{"title":"利用大环传感器阵列诊断人体血清中 SARS-Cov-2 感染的方法学研究","authors":"Monica Swetha Bosco, Zeki Topçu, Soumen Pradhan, Ariadne Sossah, Vassilis Tsatsaris, Christelle Vauloup-Fellous, Sarit S. Agasti, Yves Rozenholc and Nathalie Gagey-Eilstein","doi":"10.1039/D4SD00009A","DOIUrl":null,"url":null,"abstract":"<p >This article reports the methodology and the proof of concept of a blood-based diagnostic strategy for the SARS-CoV-2 infection. The proposed method relies on the non-specific/selective array-based sensing strategy mimicking the human olfactory system using a cucurbit[7]uril macrocycle receptor conjugated with a library of environmentally sensitive fluorophores. The study cohort includes 26 samples, <em>i.e.</em> 12 cases and 14 controls. Statistical analysis methods such as linear discriminant and random forest were able to successfully classify and discriminate the two groups with almost 90% accuracy. This diagnostic result highlights the methodology and confirms the potential of this non-specific/selective sensing approach for non-invasive clinical diagnosis.</p>","PeriodicalId":74786,"journal":{"name":"Sensors & diagnostics","volume":" 5","pages":" 863-871"},"PeriodicalIF":3.5000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://pubs.rsc.org/en/content/articlepdf/2024/sd/d4sd00009a?page=search","citationCount":"0","resultStr":"{\"title\":\"A methodological study for the diagnosis of the SARS-Cov-2 infection in human serum with a macrocyclic sensor array†\",\"authors\":\"Monica Swetha Bosco, Zeki Topçu, Soumen Pradhan, Ariadne Sossah, Vassilis Tsatsaris, Christelle Vauloup-Fellous, Sarit S. Agasti, Yves Rozenholc and Nathalie Gagey-Eilstein\",\"doi\":\"10.1039/D4SD00009A\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p >This article reports the methodology and the proof of concept of a blood-based diagnostic strategy for the SARS-CoV-2 infection. The proposed method relies on the non-specific/selective array-based sensing strategy mimicking the human olfactory system using a cucurbit[7]uril macrocycle receptor conjugated with a library of environmentally sensitive fluorophores. The study cohort includes 26 samples, <em>i.e.</em> 12 cases and 14 controls. Statistical analysis methods such as linear discriminant and random forest were able to successfully classify and discriminate the two groups with almost 90% accuracy. This diagnostic result highlights the methodology and confirms the potential of this non-specific/selective sensing approach for non-invasive clinical diagnosis.</p>\",\"PeriodicalId\":74786,\"journal\":{\"name\":\"Sensors & diagnostics\",\"volume\":\" 5\",\"pages\":\" 863-871\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://pubs.rsc.org/en/content/articlepdf/2024/sd/d4sd00009a?page=search\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sensors & diagnostics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://pubs.rsc.org/en/content/articlelanding/2024/sd/d4sd00009a\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"CHEMISTRY, ANALYTICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensors & diagnostics","FirstCategoryId":"1085","ListUrlMain":"https://pubs.rsc.org/en/content/articlelanding/2024/sd/d4sd00009a","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, ANALYTICAL","Score":null,"Total":0}
A methodological study for the diagnosis of the SARS-Cov-2 infection in human serum with a macrocyclic sensor array†
This article reports the methodology and the proof of concept of a blood-based diagnostic strategy for the SARS-CoV-2 infection. The proposed method relies on the non-specific/selective array-based sensing strategy mimicking the human olfactory system using a cucurbit[7]uril macrocycle receptor conjugated with a library of environmentally sensitive fluorophores. The study cohort includes 26 samples, i.e. 12 cases and 14 controls. Statistical analysis methods such as linear discriminant and random forest were able to successfully classify and discriminate the two groups with almost 90% accuracy. This diagnostic result highlights the methodology and confirms the potential of this non-specific/selective sensing approach for non-invasive clinical diagnosis.