Suppr超能文献

紫外线诱导的皮肤绿色自发荧光是用于皮肤紫外线暴露剂量的非侵入性评估以及紫外线诱导的皮肤损伤的非侵入性预测的生物标志物。

UV-induced skin's green autofluorescence is a biomarker for both non-invasive evaluations of the dosages of UV exposures of the skin and non-invasive prediction of UV-induced skin damage.

作者信息

Zhang Mingchao, Ying Weihai

机构信息

School of Biomedical Engineering and Med-X Research Institute, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai, 200030, People's Republic of China.

Multiscale Research Institute of Complex Systems, Fudan University, 220 Handan Road, Shanghai, People's Republic of China.

出版信息

Photochem Photobiol Sci. 2023 Jan;22(1):159-168. doi: 10.1007/s43630-022-00306-z. Epub 2022 Sep 22.

Abstract

It is crucial to discover biomarkers for non-invasive evaluations of the dosages of UV exposures to a person during post-UV exposure period, and for non-invasive prediction of UV-induced skin damage. Our current study has obtained findings: UVB exposures produced dose-dependent increases in skin's green autofluorescence (AF) intensity of mice, which were significantly associated with the UVB dosages. The UVC-induced green AF increases were dose dependent, which were highly associated with the UVC dosages. Moreover, both previous reports and our current study have collectively shown significant association between UVB/UVC dosages and UVB/UVC-induced skin damage. Collectively, our study has indicated that the UVB/UVC-induced skin's AF are first biomarkers for both non-invasive evaluations of the dosages of UV exposures to a person during post-UV exposure period and non-invasive and label-free prediction of UVB/UVC-induced skin damage.

摘要

发现生物标志物对于在紫外线暴露后期间对个体紫外线暴露剂量进行非侵入性评估以及对紫外线诱导的皮肤损伤进行非侵入性预测至关重要。我们目前的研究有以下发现:紫外线B(UVB)照射使小鼠皮肤的绿色自发荧光(AF)强度呈剂量依赖性增加,这与UVB剂量显著相关。紫外线C(UVC)诱导的绿色AF增加也是剂量依赖性的,且与UVC剂量高度相关。此外,先前的报告和我们目前的研究共同表明,UVB/UVC剂量与UVB/UVC诱导的皮肤损伤之间存在显著关联。总体而言,我们的研究表明,UVB/UVC诱导的皮肤AF是用于在紫外线暴露后期间对个体紫外线暴露剂量进行非侵入性评估以及对UVB/UVC诱导的皮肤损伤进行非侵入性和无标记预测的首批生物标志物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验