Performance Tuning Non-Uniform Sampling for Sensitivity Enhancement of Signal-Limited Biological NMR

Non-uniform sampling (NUS) has been established as a route to obtaining true sensitivity enhancements when recording indirect dimensions of decaying signals in the same total experimental time as traditional uniform incrementation of the indirect evolution period. Theory and experiments have shown that NUS can yield up to two-fold improvements in the intrinsic signal-to-noise ratio (SNR) of each dimension, while even conservative protocols can yield 20-40 % improvements in the intrinsic SNR of NMR data. Applications of biological NMR that can benefit from these improvements are emerging, and in this work we develop some practical aspects of applying NUS nD-NMR to studies that approach the traditional detection limit of nD-NMR spectroscopy. Conditions for obtaining high NUS sensitivity enhancements are considered here in the context of enabling H-1,N-15-HSQC experiments on natural abundance protein samples and H-1,C-13-HMBC experiments on a challenging natural product. Through systematic studies we arrive at more precise guidelines to contrast sensitivity enhancements with reduced line shape constraints, and report an alternative sampling density based on a quarter-wave sinusoidal distribution that returns the highest fidelity we have seen to date in line shapes obtained by maximum entropy processing of non-uniformly sampled data.

Sensitivity Gains, Linearity, and Spectral Reproducibility in Nonuniformly Sampled Multidimensional MAS NMR Spectra of High Dynamic Range

Recently, we have demonstrated that considerable inherent sensitivity gains are attained in MAS NMR spectra acquired by nonuniform sampling (NUS) and introduced maximum entropy interpolation (MINT) processing that assures the linearity of transformation between the time and frequency domains. In this report, we examine the utility of the NUS/MINT approach in multidimensional datasets possessing high dynamic range, such as homonuclear C-13-C-13 correlation spectra. We demonstrate on model compounds and on 1-73-(U-C-13,N-15)/74-108-(U-N-15) E. coli thioredoxin reassembly, that with appropriately constructed 50 % NUS schedules inherent sensitivity gains of 1.7-2.1-fold are readily reached in such datasets. We show that both linearity and line width are retained under these experimental conditions throughout the entire dynamic range of the signals. Furthermore, we demonstrate that the reproducibility of the peak intensities is excellent in the NUS/MINT approach when experiments are repeated multiple times and identical experimental and processing conditions are employed. Finally, we discuss the principles for design and implementation of random exponentially biased NUS sampling schedules for homonuclear C-13-C-13 MAS correlation experiments that yield high-quality artifact-free datasets.

Development and implementation of a web-enabled 3D consultation tool for breast augmentation surgery based on 3D-image reconstruction of 2D pictures

Producing a rich, personalized Web-based consultation tool for plastic surgeons and patients is challenging.

Novel sst2-selective somatostatin agonists. Three-dimensional consensus structure by NMR

The 3D NMR structures of six octapeptide agonist analogues of somatostatin (SRIF) in the free form are described. These analogues, with the basic sequence H-DPhe/Phe2-c[Cys3-Xxx7-DTrp8-Lys9-Thr10-Cys14]-Thr-NH2 (the numbering refers to the position in native SRIF), with Xxx7 being Ala/Aph, exhibit potent and highly selective binding to human SRIF type 2 (sst2) receptors. The backbone of these sst2-selective analogues have the usual type-II' beta-turn reported in the literature for sst2/3/5-subtype-selective analogues. Correlating the biological results and NMR studies led to the identification of the side chains of DPhe2, DTrp8, and Lys9 as the necessary components of the sst2 pharmacophore. This is the first study to show that the aromatic ring at position 7 (Phe7) is not critical for sst2 binding and that it plays an important role in sst3 and sst5 binding. This pharmacophore is, therefore, different from that proposed by others for sst2/3/5 analogues.

Conformational analysis of a potent SSTR3-selective somatostatin analogue by NMR in water solution

The three-dimensional structure of a potent SSTR3-selective analogue of somatostatin, cyclo(3-14)H-Cys(3)-Phe(6)-Tyr(7)-D-Agl(8)(N(beta) Me, 2-naphthoyl)-Lys(9)-Thr(10)-Phe(11)-Cys(14)-OH (des-AA(1, 2, 4, 5, 12, 13)[Tyr(7), D-Agl(8)(N(beta) Me, 2-naphthoyl)]-SRIF) (peptide 1) has been determined by (1)H NMR in water and molecular dynamics (MD) simulations. The peptide exists in two conformational isomers differing mainly by the cis/trans isomerization of the side chain in residue 8. The structure of 1 is compared with the consensus structural motifs of other somatostatin analogues that bind predominantly to SSTR1, SSTR2/SSTR5 and SSTR4 receptors, and to the 3D structure of a non-selective SRIF analogue, cyclo(3-14)H-Cys(3)-Phe(6)-Tyr(7)-D-2Nal(8)-Lys(9)-Thr(10)-Phe(11)-Cys(14)-OH (des-AA(1, 2, 4, 5, 12, 13)[Tyr(7), D-2Nal(8)]-SRIF) (peptide 2). The structural determinant factors that could explain selectivity of peptide 1 for SSTR3 receptors are discussed.

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.