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傅里叶变换红外光谱法的无监督和有监督分析方法对非标记感染性急性肾盂肾炎组织的研究。

Label-free investigation of infected acute pyelonephritis tissue by FTIR microspectroscopy with unsupervised and supervised analytical methods.

机构信息

Center for Biophotonics, Institute of Medical Robotics, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

出版信息

Spectrochim Acta A Mol Biomol Spectrosc. 2024 Nov 15;321:124753. doi: 10.1016/j.saa.2024.124753. Epub 2024 Jun 28.

Abstract

Acute pyelonephritis (AP) is a severe urinary tract infection (UTI) syndrome with a large population of patients worldwide. Current approaches to confirming AP are limited to urinalysis, radiological imaging methods and histological assessment. Fourier transform infrared (FTIR) microspectroscopy is a promising label-free modality that can offer information about both morphological and molecular pathologic alterations from biological tissues. Here, FTIR microspectroscopy serves to investigate renal biological histology of a rat model with AP and classify normal cortex, normal medulla and infected acute pyelonephritis tissues. The spectra were experimentally collected by FTIR with an infrared Globar source through raster scanning procedure. Unsupervised analysis methods, including integrating, clustering and principal component analysis (PCA) were performed on such spectra data to form infrared histological maps of entire kidney section. In comparison to Hematoxylin & Eosin-stained results of the adjacent tissue sections, these infrared maps were proved to enable the differentiation of the renal tissue types. The results of both integration and clustering indicated that the concentration of amide II decreases in the infected acute pyelonephritis tissues, with an increased presence of nucleic acids and lipids. By means of PCA, the infected tissue was linearly separated from normal ones by plotting confident ellipses with the score values of the first and second principal components. Moreover, supervised analysis was performed based on the supported vector machines (SVM). Normal cortex, normal medulla and infected acute pyelonephritis tissues were classified by SVM models with the best accuracy of 96.11% in testing dataset. In addition, these analytical methods were further employed on synchrotron-based FTIR spectra data and successfully form high-resolution infrared histological maps of glomerulus and necrotic cell mass. This work demonstrates that FTIR microspectroscopy will be a powerful manner to investigate AP tissue and differentiate infected tissue from normal tissue in a renal infected model system.

摘要

急性肾盂肾炎(AP)是一种严重的尿路感染(UTI)综合征,在全球范围内有大量患者。目前确认 AP 的方法仅限于尿液分析、放射影像学方法和组织学评估。傅里叶变换红外(FTIR)显微光谱技术是一种很有前途的无标记模式,可以提供有关生物组织形态和分子病理改变的信息。在这里,FTIR 显微光谱技术用于研究 AP 大鼠模型的肾脏生物学组织,并对正常皮质、正常髓质和感染性急性肾盂肾炎组织进行分类。通过光栅扫描程序,使用带有红外 Globar 源的 FTIR 实验采集光谱。对这些光谱数据进行无监督分析方法,包括积分、聚类和主成分分析(PCA),以形成整个肾脏切片的红外组织学图谱。与相邻组织切片的苏木精和伊红染色结果相比,这些红外图谱被证明能够区分肾脏组织类型。积分和聚类的结果均表明,感染性急性肾盂肾炎组织中的酰胺 II 浓度降低,核酸和脂质增加。通过 PCA,通过绘制置信椭圆并用第一和第二主成分的得分值对正常和感染组织进行线性分离。此外,还基于支持向量机(SVM)进行了监督分析。通过 SVM 模型对正常皮质、正常髓质和感染性急性肾盂肾炎组织进行分类,在测试数据集上的准确率最高可达 96.11%。此外,这些分析方法还进一步应用于基于同步加速器的 FTIR 光谱数据,并成功形成肾小球和坏死细胞团的高分辨率红外组织学图谱。这项工作表明,FTIR 显微光谱技术将是一种研究 AP 组织并在肾脏感染模型系统中区分感染组织和正常组织的有力方法。

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