Institute of Structural and Molecular Biology, University College London and Birkbeck College, London WC1E 6BT, UK.
J Magn Reson. 2012 Jun;219:46-52. doi: 10.1016/j.jmr.2012.04.013. Epub 2012 May 1.
Non-uniform weighted sampling (NUWS) is a sampling strategy, related to non-uniform sampling (NUS) in the limit of long acquisition times, in which each indirect increment of a multidimensional spectrum is sampled multiple times according to some weighting function. As the spectrum is fully sampled it can be processed in a conventional manner by the discrete Fourier transform, making the analysis of sensitivity much more straightforward than for NUS data. Previously, 2-3 fold increases in signal-to-noise ratio (SNR) have been reported using NUWS. However, as the sampling schedule acts as a window function, the observed SNR must be compared with uniformly sampled data apodized using the same weighting function. On doing this, we calculate more modest improvements of 10-20% in SNR, and these are verified experimentally for spectra of α-synuclein and YFP. Nevertheless, we prove that NUWS always improves the sensitivity compared with identically processed uniformly sampled data, and when combined with rapid recycling experiments such as the SOFAST-HMQC, NUWS methods have the potential to make a useful and practical contribution to sensitivity-limited measurements.
非均匀加权采样(NUWS)是一种采样策略,与长时间采集条件下的非均匀采样(NUS)有关,其中多维光谱的每个间接增量根据某些加权函数多次采样。由于对光谱进行了完全采样,因此可以通过离散傅里叶变换以常规方式对其进行处理,这使得灵敏度分析比 NUS 数据更为直接。先前已经报道了使用 NUWS 可将信号与噪声比(SNR)提高 2-3 倍。但是,由于采样方案充当了窗口函数,因此必须使用相同的加权函数对观察到的 SNR 与均匀采样数据进行加权处理。通过这样做,我们计算出 SNR 提高了 10-20%,并且针对α-突触核蛋白和 YFP 的光谱进行了实验验证。尽管如此,我们证明 NUWS 始终比经过相同处理的均匀采样数据具有更高的灵敏度,并且当与诸如 SOFAST-HMQC 之类的快速循环实验相结合时,NUWS 方法有可能为灵敏度受限的测量做出有用且实用的贡献。