Suppr超能文献

[两种急性髓系白血病细胞的超微结构及拉曼光谱特征]

[Ultrastructure and Raman Spectral Characteristics of Two Kinds of Acute Myeloid Leukemia Cells].

作者信息

Liang Hao-Yue, Cheng Xue-Lian, Dong Shu-Xu, Zhao Shi-Xuan, Wang Ying, Ru Yong-Xin

机构信息

State Key Laboratory of Experimental Hematology, Institute of Hematology & Blood Disease Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China.

State Key Laboratory of Experimental Hematology, Institute of Hematology & Blood Disease Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China. E-mail:

出版信息

Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2018 Feb;26(1):1-7. doi: 10.7534/j.issn.1009-2137.2018.01.001.

Abstract

OBJECTIVE

To investigate the Raman spectral characteristics of leukemia cells from 4 patients with acute promyelocytic leukemia (M) and 3 patients with acute monoblastic leukemia (M), establish a novel Raman label-free method to distinguish 2 kinds of acute myeloid leukemia cells so as to provide basis for clinical research.

METHODS

Leukemia cells were collected from bone marrow of above-mentioned patients. Raman spectra were acquired by Horiba Xplora Raman spectrometer and Raman spectra of 30-50 cells from each patient were recorded. The diagnostic model was established according to principle component analysis (PCA), discriminant function analysis (DFA) and cluster analysis, and the spectra of leukemia cells from 7 patients were analyzed and classified. Characteristics of Raman spectra were analyzed combining with ultrastructure of leukemia cells.

RESULTS

There were significant differences between Raman spectra of 2 kinds of leukemia cells. Compared with acute monoblastic leukemia cells, the spectra of acute promyelocytic leukemia cells showed stronger peaks in 622, 643, 757, 852, 1003, 1033, 1117, 1157, 1173, 1208, 1340, 1551, 1581 cm. The diagnostic models established by PCA-DFA and cluster analysis could successfully classify these Raman spectra of different samples with a high accuracy of 100% (233/233). The model was evaluated by "Leave-one-out" cross-validation and reached a high accuracy of 97% (226/233).

CONCLUSION

The level of macromolecules of M cells is higher than that of M. The diagnostic models established by PCA-DFA can classify these Raman spectra of different cells with a high accuracy. Raman spectra shows consistent result with ultrastructure by TEM.

摘要

目的

研究4例急性早幼粒细胞白血病(M3)患者和3例急性单核细胞白血病(M5)患者白血病细胞的拉曼光谱特征,建立一种新型的无标记拉曼方法区分这两种急性髓系白血病细胞,为临床研究提供依据。

方法

采集上述患者骨髓中的白血病细胞。采用Horiba Xplora拉曼光谱仪获取拉曼光谱,记录每位患者30 - 50个细胞的拉曼光谱。根据主成分分析(PCA)、判别函数分析(DFA)和聚类分析建立诊断模型,并对7例患者白血病细胞的光谱进行分析和分类。结合白血病细胞超微结构分析拉曼光谱特征。

结果

两种白血病细胞的拉曼光谱存在显著差异。与急性单核细胞白血病细胞相比,急性早幼粒细胞白血病细胞的光谱在622、643、757、852、1003、1033、1117、1157、1173、1208、1340、1551、1581 cm处显示出更强的峰。通过PCA - DFA和聚类分析建立的诊断模型能够成功地对这些不同样本的拉曼光谱进行分类,准确率高达100%(233/233)。该模型通过“留一法”交叉验证进行评估,准确率达到97%(226/233)。

结论

M3细胞的大分子水平高于M5。PCA - DFA建立的诊断模型能够对不同细胞的拉曼光谱进行高精度分类。拉曼光谱与透射电镜超微结构结果一致。

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