Glycosidase mechanisms: anatomy of a finely tuned catalyst

In order to accelerate the hydrolysis of glycosidic bonds by factors approaching 10(17)-fold, glycosidases have evolved finely tuned active sites optimally configured for transition-state stabilization. Structural analyses of various enzyme complexes representing stable intermediates along the reaction coordinate, in conjunction with detailed mechanistic studies on wild-type and mutant enzymes, have delineated the contributions of nucleophilic and general acid/base catalysis, as well as the roles of noncovalent interactions, to these impressive rate enhancements.     

Development of a photofragmentation laser-induced-fluorescence laser sensor for detection of 2, 4, 6-trinitrotoluene in soil and groundwater

Laser photofragmentation (PF) and subsequent nitric oxide (NO) laser-induced fluorescence (LIF) have been developed to measure the concentration of energetic materials (EM's), such as 2, 4, 6-trinitrotoluene (TNT), in soil and other media. Gas-phase EM's photodissociate, releasing NO(2), when exposed to laser radiation near 226 nm. Laser-excited NO(2) predissociates to form NO that gives an intense fluorescence when excited near 226 nm. The EM concentration is inferred from the intensity of the NO fluorescence. A PF-LIF laser-based sensor is being developed to be used with the U.S. Army Corps of Engineers' Waterways Experiment Station's cone penetrometer to measure in situ the concentration of subsurface TNT. Several factors that affect the PF-LIF signal waveforms, such as sample temperature, laser power, and heating time, were investigated. Also, effects on the PF-LIF signal of adding water and fertilizer to the TNT mixtures were studied. Decay times were determined by least-squares fitting of the exponential PF-LIF signal waveforms. The use of PF-LIF waveforms promises to enable diagnostics of the sample's characteristics that would otherwise not be possible in situ.     

Overdetermined least-squares aberration estimates using common-midpoint signals

As medical ultrasound imaging moves to larger apertures and higher frequencies, tissue sound-speed variations continue to limit resolution. In geophysical imaging, a standard approach for estimating near-surface aberrating delays is to analyze the time shifts between common-midpoint signals. This requires complete data-echoes from every source/receiver pair in the array. Unfocused common-midpoint signals remain highly correlated in the presence of delay aberrations; there is also tremendous redundancy in the data. In medical ultrasound, this technique has been impaired by the wide-angle, random-scattering nature of tissue. This has made it difficult to estimate azimuth-dependent aberration profiles or to harness the full redundancy in the complete data. Prefiltering the data with two-dimensional fan filters mitigates these problems, permitting highly overdetermined, least-squares solutions for the aberration profiles at many steering angles. In experiments with a tissue-mimicking phantom target and silicone rubber aberrators at nonzero stand-off distances from a one-dimensional phased array, this overdetermined, fan-filtering algorithm significantly outperformed other phase-screen algorithms based on nearest-neighbor cross-correlation, speckle brightness maximization, and common-midpoint signal analysis. Our results imply that there is still progress to be made in imaging with single-valued focusing operators. It also appears that the signal-to-noise penalty for using complete data sets is partially compensated by the overdetermined nature of the problem.     

Analog CMOS circuit design and characterization for optical coherence tomography signal processing

We have developed a custom analog CMOS circuit to perform the signal processing for an optical coherence tomography imaging system. The circuit is realized in a 1.5 /spl mu/m low-noise analog CMOS technology. The circuitry extracts the Doppler frequency from the signal and electrically mixes this with the original signal to provide a filtered A-scan. The circuitry was used to produce a two-dimensional image of an onion.     

The biochemical and physical effects of electrical stimulation on beef and sheep meat tenderness

Application of electrical stimulation in the sheep and beef processing industry has been erratic around the world and this may reflect an incomplete knowledge of how to optimise the technology. Although it is well established that stimulation increases the rate of post-mortem glycolysis, other biochemical and biophysical effects have been implicated with the use of this technology. This review seeks to examine the current theories about the effect of stimulation on post-mortem muscle. The classical view that stimulation prevents muscle from shortening excessively during rigor development has been expanded to include the possibility that it also results in physical disruption of muscle structure. The interaction of these effects with the acceleration of the rate of proteolysis through activation of the calpain protease system has not been comprehensively reviewed in the past. Thus there are two mechanisms which could explain the effect of stimulation on tenderisation, reduced 'cold-induced' shortening and alteration of protein structure. A secondary effect is the enhancement of the rate of proteolysis stimulated by release of Ca (2+) at a higher temperature. As a result of this review we highlight several areas that may prove fruitful for further research. The challenge for further development of electrical stimulation systems is optimisation of the activation of the enzyme systems in parallel with manipulation of chilling regimes so as to ensure rigor mortis is achieved at temperatures which minimise shortening. These optimal temperatures largely established at a fixed incubation temperature for detached muscle may be different when measured in intact carcasses. The potential of regional stimulation of sections of the carcass to achieve this outcome is worthy of study given the different fibre composition of muscles and temperature gradients. In addition, to ensure that appropriate amounts of energy are applied to individual carcasses, development of self-response stimulation units, which are able to determine carcass resistance and apply appropriate durations or strengths of stimulation is worthy of future research. This would lead to more effective electrical stimulation practices.     

Effect of inherent location uncertainty on detection of stationary targets in noisy image sequences

The effect of inherent location uncertainty on the detection of stationary targets was determined in noisy image sequences. Targets were thick and thin projected cylinders mimicking arteries, catheters, and guide wires in medical imaging x-ray fluoroscopy. With the use of an adaptive forced-choice method, detection contrast sensitivity (the inverse of contrast) was measured both with and without marker cues that directed the attention of observers to the target location. With the probability correct clamped at 80%, contrast sensitivity increased an average of 77% when the marker was added to the thin-cylinder target. There was an insignificant effect on the thick cylinder. The large enhancement with the thin cylinder was obtained even though the target was located exactly in the center of a small panel, giving observers the impression that it was well localized. Psychometric functions consisting of d' plotted as a function of the square root of the signal-energy-to-noise-ratio gave a positive x intercept for the case of the thin cylinder without a marker. This x intercept, characteristic of uncertainty in other types of detection experiments, disappeared when the marker was added or when the thick cylinder was used. Inherent location uncertainty was further characterized by using four different markers with varying proximity to the target. Visual detection by human observers increased monotonically as the markers better localized the target. Human performance was modeled as a matched-filter detector with an uncertainty in the placement of the template. The removal of a location cue was modeled by introducing a location uncertainty of approximately equals 0.4 mm on the display device or only 7 microm on the retina, a size on the order of a single photoreceptor field. We conclude that detection is affected by target location uncertainty on the order of cellular dimensions, an observation with important implications for detection mechanisms in humans. In medical imaging, the results argue strongly for inclusion of high-contrast visualization markers on catheters and other interventional devices.     

Detection improvement in spatially filtered x-ray fluoroscopy image sequences

The effect of spatial noise-reduction filtering on human observer detection of stationary cylinders mimicking arteries, catheters, and guide wires in x-ray fluoroscopy was investigated in both single image frames and image sequences. Ideal edge-preserving spatial filtering was simulated by filtering of the noise before addition of the target cylinder. This allowed us to separate the effect of edge blurring from those of noise reduction and spatial noise correlation. We used three different center-weighted averagers that reduced pixel noise variance by factors of 0.75, 0.50, and 0.25. As compared with no filtering, the effect of filtering on detection in single images was statistically insignificant. This indicated an adverse effect of spatial noise correlation on detection that countered the effect of noise reduction. By comparison, spatial filtering significantly improved detection in image sequences and yielded potential x-ray dose savings of 26-34%. Comparison of results with two observer models suggested that human observers have an improved detection efficiency in spatially filtered image sequences as compared with white-noise sequences. Pixel noise reduction, a measure commonly used to assess filter performance, overestimated the effect of filtering on detection and was not a good indicator of image quality. We conclude that edge-preserving spatial filtering is more effective in sequences than in single images and that such filtering can be used to improve image quality in noisy image sequences such as x-ray fluoroscopy.     

Toxicity of benzotriazole and benzotriazole derivatives to three aquatic species

Benzotriazole and its derivatives comprise an important class of corrosion inhibitors, typically used as trace additives in industrial chemical mixtures such as coolants, deicers, surface coatings, cutting fluids, and hydraulic fluids. Recent studies have shown that benzotriazole derivatives are a major component of aircraft deicing fluids (ADFs) responsible for toxicity to bacteria (Microtox). Our current research compared the toxicity of benzotriazole (BT), two methylbenzotriazole (MeBT) isomers, and butylbenzotriazole (BBT). Acute toxicity assays were used to model the response of three common test organisms: Microtox bacteria (Vibrio fischeri), fathead minnow (Pimephales promelas) and water flea (Ceriodaphnia dubia). The response of all the three organisms varied over two orders of magnitude among all compounds. Vibrio fischeri was more sensitive than either C. dubia or P. promelas to all the test materials, while C. dubia was less sensitive than P. promelas. The response of test organisms to unmethylated benzotriazole and 4-methylbenzotriazole was similar, whereas 5-methylbenzotriazole was more toxic than either of these two compounds. BBT was the most toxic benzotriazole derivative tested, inducing acute toxicity at a concentration of < or = 3.3 mg/l to all organisms.     

Model-based 3-D segmentation of multiple sclerosis lesions in magnetic resonance brain images

Human investigators instinctively segment medical images into their anatomical components, drawing upon prior knowledge of anatomy to overcome image artifacts, noise, and lack of tissue contrast. The authors describe: 1) the development and use of a brain tissue probability model for the segmentation of multiple sclerosis (MS) lesions in magnetic resonance (MR) brain images, and 2) an empirical comparison of the performance of statistical and decision tree classifiers, applied to MS lesion segmentation. Based on MR image data obtained from healthy volunteers, the model provides prior probabilities of brain tissue distribution per unit voxel in a standardized 3-D "brain space". In comparison to purely data-driven segmentation, the use of the model to guide the segmentation of MS lesions reduced the volume of false positive lesions by 50-80%