Suppr超能文献

非均匀采样核磁共振的灵敏度

Sensitivity of nonuniform sampling NMR.

作者信息

Palmer Melissa R, Suiter Christopher L, Henry Geneive E, Rovnyak James, Hoch Jeffrey C, Polenova Tatyana, Rovnyak David

机构信息

†Department of Chemistry, Bucknell University, Lewisburg, Pennsylvania 17837, United States.

‡Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware 19716, United States.

出版信息

J Phys Chem B. 2015 Jun 4;119(22):6502-15. doi: 10.1021/jp5126415. Epub 2015 May 18.

Abstract

Many information-rich multidimensional experiments in nuclear magnetic resonance spectroscopy can benefit from a signal-to-noise ratio (SNR) enhancement of up to about 2-fold if a decaying signal in an indirect dimension is sampled with nonconsecutive increments, termed nonuniform sampling (NUS). This work provides formal theoretical results and applications to resolve major questions about the scope of the NUS enhancement. First, we introduce the NUS Sensitivity Theorem in which any decreasing sampling density applied to any exponentially decaying signal always results in higher sensitivity (SNR per square root of measurement time) than uniform sampling (US). Several cases will illustrate this theorem and show that even conservative applications of NUS improve sensitivity by useful amounts. Next, we turn to a serious limitation of uniform sampling: the SNR by US decreases for extending evolution times, and thus total experimental times, beyond 1.26T2 (T2 = signal decay constant). Thus, SNR and resolution cannot be simultaneously improved by extending US beyond 1.26T2. We find that NUS can eliminate this constraint, and we introduce the matched NUS SNR Theorem: an exponential sampling density matched to the signal decay always improves the SNR with additional evolution time. Though proved for a specific case, broader classes of NUS densities also improve SNR with evolution time. Applications of these theoretical results are given for a soluble plant natural product and a solid tripeptide (u-(13)C,(15)N-MLF). These formal results clearly demonstrate the inadequacies of applying US to decaying signals in indirect nD-NMR dimensions, supporting a broader adoption of NUS.

摘要

如果在间接维度中对衰减信号采用非连续增量进行采样(即非均匀采样,NUS),那么核磁共振波谱学中许多信息丰富的多维实验的信噪比(SNR)可提高约2倍。这项工作提供了正式的理论结果和应用,以解决有关NUS增强范围的主要问题。首先,我们引入了NUS灵敏度定理,即对任何指数衰减信号应用任何递减的采样密度,其灵敏度(每测量时间平方根的SNR)总是高于均匀采样(US)。几个例子将说明这个定理,并表明即使是保守地应用NUS也能显著提高灵敏度。接下来,我们转向均匀采样的一个严重限制:当演化时间(进而总实验时间)超过1.26T2(T2 = 信号衰减常数)时,均匀采样的SNR会降低。因此,将均匀采样扩展到超过1.26T2并不能同时提高SNR和分辨率。我们发现NUS可以消除这个限制,并引入了匹配NUS SNR定理:与信号衰减相匹配的指数采样密度总是能随着额外的演化时间提高SNR。尽管是针对特定情况证明的,但更广泛的NUS密度类别也能随着演化时间提高SNR。这些理论结果应用于一种可溶性植物天然产物和一种固体三肽(u-(13)C,(15)N-MLF)。这些正式结果清楚地表明了在间接nD-NMR维度中对衰减信号应用均匀采样的不足,支持更广泛地采用NUS。

相似文献

1
Sensitivity of nonuniform sampling NMR.非均匀采样核磁共振的灵敏度
J Phys Chem B. 2015 Jun 4;119(22):6502-15. doi: 10.1021/jp5126415. Epub 2015 May 18.
10
Knowledge-based nonuniform sampling in multidimensional NMR.基于知识的多维 NMR 非均匀采样。
J Biomol NMR. 2011 Jul;50(3):247-62. doi: 10.1007/s10858-011-9512-6. Epub 2011 May 29.

引用本文的文献

1
Enhancing Spectrometer Performance with Unsupervised Machine Learning.利用无监督机器学习提高光谱仪性能。
J Phys Chem B. 2024 Oct 24;128(42):10397-10407. doi: 10.1021/acs.jpcb.4c05109. Epub 2024 Oct 12.
3
5D solid-state NMR spectroscopy for facilitated resonance assignment.5D 固态核磁共振波谱学促进共振分配。
J Biomol NMR. 2023 Dec;77(5-6):229-245. doi: 10.1007/s10858-023-00424-5. Epub 2023 Nov 9.
4
Solution Structure of Poly(UG) RNA.聚(尿嘧啶核苷酸)RNA 的结构。
J Mol Biol. 2023 Dec 15;435(24):168340. doi: 10.1016/j.jmb.2023.168340. Epub 2023 Nov 2.
8
Primary Structure of Glycans by NMR Spectroscopy.通过 NMR 光谱学研究聚糖的一级结构。
Chem Rev. 2023 Feb 8;123(3):1040-1102. doi: 10.1021/acs.chemrev.2c00580. Epub 2023 Jan 9.

本文引用的文献

5
Time-resolved multidimensional NMR with non-uniform sampling.时分辨多维 NMR 与非均匀采样。
J Biomol NMR. 2014 Feb;58(2):129-39. doi: 10.1007/s10858-013-9811-1. Epub 2014 Jan 17.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验