{"title":"Green autofluorescence of the skin and fingernails is a novel biomarker for evaluating the risk for developing acute ischemic stroke","authors":"Yue Tao, Haibo Yu, Mingchao Zhang, Xiaofeng Zou, Peilu Li, Jian-Ge Qiu, Bing-Hua Jiang, Weihai Ying","doi":"10.1002/jbio.202300473","DOIUrl":null,"url":null,"abstract":"<p>The only existing approach for assessing the risk of developing acute ischemic stroke (AIS) necessitates that individuals possess a strong understanding of their health status. Our research gathered compelling evidence in favor of our hypothesis, suggesting that the likelihood of developing AIS can be assessed by analyzing the green autofluorescence (AF) of the skin and fingernails. Utilizing machine learning-based analyses of AF images, we found that the area under the curve (AUC) for distinguishing subjects with three risk factors from those with zero, one, or two risk factors was 0.79, 0.76, and 0.75, respectively. Our research has revealed that green AF serves as an innovative biomarker for assessing the risk of developing AIS. Our method is objective, non-invasive, efficient, and economic, which shows great promise to boost a technology for screening natural populations for risk of developing AIS.</p>","PeriodicalId":184,"journal":{"name":"Journal of Biophotonics","volume":null,"pages":null},"PeriodicalIF":2.0000,"publicationDate":"2024-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biophotonics","FirstCategoryId":"101","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jbio.202300473","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
The only existing approach for assessing the risk of developing acute ischemic stroke (AIS) necessitates that individuals possess a strong understanding of their health status. Our research gathered compelling evidence in favor of our hypothesis, suggesting that the likelihood of developing AIS can be assessed by analyzing the green autofluorescence (AF) of the skin and fingernails. Utilizing machine learning-based analyses of AF images, we found that the area under the curve (AUC) for distinguishing subjects with three risk factors from those with zero, one, or two risk factors was 0.79, 0.76, and 0.75, respectively. Our research has revealed that green AF serves as an innovative biomarker for assessing the risk of developing AIS. Our method is objective, non-invasive, efficient, and economic, which shows great promise to boost a technology for screening natural populations for risk of developing AIS.
期刊介绍:
The first international journal dedicated to publishing reviews and original articles from this exciting field, the Journal of Biophotonics covers the broad range of research on interactions between light and biological material. The journal offers a platform where the physicist communicates with the biologist and where the clinical practitioner learns about the latest tools for the diagnosis of diseases. As such, the journal is highly interdisciplinary, publishing cutting edge research in the fields of life sciences, medicine, physics, chemistry, and engineering. The coverage extends from fundamental research to specific developments, while also including the latest applications.