树胶癌细胞DNA/RNA -抗癌纳米药物配体结构测定用单、多、零、双量子相关实验的二维核磁共振分子线形分析

A. Heidari, R. Gobato
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引用次数: 12

摘要

在目前的研究中,利用二维核磁共振分子线形状分析的单量子、多量子、零量子和双量子相关实验,研究了牙龈癌细胞的DNA/RNA -抗癌纳米药物配体结构的测定。然而,我们和其他人已经证明,使用单量子、多量子、零量子和双量子相关实验的二维NMR分子线形状分析来确定牙龈癌细胞的DNA/RNA -抗癌纳米药物配体结构的选择对组织分类结果有很大的影响。除了开发光谱预处理的最佳实践技术外,在开发牙龈癌细胞的分类DNA/RNA -抗癌纳米药物配体结构测定时,必须注意使用单、多、零和双量子相关实验的二维NMR分子线形状分析进行诊断评估。在离体标本上建立的单量子、多量子、零量子和双量子相关实验的二维NMR分子线形分析确定牙龈癌细胞的DNA/RNA -抗癌纳米药物配体结构,是否适用于体内组织,还需要进行验证研究。机器学习牙龈癌细胞的DNA/RNA -抗癌纳米药物配体结构测定与单量子、多量子、零量子和双量子相关实验的二维核磁共振分子线形状分析有望实现牙龈癌的自动化识别和诊断。深度学习训练,使用大量的光谱,也可以识别龈癌类型之间的分子模式,帮助边缘检测,并成为龈癌侵袭性的预测因子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DNA/RNA of gum cancer cells-anti–cancer nano drugs ligands structure determination with the two–dimensional NMR molecular line shape analysis of single, multiple, zero and double quantum correlation experiments
In the current research, DNA/RNA of gum cancer cells—anti–cancer Nano drugs ligands structure determination with the two–dimensional NMR molecular line shape analysis of single, multiple, zero and double quantum correlation experiments are investigated. However, it has been demonstrated by us and others that the choice of DNA/RNA of gum cancer cells—anti–cancer Nano drugs ligands structure determination with the two–dimensional NMR molecular line shape analysis of single, multiple, zero and double quantum correlation experiments can greatly influence tissue classification results. In addition to developing best–practice techniques for spectral preprocessing, care must be taken when developing classification DNA/RNA of gum cancer cells—anti–cancer Nano drugs ligands structure determination with the two–dimensional NMR molecular line shape analysis of single, multiple, zero and double quantum correlation experiments for diagnostic evaluation. Validation studies need to be performed to confirm that DNA/RNA of gum cancer cells—anti–cancer Nano drugs ligands structure determination with the two–dimensional NMR molecular line shape analysis of single, multiple, zero and double quantum correlation experiments developed on ex vivo specimens are applicable to in vivo tissues. Machine learning DNA/RNA of gum cancer cells—anti–cancer Nano drugs ligands structure determination with the two–dimensional NMR molecular line shape analysis of single, multiple, zero and double quantum correlation experiments hold the promise of automating the identification and diagnosis of gum cancer. Deep learning training, using large numbers of spectra, may also identify molecular patterns among gum cancer types, aid in margin detection, and become predictors of the aggressiveness of the gum cancer.
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