In Vitro Diagnosis and Visualization of Cerebral Ischemia/ Reperfusion Injury in Rats and Protective Effects of Ferulic Acid by Raman Biospectroscopy and Machine Learning

doi:10.1021/acschemneuro.2c00612

CORC > 长春光学精密机械与物理研究所 > 中国科学院长春光学精密机械与物理研究所

	In Vitro Diagnosis and Visualization of Cerebral Ischemia/ Reperfusion Injury in Rats and Protective Effects of Ferulic Acid by Raman Biospectroscopy and Machine Learning
	M. Y. Liu; J. Mu; W. Gong; K. A. Zhang; M. Y. Yuan; Y. Z. Song; B. Li; N. F. Jin; W. J. Zhang and D. Y. Zhang
刊名	Acs Chemical Neuroscience
	2022
页码	11
ISSN号	1948-7193
DOI	10.1021/acschemneuro.2c00612
英文摘要	Ischemic stroke is a major cause of mortality with complicated pathophysiological mechanisms, and hematoxylin and eosin (HE) staining is a histochemical diagnosis technique heavily relying on subjective observation. In this study, we developed a noninvasive assay using Raman spectroscopy for in vitro diagnosis and visualization of cerebral ischemia/reperfusion injury and protective effects of ferulic acid. By establishing a middle cerebral artery occlusion (MCAO) model in Sprague-Dawley male rats, we found effective interventions by ferulic acid using the neurological function score and HE staining. Raman spectra of neuronal and neuroglial cells exhibited significant intensity changes of protein, nucleotide, lipid, and carbohydrate at 780, 814, 1002, 1012, 1176, 1224, 1402, 1520, 1586, 1614, and 1752 cm-1. Cluster vector analysis highlighted the alterations at 1002, 1080, 1298, 1430, 1478, 1508, 1586, and 1676 cm-1. To evaluate the levels of neuron injury and intervention performance, a random forest model was developed on Raman spectral data and achieved satisfactory accuracy (0.9846), sensitivity (0.9679-0.9932), and specificity (0.9945-0.9989), ranking peaks around 1002 cm-1 as key fingerprint for classification. Spectral phenylalanine-to-tryptophan ratio was the biomarker to visualize neuronal injury and intervention performance of ferulic acid with a resolution of 1 mu m. Our results unravel the biochemical changes in neuronal cells with cerebral ischemia/reperfusion injury and ferulic acid treatment, and prove Raman spectroscopy coupled with machine learning as a power tool to classify neuron viability and evaluate the intervention performance in pharmacological research.
URL标识	查看原文
语种	英语
内容类型	期刊论文
源URL	[http://ir.ciomp.ac.cn/handle/181722/66753]
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	M. Y. Liu,J. Mu,W. Gong,et al. In Vitro Diagnosis and Visualization of Cerebral Ischemia/ Reperfusion Injury in Rats and Protective Effects of Ferulic Acid by Raman Biospectroscopy and Machine Learning[J]. Acs Chemical Neuroscience,2022:11.
APA	M. Y. Liu.,J. Mu.,W. Gong.,K. A. Zhang.,M. Y. Yuan.,...&W. J. Zhang and D. Y. Zhang.(2022).In Vitro Diagnosis and Visualization of Cerebral Ischemia/ Reperfusion Injury in Rats and Protective Effects of Ferulic Acid by Raman Biospectroscopy and Machine Learning.Acs Chemical Neuroscience,11.
MLA	M. Y. Liu,et al."In Vitro Diagnosis and Visualization of Cerebral Ischemia/ Reperfusion Injury in Rats and Protective Effects of Ferulic Acid by Raman Biospectroscopy and Machine Learning".Acs Chemical Neuroscience (2022):11.