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Three-step one-way model in terahertz biomedical detection
Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-st...
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Published in: | PhotoniX 2021-07, Vol.2 (1), Article 12 |
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container_title | PhotoniX |
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creator | Peng, Yan Huang, Jieli Luo, Jie Yang, Zhangfan Wang, Liping Wu, Xu Zang, Xiaofei Yu, Chen Gu, Min Hu, Qing Zhang, Xicheng Zhu, Yiming Zhuang, Songlin |
description | Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-step one-way terahertz model, presenting a detailed flow analysis of terahertz technology in the biomedical detection of renal fibrosis as an example:
1) biomarker determination:
screening disease biomarkers and establishing the terahertz spectrum and concentration gradient;
2) mixture interference removal:
clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and
3) individual difference removal:
excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases. |
doi_str_mv | 10.1186/s43074-021-00034-0 |
format | article |
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1) biomarker determination:
screening disease biomarkers and establishing the terahertz spectrum and concentration gradient;
2) mixture interference removal:
clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and
3) individual difference removal:
excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases.</description><identifier>ISSN: 2662-1991</identifier><identifier>EISSN: 2662-1991</identifier><identifier>DOI: 10.1186/s43074-021-00034-0</identifier><language>eng</language><publisher>Singapore: Springer Singapore</publisher><subject>Accuracy ; Algorithms ; Biomarkers ; Disease ; Engineering ; Enzymes ; High density polyethylenes ; Identification ; Labeling ; Lasers ; Medical prognosis ; Microwaves ; Morphology ; Polyethylene ; Quantitative analysis ; Radiation ; RF and Optical Engineering</subject><ispartof>PhotoniX, 2021-07, Vol.2 (1), Article 12</ispartof><rights>The Author(s) 2021</rights><rights>The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c430t-61d3355d34ceca4db2e4182ece81e02bd3fd0338571759caa2d85a9ebcca0c353</citedby><cites>FETCH-LOGICAL-c430t-61d3355d34ceca4db2e4182ece81e02bd3fd0338571759caa2d85a9ebcca0c353</cites><orcidid>0000-0002-8273-5566</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2729533239/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2729533239?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,25735,27906,27907,36994,44572,74876</link.rule.ids></links><search><creatorcontrib>Peng, Yan</creatorcontrib><creatorcontrib>Huang, Jieli</creatorcontrib><creatorcontrib>Luo, Jie</creatorcontrib><creatorcontrib>Yang, Zhangfan</creatorcontrib><creatorcontrib>Wang, Liping</creatorcontrib><creatorcontrib>Wu, Xu</creatorcontrib><creatorcontrib>Zang, Xiaofei</creatorcontrib><creatorcontrib>Yu, Chen</creatorcontrib><creatorcontrib>Gu, Min</creatorcontrib><creatorcontrib>Hu, Qing</creatorcontrib><creatorcontrib>Zhang, Xicheng</creatorcontrib><creatorcontrib>Zhu, Yiming</creatorcontrib><creatorcontrib>Zhuang, Songlin</creatorcontrib><title>Three-step one-way model in terahertz biomedical detection</title><title>PhotoniX</title><addtitle>PhotoniX</addtitle><description>Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-step one-way terahertz model, presenting a detailed flow analysis of terahertz technology in the biomedical detection of renal fibrosis as an example:
1) biomarker determination:
screening disease biomarkers and establishing the terahertz spectrum and concentration gradient;
2) mixture interference removal:
clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and
3) individual difference removal:
excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Biomarkers</subject><subject>Disease</subject><subject>Engineering</subject><subject>Enzymes</subject><subject>High density polyethylenes</subject><subject>Identification</subject><subject>Labeling</subject><subject>Lasers</subject><subject>Medical prognosis</subject><subject>Microwaves</subject><subject>Morphology</subject><subject>Polyethylene</subject><subject>Quantitative analysis</subject><subject>Radiation</subject><subject>RF and Optical Engineering</subject><issn>2662-1991</issn><issn>2662-1991</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNp9kMFKAzEQhoMoWGpfwNOC52iS2exuvElRKxS81HPIJrN2S7upSYrUpze6gp48zRy-_5_hI-SSs2vOm-omlsDqkjLBKWMM8nZCJqKqBOVK8dM_-zmZxbjJkKgVlEpMyO1qHRBpTLgv_ID03RyLnXe4LfqhSBjMGkP6KNre79D11mwLhwlt6v1wQc46s404-5lT8vJwv5ov6PL58Wl-t6Q2_5VoxR2AlA5Ki9aUrhVY8kagxYYjE62DzjGARta8lsoaI1wjjcLWWsMsSJiSq7F3H_zbAWPSG38IQz6pRS2UBBCgMiVGygYfY8BO70O_M-GoOdNfmvSoSWdN-luTZjkEYyhmeHjF8Fv9T-oTIHFp-g</recordid><startdate>20210723</startdate><enddate>20210723</enddate><creator>Peng, Yan</creator><creator>Huang, Jieli</creator><creator>Luo, Jie</creator><creator>Yang, Zhangfan</creator><creator>Wang, Liping</creator><creator>Wu, Xu</creator><creator>Zang, Xiaofei</creator><creator>Yu, Chen</creator><creator>Gu, Min</creator><creator>Hu, Qing</creator><creator>Zhang, Xicheng</creator><creator>Zhu, Yiming</creator><creator>Zhuang, Songlin</creator><general>Springer Singapore</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><orcidid>https://orcid.org/0000-0002-8273-5566</orcidid></search><sort><creationdate>20210723</creationdate><title>Three-step one-way model in terahertz biomedical detection</title><author>Peng, Yan ; Huang, Jieli ; Luo, Jie ; Yang, Zhangfan ; Wang, Liping ; Wu, Xu ; Zang, Xiaofei ; Yu, Chen ; Gu, Min ; Hu, Qing ; Zhang, Xicheng ; Zhu, Yiming ; Zhuang, Songlin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c430t-61d3355d34ceca4db2e4182ece81e02bd3fd0338571759caa2d85a9ebcca0c353</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Biomarkers</topic><topic>Disease</topic><topic>Engineering</topic><topic>Enzymes</topic><topic>High density polyethylenes</topic><topic>Identification</topic><topic>Labeling</topic><topic>Lasers</topic><topic>Medical prognosis</topic><topic>Microwaves</topic><topic>Morphology</topic><topic>Polyethylene</topic><topic>Quantitative analysis</topic><topic>Radiation</topic><topic>RF and Optical Engineering</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Peng, Yan</creatorcontrib><creatorcontrib>Huang, Jieli</creatorcontrib><creatorcontrib>Luo, Jie</creatorcontrib><creatorcontrib>Yang, Zhangfan</creatorcontrib><creatorcontrib>Wang, Liping</creatorcontrib><creatorcontrib>Wu, Xu</creatorcontrib><creatorcontrib>Zang, Xiaofei</creatorcontrib><creatorcontrib>Yu, Chen</creatorcontrib><creatorcontrib>Gu, Min</creatorcontrib><creatorcontrib>Hu, Qing</creatorcontrib><creatorcontrib>Zhang, Xicheng</creatorcontrib><creatorcontrib>Zhu, Yiming</creatorcontrib><creatorcontrib>Zhuang, Songlin</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>PhotoniX</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Peng, Yan</au><au>Huang, Jieli</au><au>Luo, Jie</au><au>Yang, Zhangfan</au><au>Wang, Liping</au><au>Wu, Xu</au><au>Zang, Xiaofei</au><au>Yu, Chen</au><au>Gu, Min</au><au>Hu, Qing</au><au>Zhang, Xicheng</au><au>Zhu, Yiming</au><au>Zhuang, Songlin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Three-step one-way model in terahertz biomedical detection</atitle><jtitle>PhotoniX</jtitle><stitle>PhotoniX</stitle><date>2021-07-23</date><risdate>2021</risdate><volume>2</volume><issue>1</issue><artnum>12</artnum><issn>2662-1991</issn><eissn>2662-1991</eissn><abstract>Terahertz technology has broad application prospects in biomedical detection. However, the mixed characteristics of actual samples make the terahertz spectrum complex and difficult to distinguish, and there is no practical terahertz detection method for clinical medicine. Here, we propose a three-step one-way terahertz model, presenting a detailed flow analysis of terahertz technology in the biomedical detection of renal fibrosis as an example:
1) biomarker determination:
screening disease biomarkers and establishing the terahertz spectrum and concentration gradient;
2) mixture interference removal:
clearing the interfering signals in the mixture for the biomarker in the animal model and evaluating and retaining the effective characteristic peaks; and
3) individual difference removal:
excluding individual interference differences and confirming the final effective terahertz parameters in the human sample. The root mean square error of our model is three orders of magnitude lower than that of the gold standard, with profound implications for the rapid, accurate and early detection of diseases.</abstract><cop>Singapore</cop><pub>Springer Singapore</pub><doi>10.1186/s43074-021-00034-0</doi><orcidid>https://orcid.org/0000-0002-8273-5566</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Algorithms Biomarkers Disease Engineering Enzymes High density polyethylenes Identification Labeling Lasers Medical prognosis Microwaves Morphology Polyethylene Quantitative analysis Radiation RF and Optical Engineering |
title | Three-step one-way model in terahertz biomedical detection |
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