Capillary HPLC-NMR Coupling: High-Resolution (1)H NMR Spectroscopy in the Nanoliter Scale

Coupling HPLC and NMR is one of the most powerful techniques for simultaneous separation and structural elucidation of unknown compounds in mixtures. To date, however, minimizing the detection volume, as is required when coupling NMR with miniaturized separation techniques, has been accompanied by a dramatic loss in resolution of the NMR spectra. Here, we report on the coupling of gradient capillary HPLC with on-column, high-resolution NMR detection. On-line stopped-flow and static (1)H NMR spectra were acquired with capillary columns of 75-315 μm i.d. With detection over a length of 1.2 cm, cell volumes cover a range of 50-900 nL. An on-line-detected NMR separation of dansylated amino acids was carried out in a 315 μm i.d. fused silica capillary packed to a length of 12 cm with C(18) stationary phase. The low solvent consumption makes the use of fully deuterated solvents economically feasible. NMR spectra with resolution on the order of 3 Hz were obtained using a 50 nL detection cell to measure 1.1 nmol of dansylated γ-aminobutyric acid under static conditions in a 75 μm i.d. capillary.     

Glu227-->Lys substitution in the acidic loop of major histocompatibility complex class I alpha 3 domain distinguishes low avidity CD8 coreceptor and avidity-enhanced CD8 accessory functions

Cytotoxic T lymphocyte (CTL) activation requires specific T cell receptor (TCR)-class I major histocompatibility complex (MHC) antigen complex interactions as well as the participation of coreceptor or accessory molecules on the surface of CTL. CD8 can serve as a coreceptor in that it binds to the same MHC class I molecules as the TCR to facilitate efficient TCR signaling. In addition, CD8 can be "activated" by TCR stimulation to bind to class I molecules with high avidity, including class I not recognized by the TCR as antigenic complexes (non-antigen [Ag] class I), to augment CTL responses and thus serve an accessory molecule function. A Glu/Asp227-->Lys substitution in the class I alpha 3 domain acidic loop abrogates lysis of target cells expressing these mutant molecules by alloreactive CD8-dependent CTL. Lack of response is attributed to the destruction of the CD8 binding site in the alpha 3 domain which is likely to disrupt CD8 coreceptor function. The relative importance of the class I alpha 3 domain acidic loop Glu227 in coreceptor as opposed to accessory functions of CD8 is unclear. To address this issue, we examined CTL adhesion and degranulation in response to immobilized class I-peptide complexes formed in vitro from antigenic peptides and purified class I molecules containing wild-type or Glu227-->Lys substituted alpha 3 domains. The alpha 3 domain mutant class I-peptide complexes were bound by CTL and triggered degranulation, however to much lower levels than wild-type class I-peptide complexes. In further experiments, it is directly demonstrated that the alpha 3 domain mutant class I molecules, which lack the Glu227 CD8 binding site, still serve as TCR-activated, avidity-enhanced CD8 accessory ligands. However, mutant class I peptide Ag complexes failed to effectively serve as CD8 coreceptor ligands to initiate TCR-dependent signals required to induce avidity-enhanced CD8 binding to coimmobilized non-Ag class I molecules. Thus the Glu227-->Lys mutation effectively distinguishes CD8 coreceptor and avidity-enhanced CD8 accessory functions.     

A SIMD-efficient 14 instruction shader program for high-throughput microtriangle rasterization

This paper shows that breaking the barrier of 1 triangle/clock rasterization rate for microtriangles in modern GPU architectures in an efficient way is possible. The fixed throughput of the special purpose culling and triangle setup stages of the classic pipeline limits the GPU scalability to rasterize many triangles in parallel when these cover very few pixels. In contrast, the shader core counts and increasing GFLOPs in modern GPUs clearly suggests parallelizing this computation entirely across multiple shader threads, making use of the powerful wide-ALU instructions. In this paper, we present a very efficient SIMD-like rasterization code targeted at very small triangles that scales very well with the number of shader cores and has higher performance than traditional edge equation based algorithms. We have extended the ATTILA GPU shader ISA (del Barrioet al. in IEEE International Symposium on Performance Analysis of Systems and Software, pp. 231–241, 2006) with two fixed point instructions to meet the rasterization precision requirement. This paper also introduces a novel subpixel Bounding Box size optimization that adjusts the bounds much more finely, which is critical for small triangles, and doubles the 2×2-pixel stamp test efficiency. The proposed shader rasterization program can run on top of the original pixel shader program in such a way that selected fragments are rasterized, attribute interpolated and pixel shaded in the same pass. Our results show that our technique yields better performance than a classic rasterizer at 8 or more shader cores, with speedups as high as 4× for 16 shader cores.     

3-D B-spline Wavelet-Based Local Standard Deviation (BWLSD): Its Application to Edge Detection and Vascular Segmentation in Magnetic Resonance Angiography

Extracting reliable image edge information is crucial for active contour models as well as vascular segmentation in magnetic resonance angiography (MRA). However, conventional edge detection techniques, such as gradient-based methods and wavelet-based methods, are incapable of returning reliable detection responses from low contrast edges in the images. In this paper, we propose a novel edge detection method by combining B-spline wavelet magnitude with standard deviation inside local region. It is proved theoretically and demonstrated experimentally in this paper that the new edge detection method, namely BWLSD, is able to give consistent and reliable strengths for edges with different image contrasts. Moreover, the relationship between the size of local region with non-zero wavelet magnitudes and the scale of wavelet function is established. This relationship indicates that if the scale of the adopted wavelet function is s, then the size of a local region, from which the standard deviation is estimated, should be 2s−1. The proposed edge detection technique is embedded in FLUX, namely, BWLSD-FLUX, for vascular segmentation in MRA image volumes. Experimental results on clinical images show that, as compared with the conventional FLUX, BWLSD-FLUX can achieve better segmentations of vasculatures in MRA images under same initial conditions.     

Anisotropic Smoothness Classes: From Finite Element Approximation to Image Models

We propose and study quantitative measures of smoothness f ? A(f) which are adapted to anisotropic features such as edges in images or shocks in PDE’s. These quantities govern the rate of approximation by adaptive finite elements, when no constraint is imposed on the aspect ratio of the triangles, the simplest example being \(A_{p}(f)=\|\sqrt{|\mathrm{det}(d^{2}f)|}\|_{L^{\tau}}\) which appears when approximating in the L ^p norm by piecewise linear elements when \(\frac{1}{\tau}=\frac{1}{p}+1\). The quantities A(f) are not semi-norms, and therefore cannot be used to define linear function spaces. We show that these quantities can be well defined by mollification when f has jump discontinuities along piecewise smooth curves. This motivates for using them in image processing as an alternative to the frequently used total variation semi-norm which does not account for the smoothness of the edges.     

Approximated approximations for SAO

We propose to replace a number of popular approximations by their diagonal quadratic Taylor series expansions. The resulting separable quadratic approximations are easily convexified, and are well suited for use in dual sequential approximate optimization (SAO) algorithms. Global convergence of the resulting SAO algorithms may be enforced in a natural way using conservatism. The approximated approximation approach is explicitly illustrated for (i) reciprocal and exponential intervening variables, (ii) the intervening variables used in the method of moving asymptotes (MMA), (iii) the intervening variables used in CONLIN, and (iv) the TANA-3 approximations. The use of intermediate responses for use in, for example, truss and frame-like structures, is also discussed. Key advantages of replacing nonlinear approximations by their diagonal quadratic approximations are that these approximated approximations can all be used simultaneously in a single dual statement; the dual does not depend on the form of the original approximations. In addition, in a dual setting, the resulting subproblems yield simple analytical relationships between the primal and dual variables, which is often not the case with the original nonlinear approximations. An important example hereof is the exponential approximation. Although the diagonal quadratic approximations may differ notably from their original counterparts, they typically are quite similar in a sufficiently small search subregion, which relates to the move limits commonly used in SAO anyway.     

IEEE 802.21: Media independence beyond handover

The IEEE 802.21 standard facilitates media independent handovers by providing higher layer mobility management functions with common service primitives for all technologies. Right after the base specification was published, several voices rose up in the working group advocating to broaden the scope of IEEE 802.21 beyond handovers. This paper aims at updating the reader with the main challenges and functionalities required to create a Media Independence Service Layer, through the analysis of scenarios which are being discussed within the working group: 1) Wireless Coexistence, and 2) Heterogeneous Wireless Multihop Backhaul Networks.     

Principles and typical computational limitations of sparse speaker separation based on deterministic speech features

The separation of mixed auditory signals into their sources is an eminent neuroscience and engineering challenge. We reveal the principles underlying a deterministic, neural network-like solution to this problem. This approach is orthogonal to ICA/PCA that views the signal constituents as independent realizations of random processes. We demonstrate exemplarily that in the absence of salient frequency modulations, the decomposition of speech signals into local cosine packets allows for a sparse, noise-robust speaker separation. As the main result, we present analytical limitations inherent in the approach, where we propose strategies of how to deal with this situation. Our results offer new perspectives toward efficient noise cleaning and auditory signal separation and provide a new perspective of how the brain might achieve these tasks.