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使用稀疏重建方法分析的多维手风琴数据的最优非均匀采样进行快速核磁共振弛豫测量

Rapid NMR Relaxation Measurements Using Optimal Nonuniform Sampling of Multidimensional Accordion Data Analyzed by a Sparse Reconstruction Method.

作者信息

Carlström Göran, Elvander Filip, Swärd Johan, Jakobsson Andreas, Akke Mikael

机构信息

Department of Mathematical Statistics , Lund University , Box 118, SE-22100 Lund , Sweden.

出版信息

J Phys Chem A. 2019 Jul 11;123(27):5718-5723. doi: 10.1021/acs.jpca.9b04152. Epub 2019 Jun 26.

Abstract

Nonuniform sampling (NUS) of multidimensional NMR data offers significant time savings while improving spectral resolution or increasing sensitivity per unit time. However, NUS has not been widely used for quantitative analysis because of the nonlinearity of most methods used to model NUS data, which leads to problems in estimating signal intensities, relaxation rate constants, and their error bounds. Here, we present an approach that avoids these limitations by combining accordion spectroscopy and NUS in the indirect dimensions of multidimensional spectra and then applying sparse exponential mode analysis, which is well suited for analyzing accordion-type relaxation data in a NUS context. By evaluating the Cramér-Rao lower bound of the variances of the estimated relaxation rate constants, we achieve a robust benchmark for the underlying reconstruction model. Furthermore, we design NUS schemes optimized with respect to the information theoretical lower bound of the error in the parameters of interest, given a specified number of sampling points. The accordion-NUS method compares favorably with conventional relaxation experiments in that it produces identical results, within error, while shortening the length of the experiment by an order of magnitude. Thus, our approach enables rapid acquisition of NMR relaxation data for optimized use of spectrometer time or accurate measurements on samples of limited lifetime.

摘要

多维核磁共振(NMR)数据的非均匀采样(NUS)可显著节省时间,同时提高光谱分辨率或增加单位时间内的灵敏度。然而,由于用于对NUS数据进行建模的大多数方法具有非线性,导致在估计信号强度、弛豫速率常数及其误差范围时出现问题,因此NUS尚未广泛用于定量分析。在此,我们提出一种方法,通过在多维光谱的间接维度中将手风琴光谱学与NUS相结合,然后应用稀疏指数模式分析来避免这些限制,该分析非常适合在NUS背景下分析手风琴型弛豫数据。通过评估估计的弛豫速率常数方差的克拉美 - 罗下界,我们为基础重建模型建立了一个稳健的基准。此外,在给定指定数量的采样点的情况下,我们设计了针对感兴趣参数误差的信息理论下界进行优化的NUS方案。手风琴 - NUS方法与传统弛豫实验相比具有优势,因为它在误差范围内产生相同的结果,同时将实验长度缩短了一个数量级。因此,我们的方法能够快速获取NMR弛豫数据,以便优化光谱仪时间的使用或对有限寿命的样品进行准确测量。

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