ; Modules ; Prognosis ; Ribonucleic acid ; Risk analysis ; Risk factors ; RNA ; RNA, Long Noncoding - genetics ; RNA, Long Noncoding - metabolism ; survival biomarkers ; Survival Rate ; Therapeutic applications ; Topology ; Transcription factors ; Transcription Factors - genetics ; Transcription Factors - metabolism</subject><ispartof>Journal of cellular biochemistry, 2020-01, Vol.121 (1), p.755-767</ispartof><rights>2019 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3</citedby><cites>FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3</cites><orcidid>0000-0001-8299-5723</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31478223$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ji, Yang</creatorcontrib><creatorcontrib>Gu, Yaqin</creatorcontrib><creatorcontrib>Hong, Shuai</creatorcontrib><creatorcontrib>Yu, Bo</creatorcontrib><creatorcontrib>Zhang, Jian‐Hua</creatorcontrib><creatorcontrib>Liu, Jin‐Na</creatorcontrib><title>Comprehensive analysis of lncRNA‐TF crosstalks and identification of prognostic regulatory feedback loops of glioblastoma using lncRNA/TF‐mediated ceRNA network</title><title>Journal of cellular biochemistry</title><addtitle>J Cell Biochem</addtitle><description>Glioblastoma (GBM) has become the most aggressive primary brain tumor in the world. Patients with GBM usually have a poor prognosis. The median survival times of GBM patients retain less than 2 years. Thus, it is urgent to investigate the molecular mechanism of GBM. Recently, studies have demonstrated that transcription factors (TFs) participate in cancer pathology by regulating long noncoding RNAs (lncRNAs). However, the functional and regulatory roles of TF‐lncRNA crosstalks are still unclear. In this study, we constructed a global lncRNA‐TF network (GLTN) based on competing endogenous RNA. As a result, some topological features of GLTN were identified. A known GBM lncRNA MCM3AP‐AS1 showed multiple central topological features in GLTN. Furthermore, we identified hub genes and extracted the hub‐hub pairs from GLTN to form a hub associated lncRNA‐TF network (HALTN). Results showed that a risk model combined with multiple hubs had a significant effect on prognosis. Additionally, we performed module searching and two functional modules from HALTN were identified, which were confirmed as risk factors of GBM. More importantly, we also identified some core lncRNA‐TF crosstalks that might form feedback loops to control the biological processes in GBM. Our results demonstrated that the synergistic, competitive lncRNA‐TF crosstalks played an important role in pathological processes of GBM, and had strong effect on prognosis. All these results can help us to uncover the molecular mechanism and provide a new therapeutic target for GBM. 1. A global view of long noncoding RNA transcription factor (lncRNA‐TF) crosstalks was constructed for glioblastoma (GBM) investigation. 2. Integration of competing endogenous RNA (ceRNA) crosstalks and TF‐DNA binding, some core lncRNA‐TF feedback loops with strong prognostic effect were identified.</description><subject>Biological activity</subject><subject>Biomarkers, Tumor - genetics</subject><subject>Biomarkers, Tumor - metabolism</subject><subject>Brain cancer</subject><subject>Brain tumors</subject><subject>ceRNA networks</subject><subject>Control theory</subject><subject>core lncRNA‐TF crosstalks</subject><subject>Feature extraction</subject><subject>Feedback</subject><subject>Feedback loops</subject><subject>Feedback, Physiological</subject><subject>Gene Expression Profiling</subject><subject>Gene Expression Regulation, Neoplastic</subject><subject>Gene Regulatory Networks</subject><subject>Glioblastoma</subject><subject>Glioblastoma - genetics</subject><subject>Glioblastoma - metabolism</subject><subject>Glioblastoma - pathology</subject><subject>Humans</subject><subject>Medical prognosis</subject><subject>MicroRNAs - genetics</subject><subject>MicroRNAs - metabolism</subject><subject>Modules</subject><subject>Prognosis</subject><subject>Ribonucleic acid</subject><subject>Risk analysis</subject><subject>Risk factors</subject><subject>RNA</subject><subject>RNA, Long Noncoding - genetics</subject><subject>RNA, Long Noncoding - metabolism</subject><subject>survival biomarkers</subject><subject>Survival Rate</subject><subject>Therapeutic applications</subject><subject>Topology</subject><subject>Transcription factors</subject><subject>Transcription Factors - genetics</subject><subject>Transcription Factors - metabolism</subject><issn>0730-2312</issn><issn>1097-4644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10cuO0zAUBmALgZgysOAFkCU2sMjUl6S2l0NFuWgEEirryHGOi1snLrbDqDsegYfgyXgSPG1hgcTKkvXpP_b5EXpKyRUlhM23prtiijN6D80oUaKqF3V9H82I4KRinLIL9CilLSFEFfUQXXBaC8kYn6GfyzDsI3yBMblvgPWo_SG5hIPFfjSfPlz_-v5jvcImhpSy9rtUSI9dD2N21hmdXRjv8D6GzRhSdgZH2Exe5xAP2AL0nTY77EPYH0M33oXO65TDoPGU3Lg5z5mvV2XUAL3TGXpsoNzhEfJtiLvH6IHVPsGT83mJPq9er5dvq5uPb94tr28qw6WkFWsYbbRsJAildM2EArvoTd0L4NRyVh6jGgoKuoYwrQSRYLUAaQkwKWvLL9GLU275zdcJUm4Hlwx4r0cIU2oZk1wVKWShz_-h2zDFsr2iOBUNk2rBi3p5Usf9RbDtPrpBx0NLSXtXXVuqa4_VFfvsnDh1ZQ1_5Z-uCpifwK3zcPh_Uvt--eoU-Rs-s6by</recordid><startdate>202001</startdate><enddate>202001</enddate><creator>Ji, Yang</creator><creator>Gu, Yaqin</creator><creator>Hong, Shuai</creator><creator>Yu, Bo</creator><creator>Zhang, Jian‐Hua</creator><creator>Liu, Jin‐Na</creator><general>Wiley Subscription Services, Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QL</scope><scope>7QP</scope><scope>7QR</scope><scope>7T7</scope><scope>7TK</scope><scope>7U9</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>M7N</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8299-5723</orcidid></search><sort><creationdate>202001</creationdate><title>Comprehensive analysis of lncRNA‐TF crosstalks and identification of prognostic regulatory feedback loops of glioblastoma using lncRNA/TF‐mediated ceRNA network</title><author>Ji, Yang ; Gu, Yaqin ; Hong, Shuai ; Yu, Bo ; Zhang, Jian‐Hua ; Liu, Jin‐Na</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Biological activity</topic><topic>Biomarkers, Tumor - genetics</topic><topic>Biomarkers, Tumor - metabolism</topic><topic>Brain cancer</topic><topic>Brain tumors</topic><topic>ceRNA networks</topic><topic>Control theory</topic><topic>core lncRNA‐TF crosstalks</topic><topic>Feature extraction</topic><topic>Feedback</topic><topic>Feedback loops</topic><topic>Feedback, Physiological</topic><topic>Gene Expression Profiling</topic><topic>Gene Expression Regulation, Neoplastic</topic><topic>Gene Regulatory Networks</topic><topic>Glioblastoma</topic><topic>Glioblastoma - genetics</topic><topic>Glioblastoma - metabolism</topic><topic>Glioblastoma - pathology</topic><topic>Humans</topic><topic>Medical prognosis</topic><topic>MicroRNAs - genetics</topic><topic>MicroRNAs - metabolism</topic><topic>Modules</topic><topic>Prognosis</topic><topic>Ribonucleic acid</topic><topic>Risk analysis</topic><topic>Risk factors</topic><topic>RNA</topic><topic>RNA, Long Noncoding - genetics</topic><topic>RNA, Long Noncoding - metabolism</topic><topic>survival biomarkers</topic><topic>Survival Rate</topic><topic>Therapeutic applications</topic><topic>Topology</topic><topic>Transcription factors</topic><topic>Transcription Factors - genetics</topic><topic>Transcription Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ji, Yang</creatorcontrib><creatorcontrib>Gu, Yaqin</creatorcontrib><creatorcontrib>Hong, Shuai</creatorcontrib><creatorcontrib>Yu, Bo</creatorcontrib><creatorcontrib>Zhang, Jian‐Hua</creatorcontrib><creatorcontrib>Liu, Jin‐Na</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Neurosciences Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of cellular biochemistry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ji, Yang</au><au>Gu, Yaqin</au><au>Hong, Shuai</au><au>Yu, Bo</au><au>Zhang, Jian‐Hua</au><au>Liu, Jin‐Na</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comprehensive analysis of lncRNA‐TF crosstalks and identification of prognostic regulatory feedback loops of glioblastoma using lncRNA/TF‐mediated ceRNA network</atitle><jtitle>Journal of cellular biochemistry</jtitle><addtitle>J Cell Biochem</addtitle><date>2020-01</date><risdate>2020</risdate><volume>121</volume><issue>1</issue><spage>755</spage><epage>767</epage><pages>755-767</pages><issn>0730-2312</issn><eissn>1097-4644</eissn><abstract>Glioblastoma (GBM) has become the most aggressive primary brain tumor in the world. Patients with GBM usually have a poor prognosis. The median survival times of GBM patients retain less than 2 years. Thus, it is urgent to investigate the molecular mechanism of GBM. Recently, studies have demonstrated that transcription factors (TFs) participate in cancer pathology by regulating long noncoding RNAs (lncRNAs). However, the functional and regulatory roles of TF‐lncRNA crosstalks are still unclear. In this study, we constructed a global lncRNA‐TF network (GLTN) based on competing endogenous RNA. As a result, some topological features of GLTN were identified. A known GBM lncRNA MCM3AP‐AS1 showed multiple central topological features in GLTN. Furthermore, we identified hub genes and extracted the hub‐hub pairs from GLTN to form a hub associated lncRNA‐TF network (HALTN). Results showed that a risk model combined with multiple hubs had a significant effect on prognosis. Additionally, we performed module searching and two functional modules from HALTN were identified, which were confirmed as risk factors of GBM. More importantly, we also identified some core lncRNA‐TF crosstalks that might form feedback loops to control the biological processes in GBM. Our results demonstrated that the synergistic, competitive lncRNA‐TF crosstalks played an important role in pathological processes of GBM, and had strong effect on prognosis. All these results can help us to uncover the molecular mechanism and provide a new therapeutic target for GBM. 1. A global view of long noncoding RNA transcription factor (lncRNA‐TF) crosstalks was constructed for glioblastoma (GBM) investigation. 2. Integration of competing endogenous RNA (ceRNA) crosstalks and TF‐DNA binding, some core lncRNA‐TF feedback loops with strong prognostic effect were identified.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>31478223</pmid><doi>10.1002/jcb.29321</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0001-8299-5723</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0730-2312
ispartof Journal of cellular biochemistry, 2020-01, Vol.121 (1), p.755-767
issn 0730-2312
1097-4644
language eng
recordid cdi_proquest_miscellaneous_2283988478
source Wiley
subjects Biological activity
Biomarkers, Tumor - genetics
Biomarkers, Tumor - metabolism
Brain cancer
Brain tumors
ceRNA networks
Control theory
core lncRNA‐TF crosstalks
Feature extraction
Feedback
Feedback loops
Feedback, Physiological
Gene Expression Profiling
Gene Expression Regulation, Neoplastic
Gene Regulatory Networks
Glioblastoma
Glioblastoma - genetics
Glioblastoma - metabolism
Glioblastoma - pathology
Humans
Medical prognosis
MicroRNAs - genetics
MicroRNAs - metabolism
Modules
Prognosis
Ribonucleic acid
Risk analysis
Risk factors
RNA
RNA, Long Noncoding - genetics
RNA, Long Noncoding - metabolism
survival biomarkers
Survival Rate
Therapeutic applications
Topology
Transcription factors
Transcription Factors - genetics
Transcription Factors - metabolism
title Comprehensive analysis of lncRNA‐TF crosstalks and identification of prognostic regulatory feedback loops of glioblastoma using lncRNA/TF‐mediated ceRNA network
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T11%3A04%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Comprehensive%20analysis%20of%20lncRNA%E2%80%90TF%20crosstalks%20and%20identification%20of%20prognostic%20regulatory%20feedback%20loops%20of%20glioblastoma%20using%20lncRNA/TF%E2%80%90mediated%20ceRNA%20network&rft.jtitle=Journal%20of%20cellular%20biochemistry&rft.au=Ji,%20Yang&rft.date=2020-01&rft.volume=121&rft.issue=1&rft.spage=755&rft.epage=767&rft.pages=755-767&rft.issn=0730-2312&rft.eissn=1097-4644&rft_id=info:doi/10.1002/jcb.29321&rft_dat=%3Cproquest_cross%3E2317528963%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c3881-25215a858e799a4279ef6dc4d7e31f32eed951e9eb502a9708efa7e8f0e2884f3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2317528963&rft_id=info:pmid/31478223&rfr_iscdi=true