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基于同步辐射的 STXM 和 FTIR 测量砷诱导细胞的剂量依赖性定量毒理学研究。

Quantitative toxicological study of dose-dependent arsenic-induced cells via synchrotron-based STXM and FTIR measurement.

机构信息

School of Physics and Optoelectronic Engineering, Shandong University of Technology, Zibo 255000, China.

出版信息

Analyst. 2020 Jul 7;145(13):4560-4568. doi: 10.1039/d0an00346h. Epub 2020 May 20.

Abstract

Inorganic arsenic (iAs) is a well-known naturally occurring metalloid with abundant hazards to our environment, especially being a human carcinogen through arsenic-contaminated drinking water. The iAs-related contamination is usually examined by a chemical assay system or fluorescence staining technique to investigate iAs accumulation and its deleterious effects. In this work, we present a dual-modality measurement and quantitative analysis methods for the overall evaluation of various dose-dependent iAs-related cytotoxicological manifestations by the combination of the synchrotron-radiation-based scanning transmission soft X-ray microscopy (SR-STXM) and Fourier transform infrared micro-spectroscopy (SR-FTIR) techniques. The gray level co-occurrence matrix (GLCM) based machine learning was employed on SR-STXM data to quantify the cytomorphological feature changes and the dose-dependent iAs-induced feature classifications with increasing doses. The infrared spectral absorption peaks and changes of dose-dependent iAs-induced cells were obtained by the SR-FTIR technique and classified by the multi-spectral-variate principle component analysis (PCA-LDA) method, showing the separated spatial distribution of dose-dependent groups. In addition, the quantitative comparisons of trivalent and pentavalent iAs under high dose conditions (iAs_H & iAs_H) demonstrated that iAs_H and its compounds were more toxic than iAs_H. This method has a potential in providing the morphological and spectral characteristics evolution of the iAs-related cells or particles, revealing the actual risk of arsenic contamination and metabolism.

摘要

无机砷(iAs)是一种众所周知的天然类金属,对我们的环境有很大的危害,尤其是通过砷污染的饮用水成为人类的致癌物质。通常通过化学分析系统或荧光染色技术来检测与 iAs 相关的污染,以研究 iAs 的积累及其有害影响。在这项工作中,我们提出了一种双重模式测量和定量分析方法,通过同步辐射扫描透射软 X 射线显微镜(SR-STXM)和傅里叶变换红外微光谱(SR-FTIR)技术的组合,对各种剂量依赖性 iAs 相关细胞毒性表现进行整体评估。基于灰度共生矩阵(GLCM)的机器学习被应用于 SR-STXM 数据,以量化细胞形态特征变化和剂量依赖性 iAs 诱导的特征分类,随着剂量的增加而增加。通过 SR-FTIR 技术获得了红外光谱吸收峰和剂量依赖性 iAs 诱导细胞的变化,并通过多光谱变量主成分分析(PCA-LDA)方法进行分类,显示出剂量依赖性组的分离空间分布。此外,在高剂量条件下(iAs_H 和 iAs_H)对三价和五价 iAs 的定量比较表明,iAs_H 及其化合物比 iAs_H 更具毒性。该方法有可能提供与 iAs 相关的细胞或颗粒的形态和光谱特征演变,揭示砷污染和代谢的实际风险。

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