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Compressed sensing: Reconstruction of non-uniformly sampled multidimensional NMR data
© 2018 Wiley Periodicals, Inc. Nuclear magnetic resonance (NMR) spectroscopy is widely used across the physical, chemical, and biological sciences. A core component of NMR studies is multidimensional experiments, which enable correlation of properties from one or more NMR-active nuclei. In high-resolution biomolecular NMR, common nuclei are1H,15N, and13C, and triple resonance experiments using these three nuclei form the backbone of NMR structural studies. In other fields, a range of other nuclei may be used. Multidimensional NMR experiments provide unparalleled information content, but this comes at the price of long experiment times required to achieve the necessary resolution and sensitivity. Non-uniform sampling (NUS) techniques to reduce the required data sampling have existed for many decades. Recently, such techniques have received heightened interest due to the development of compressed sensing (CS) methods for reconstructing spectra from such NUS datasets. When applied jointly, these methods provide a powerful approach to dramatically improve the resolution of spectra per time unit and under suitable conditions can also lead to signal-to-noise ratio improvements. In this review, we explore the basis of NUS approaches, the fundamental features of NUS reconstruction using CS and applications based on CS approaches including the benefits of expanding the repertoire of biomolecular NMR experiments into higher dimensions. We discuss some of the recent algorithms and software packages and provide practical tips for recording and processing NUS data by CS
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Improving resolution in multidimensional NMR using random quadrature detection with compressed sensing reconstruction.
NMR spectroscopy is central to atomic resolution studies in biology and chemistry. Key to this approach are multidimensional experiments. Obtaining such experiments with sufficient resolution, however, is a slow process, in part since each time increment in every indirect dimension needs to be recorded twice, in quadrature. We introduce a modified compressed sensing (CS) algorithm enabling reconstruction of data acquired with random acquisition of quadrature components in gradient-selection NMR. We name this approach random quadrature detection (RQD). Gradient-selection experiments are essential to the success of modern NMR and with RQD, a 50 % reduction in the number of data points per indirect dimension is possible, by only acquiring one quadrature component per time point. Using our algorithm (CSRQD), high quality reconstructions are achieved. RQD is modular and combined with non-uniform sampling we show that this provides increased flexibility in designing sampling schedules leading to improved resolution with increasing benefits as dimensionality of experiments increases, with particular advantages for 4- and higher dimensional experiments.Part of this work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council.This is the final version of the article. It first appeared from Springer via https://doi.org/10.1007/s10858-016-0062-
Spin asymmetries for electron-thallium scattering calculated with the relativistic convergentclose-coupling method
Spin asymmetries for elastic and inelastic scattering of electrons from thallium are presented. Thalliumis a heavy target (Z 81) and the spin asymmetries can be caused by relativistic effects (spin-orbit interactions) in addition to exchange effects
Accommodation to hyperpolarization of human axons assessed in the frequency domain
Human axonsin vivowere subjected to subthreshold currents with a threshold-"ZAP" profile (Impedance [ Z: ] A: mplitude P: rofile) to allow the use of frequency domain techniques to determine the propensity for resonant behavior, and to clarify the relative contributions of different ion channels to their low-frequency responsiveness. Twenty-four studies were performed on the motor and sensory axons in 6 subjects. The response to oscillatory currents was tested between 'DC' and 16 Hz. A resonant peak at ~2 to 2.5 Hz was found in the response of hyperpolarized axons, but there was only a small broad response in axons at resting membrane potential (RMP). A mathematical model of axonal excitability developed using DC pulses provided a good fit to the frequency response for human axons, and indicated that the hyperpolarization-activated currentIh, and the slow potassium currentIKsare principally responsible for the resonance. However the results indicate that if axons are hyperpolarized more than -60% of resting threshold, the only conductances that are appreciably active areIhand the leak conductance - i.e., that the activity of these conductances can be studiedin vivovirtually in isolation at hyperpolarized membrane potentials. Given that the leak conductance dampens resonance it is suggested that the -60% hyperpolarization used here is optimal forIh As expected differences between the frequency responses of motor and sensory axons were present and best explained by reduced GKs, up-modulation ofIhand increased persistent Na(+)current,INaP(due to depolarization of RMP) in sensory axons
Nonperturbative electron-ion scattering theory incorporating the Møller interaction
We present the first calculations that investigate the effects of both the Møller interaction and close-coupling in the calculation of electron-impact excitation cross sections. Electron scattering from U 91+ is used as a test case. The RCCC method is nonperturbative and we emphasise the restrictions and subsequent limitations associated with employing the Møller interaction in the RCCC method
Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off
Bundling of graph edges (node-to-node connections) is a common technique to
enhance visibility of overall trends in the edge structure of a large graph
layout, and a large variety of bundling algorithms have been proposed. However,
with strong bundling, it becomes hard to identify origins and destinations of
individual edges. We propose a solution: we optimize edge coloring to
differentiate bundled edges. We quantify strength of bundling in a flexible
pairwise fashion between edges, and among bundled edges, we quantify how
dissimilar their colors should be by dissimilarity of their origins and
destinations. We solve the resulting nonlinear optimization, which is also
interpretable as a novel dimensionality reduction task. In large graphs the
necessary compromise is whether to differentiate colors sharply between locally
occurring strongly bundled edges ("local bundles"), or also between the weakly
bundled edges occurring globally over the graph ("global bundles"); we allow a
user-set global-local tradeoff. We call the technique "peacock bundles".
Experiments show the coloring clearly enhances comprehensibility of graph
layouts with edge bundling.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
In vivo assessment of muscle membrane properties in myotonic dystrophy
INTRODUCTION: Myotonia in myotonic dystrophy types 1 (DM1) and 2 (DM2) is generally attributed to reduced chloride channel conductance. We used muscle velocity recovery cycles (MVRCs) to investigate muscle membrane properties in DM1 and DM2, with comparisons with myotonia congenita (MC). METHODS: MVRCs and responses to repetitive stimulation were compared between patients with DM1 (n=18), DM2 (n=5), MC (n=18), and normal controls (n=20). RESULTS: Both DM1 and DM2 showed enhanced late supernormality after multiple conditioning stimuli, indicating delayed repolarization as in MC. Contrary to MC, however, DM1 showed reduced early supernormality after multiple conditioning stimuli, and weak DM1 patients also showed abnormally slow latency recovery after repetitive stimulation. DISCUSSION: These findings support impaired chloride conductance in both DM1 and DM2. The early supernormality changes indicate that sodium currents were reduced in DM1, while the weakness-associated slow recovery after repetitive stimulation may provide an indication of reduced Na(+) /K(+) -ATPase activation
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