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Raman spectroscopic detection of early stages in DMBA-induced tumor evolution in hamster buccal pouch model: an exploratory study

机译:拉曼光谱法检测仓鼠颊囊模型中DMBA诱导的肿瘤进化的早期阶段:一项探索性研究

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Oral cancers are the serious health problem in developing as well as developed world, and more so in India and other south Asian countries. Survival rate of these cancers, despite advances in treatment modalities are one of the poorest which is attributed to lack of reliable screening and early detection methods. The hamster buccal pouch (HBP) carcinogenesis model closely mimics human oral cancers. Optical spectroscopy methods are sensitive enough to detect subtle biochemical changes and thus hold great potential in early detection of cancers. However, efficacy of these techniques in classifying of sequential evolution of tumors has never been tested. Therefore, in this study, we have explored the feasibility of Raman spectroscopic classification of different stages of cancers in hamster model. Strong vibrational modes of lipids (1440, 1654, and 1746 cm~(-1)) are seen in control tissue spectra, whereas strong protein bands are seen in spectra of DMBA treated tissues. These differences were exploited to classify control and treated tissues using Linear Discriminant Analysis (LDA), Principle Component Analysis (PCA)-Limit test, Factorial Discriminant Analysis (FDA), Quadratic Discriminant Analysis (QDA), PLS-DA and non- linear decision tree methods. All these techniques have shown good classification between spectra of different stages of tumor evolution and results were further successfully verified by leave-one-out and single blinded methods. Thus findings of this study, first of its kind, demonstrate the feasibility of Raman spectroscopic detection of early changes in tumor evolution.
机译:在发展中国家和发达国家,口腔癌都是严重的健康问题,在印度和其他南亚国家尤其如此。尽管治疗方式有所进步,但这些癌症的存活率是最差的癌症之一,这归因于缺乏可靠的筛查和早期检测方法。仓鼠颊囊(HBP)致癌模型非常类似于人类口腔癌。光谱法足够灵敏以检测细微的生化变化,因此在癌症的早期检测中具有巨大的潜力。但是,从未测试过这些技术在对肿瘤的顺序演变进行分类中的功效。因此,在这项研究中,我们探索了仓鼠模型中不同阶段癌症的拉曼光谱分类的可行性。在对照组织光谱中观察到脂质的强振动模式(1440、1654和1746 cm〜(-1)),而在DMBA处理的组织光谱中观察到强蛋白带。利用线性判别分析(LDA),主成分分析(PCA)限度检验,因子判别分析(FDA),二次判别分析(QDA),PLS-DA和非线性决策,利用这些差异对对照组织和治疗组织进行分类树方法。所有这些技术均显示出了肿瘤演化不同阶段的光谱之间的良好分类,并且通过留一法和单盲法进一步成功地验证了结果。因此,这项研究的发现首次证明了拉曼光谱检测肿瘤发展早期变化的可行性。

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