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Interpolating and extrapolating with hmsIST - seeking a tmax for optimal sensitivity resolution and frequency accuracy

机译:使用hmsIST进行内插和外推-寻求tmax以获得最佳灵敏度分辨率和频率精度

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摘要

Non-Uniform Sampling (NUS) has the potential to exploit the optimal resolution of high-field NMR instruments. This is not possible in 3D and 4D NMR experiments when using traditional uniform sampling due to the long overall measurement time. Nominally, uniformly sampled (US) time domain data acquired to a maximum evolution time tmax can be extended to high resolution via a virtual maximum evolution time t*max while extrapolating with linear prediction or iterative soft thresholding (IST). At the high resolution obtainable with extrapolation of US data, however, the accuracy of peak positions is compromised as observed when comparing inter- and intra-residue peaks in a 3D HNCA experiment. However, the accuracy of peak positions is largely improved by spreading the same number of acquired time domain data points non-uniformly over a larger evolution time to an optimal tmax followed by extrapolation to a total t*max and processing the data with an appropriate reconstruction method, such as hmsIST. To explore the optimum value of experimentally measured tmax to be reached non-uniformly with a given number of sampling points we have created test situations of time-equivalent experiments and evaluate sensitivity and accuracy of peak positions. Here we use signal-to-maximum-noise ratio as the decisive measure of sensitivity. We find that both sensitivity and resolution are optimal when PoissonGap sampling to a tmax of about ½*T2*. Digital resolution is further enhanced by extrapolating the range of acquired time domain data to 2*T2* but without measuring experimental points beyond ½*T2*.
机译:非均匀采样(NUS)有潜力开发高磁场NMR仪器的最佳分辨率。当使用传统的均匀采样时,由于较长的总体测量时间,在3D和4D NMR实验中这是不可能的。名义上,采集到最大进化时间tmax的统一采样(US)时域数据可以通过虚拟的最大进化时间t * max扩展到高分辨率,同时通过线性预测或迭代软阈值(IST)进行推断。但是,在通过US数据外推可获得的高分辨率下,如在3D HNCA实验中比较残基间和残基内峰时所观察到的,峰位置的准确性会受到损害。但是,通过在较大的演化时间内将相同数量的获取的时域数据点不均匀地扩展到最佳tmax,然后外推到总t * max,并通过适当的重构处理数据,可以大大提高峰位置的准确性。方法,例如hmsIST。为了探索在给定数量的采样点下无法均匀达到的实验测量tmax的最佳值,我们创建了时间等效实验的测试情况,并评估了峰位置的灵敏度和准确性。在这里,我们使用信噪比作为灵敏度的决定性指标。我们发现,当PoissonGap采样的tmax约为½* T2 * 时,灵敏度和分辨率都是最佳的。通过将获取的时域数据范围外推到2 * T2 * ,而无需测量超过½* T2 * 的实验点,可以进一步提高数字分辨率。

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