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

被引:7
作者
Liu, Mingying [1 ]
Mu, Ju [1 ]
Gong, Wan [1 ]
Zhang, Kena [1 ]
Yuan, Maoyun [1 ]
Song, Yizhi [2 ]
Li, Bei [3 ]
Jin, Naifu [4 ]
Zhang, Wenjing [5 ,6 ]
Zhang, Dayi [5 ,6 ]
机构
[1] Zhejiang Chinese Med Univ, Sch Basic Med Sci, Hangzhou 310053, Peoples R China
[2] Chinese Acad Sci, Suzhou Inst Biomed Engn & Technol, CAS Key Lab Biomed Diagnost, Suzhou 215163, Peoples R China
[3] Chinese Acad Sci, Changchun Inst Opt, State Key Lab Appl Opt, Fine Mech & Phys, Changchun 130033, Peoples R China
[4] Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China
[5] Minist Educ, Key Lab Groundwater Resources & Environm, Changchun 130021, Peoples R China
[6] Jilin Univ, Coll New Energy & Environm, Changchun 130021, Peoples R China
关键词
Ischemic stroke; vibrational spectroscopy; machine learning; OXIDATIVE STRESS; ARTERY OCCLUSION; STROKE; NEUROPROTECTION; MECHANISMS;
D O I
10.1021/acschemneuro.2c00612
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
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.
引用
收藏
页码:159 / 169
页数:11
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