Alan S. Stern

User-Level Implementations of Read-Copy Update

Read-copy update (RCU) is a synchronization technique that often replaces reader-writer locking because RCUs read-side primitives are both wait-free and an order of magnitude faster than uncontended locking. Although RCU updates are relatively heavy weight, the importance of read-side performance is increasing as computing systems become more responsive to changes in their environments. RCU is heavily used in several kernel-level environments. Unfortunately, kernel-level implementations use facilities that are often unavailable to user applications. The few prior user-level RCU implementations either provided inefficient read-side primitives or restricted the application architecture. This paper fills this gap by describing efficient and flexible RCU implementations based on primitives commonly available to user-level applications. Finally, this paper compares these RCU implementations with each other and with standard locking, which enables choosing the best mechanism for a given workload. This work opens the door to widespread user-application use of RCU.

Application of nonlinear sampling schemes to COSY-type spectra

SummaryNonlinear sampling along the t1 dimension is applied to COSY-type spectra. The sine dependence of the time domain signals for the cross peaks is matched by a nonlinear sampling scheme that samples most densely around the maximum of the sine function. Data are processed by maximum entropy reconstruction, using a modified implementation of the ‘Cambridge’ algorithm of Skilling and Bryan. The procedure is demonstrated for P.E.COSY spectra recorded on a cyclic hexapeptide and on a 126-residue domain of the protein villin. The number of t1 values in the nonlinearly sampled experiments was reduced by a factor of four compared to linear sampling. The sensitivity and resolution of the resulting spectra are comparable to those achieved by conventional methods. The method described can thus significantly reduce the measuring time for COSY-type spectra.

Improved resolution in triple-resonance spectra by nonlinear sampling in the constant-time domain

SummaryNonlinear sampling along the constant-time dimension is applied to the constant-time HNCO spectrum of the dimerization domain of Ga14. Nonlinear sampling was used for the nitrogen dimension, while the carbon and proton dimensions were sampled linearly. A conventional ct-HNCO spectrum is compared with a nonlinearly sampled spectrum, where the gain in experiment time obtained from nonlinear sampling is used to increase the resolution in the carbonyl dimension. Nonlinearly sampled data are processed by maximum entropy reconstruction. It is shown that the nonlinearly sampled spectrum has a higher resolution, although it was recorded in less time. The constant intensity of the signal in the constant-time dimension allows for a variety of sampling schedules. A schedule of randomly distributed sampling points yields the best results. This general method can be used to significantly increase the quality of heteronuclear constant-time spectra.

De novo Backbone and Sequence Design of an Idealized α/β-barrel Protein: Evidence of Stable Tertiary Structure

We have designed, synthesized, and characterized a 216 amino acid residue sequence encoding a putative idealized α/β-barrel protein. The design was elaborated in two steps. First, the idealized backbone was defined with geometric parameters representing our target fold: a central eight parallel-stranded β-sheet surrounded by eight parallel α-helices, connected together with short structural turns on both sides of the barrel. An automated sequence selection algorithm, based on the dead-end elimination theorem, was used to find the optimal amino acid sequence fitting the target structure. A synthetic gene coding for the designed sequence was constructed and the recombinant artificial protein was expressed in bacteria, purified and characterized. Far-UV CD spectra with prominent bands at 222 nm and 208 nm revealed the presence of α-helix secondary structures (50%) in fairly good agreement with the model. A pronounced absorption band in the near-UV CD region, arising from immobilized aromatic side-chains, showed that the artificial protein is folded in solution. Chemical unfolding monitored by tryptophan fluorescence revealed a conformational stability (ΔGH_2O) of 35 kJ/mol. Thermal unfolding monitored by near-UV CD revealed a cooperative transition with an apparent T_m of 65 °C. Moreover, the artificial protein did not exhibit any affinity for the hydrophobic fluorescent probe 1-anilinonaphthalene-8-sulfonic acid (ANS), providing additional evidence that the artificial barrel is not in the molten globule state, contrary to previously designed artificial a/ b-barrels. Finally, ^1H NMR spectra of the folded and unfolded proteins provided evidence for specific interactions in the folded protein. Taken together, the results indicate that the de novo designed α/β-barrel protein adopts a stable three-dimensional structure in solution. These encouraging results show that de novo design of an idealized protein structure of more than 200 amino acid residues is now possible, from construction of a particular backbone conformation to determination of an amino acid sequence with an automated sequence selection algorithm.

Maximum entropy reconstruction of complex (phase-sensitive) spectra

Abstract There is no general agreement on the definition of the entropy of a complex spectrum. We consider a number of possible definitions for use in maximum entropy reconstruction, comparing their analytical properties and the quality of spectrum reconstructions computed for synthetic and experimental NMR data. On the basis of this comparison, we conclude that the entropy of the power spectrum is not well suited for spectrum reconstruction in NMR; conversely, there is one definition which appears to be better suited in every respect than the others considered.

Nonuniform Sampling and Maximum Entropy Reconstruction in Multidimensional NMR

NMR spectroscopy is one of the most powerful and versatile analytic tools available to chemists. The discrete Fourier transform (DFT) played a seminal role in the development of modern NMR, including the multidimensional methods that are essential for characterizing complex biomolecules. However, it suffers from well-known limitations: chiefly the difficulty in obtaining high-resolution spectral estimates from short data records. Because the time required to perform an experiment is proportional to the number of data samples, this problem imposes a sampling burden for multidimensional NMR experiments. At high magnetic field, where spectral dispersion is greatest, the problem becomes particularly acute. Consequently multidimensional NMR experiments that rely on the DFT must either sacrifice resolution in order to be completed in reasonable time or use inordinate amounts of time to achieve the potential resolution afforded by high-field magnets. Maximum entropy (MaxEnt) reconstruction is a non-Fourier method of spectrum analysis that can provide high-resolution spectral estimates from short data records. It can also be used with nonuniformly sampled data sets. Since resolution is substantially determined by the largest evolution time sampled, nonuniform sampling enables high resolution while avoiding the need to uniformly sample at large numbers of evolution times. The Nyquist sampling theorem does not apply to nonuniformly sampled data, and artifacts that occur with the use of nonuniform sampling can be viewed as frequency-aliased signals. Strategies for suppressing nonuniform sampling artifacts include the careful design of the sampling scheme and special methods for computing the spectrum. Researchers now routinely report that they can complete an N-dimensional NMR experiment 3(N-1) times faster (a 3D experiment in one ninth of the time). As a result, high-resolution three- and four-dimensional experiments that were prohibitively time consuming are now practical. Conversely, tailored sampling in the indirect dimensions has led to improved sensitivity. Further advances in nonuniform sampling strategies could enable further reductions in sampling requirements for high resolution NMR spectra, and the combination of these strategies with robust non-Fourier methods of spectrum analysis (such as MaxEnt) represent a profound change in the way researchers conduct multidimensional experiments. The potential benefits will enable more advanced applications of multidimensional NMR spectroscopy to study biological macromolecules, metabolomics, natural products, dynamic systems, and other areas where resolution, sensitivity, or experiment time are limiting. Just as the development of multidimensional NMR methods presaged multidimensional methods in other areas of spectroscopy, we anticipate that nonuniform sampling approaches will find applications in other forms of spectroscopy.

A non-uniformly sampled 4D HCC(CO)NH-TOCSY experiment processed using maximum entropy for rapid protein sidechain assignment.

One of the stiffest challenges in structural studies of proteins using NMR is the assignment of sidechain resonances. Typically, a panel of lengthy 3D experiments are acquired in order to establish connectivities and resolve ambiguities due to overlap. We demonstrate that these experiments can be replaced by a single 4D experiment that is time-efficient, yields excellent resolution, and captures unique carbon-proton connectivity information. The approach is made practical by the use of non-uniform sampling in the three indirect time dimensions and maximum entropy reconstruction of the corresponding 3D frequency spectrum. This 4D method will facilitate automated resonance assignment procedures and it should be particularly beneficial for increasing throughput in NMR-based structural genomics initiatives.

Sparse sampling methods in multidimensional NMR

Although the discrete Fourier transform played an enabling role in the development of modern NMR spectroscopy, it suffers from a well-known difficulty providing high-resolution spectra from short data records. In multidimensional NMR experiments, so-called indirect time dimensions are sampled parametrically, with each instance of evolution times along the indirect dimensions sampled via separate one-dimensional experiments. The time required to conduct multidimensional experiments is directly proportional to the number of indirect evolution times sampled. Despite remarkable advances in resolution with increasing magnetic field strength, multiple dimensions remain essential for resolving individual resonances in NMR spectra of biological macromolecues. Conventional Fourier-based methods of spectrum analysis limit the resolution that can be practically achieved in the indirect dimensions. Nonuniform or sparse data collection strategies, together with suitable non-Fourier methods of spectrum analysis, enable high-resolution multidimensional spectra to be obtained. Although some of these approaches were first employed in NMR more than two decades ago, it is only relatively recently that they have been widely adopted. Here we describe the current practice of sparse sampling methods and prospects for further development of the approach to improve resolution and sensitivity and shorten experiment time in multidimensional NMR. While sparse sampling is particularly promising for multidimensional NMR, the basic principles could apply to other forms of multidimensional spectroscopy.

Data Sampling in Multidimensional NMR: Fundamentals and Strategies

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (free induction decay) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform, the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records were already well understood, and despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. In this chapter we review the fundamentals of uniform and nonuniform sampling methods in one- and multidimensional NMR.

Multiple-quantum magic-angle spinning spectroscopy using nonlinear sampling.

NMR spectroscopy is a relatively insensitive technique and many biomolecular applications operate near the limits of sensitivity and resolution. A particularly challenging example is detection of the quadrupolar nucleus 17O, due to its low natural abundance, large quadrupole couplings, and low gyromagnetic ratio. Yet the chemical shift of 17O spans almost 1000 ppm in organic molecules and it serves as a potentially unique reporter of hydrogen bonding in peptides, nucleic acids, and water, and as a valuable complement to 13C and 15N NMR. Recent developments including the multiple-quantum magic-angle spinning (MQMAS) experiment have enabled the detection of 17O in biological solids, but very long data acquisitions are required to achieve sufficient sensitivity and resolution. Here, we perform nonlinear sampling in the indirect dimension of MQMAS experiments to substantially reduce the total acquisition time and improve sensitivity and resolution. Nonlinear sampling prevents the use of the discrete Fourier transform; instead, we employ maximum entropy (MaxEnt) reconstruction. Nonlinearly sampled MQMAS spectra are shown to provide high resolution and sensitivity in several systems, including lithium sulfate monohydrate (LiSO(4)-H(2)17O) and L-asparagine monohydrate (H(2)17O). The combination of nonlinear sampling and MaxEnt reconstruction promises to make the application of 17O MQMAS practical in a wider range of biological systems.