Comparison of hypertonic saline solutions and dextran in dialysis-induced hypotension

The efficacy of three hypertonic saline solutions for treating dialysis-induced hypotension in a randomized, blinded, crossover clinical trial of 10 patients (a minimum of three cycles per solution) was compared. Dialysis-induced hypotension, defined as a decrease in systolic blood pressure of at least 10 mm Hg or systolic blood pressure less than 100 mm Hg, was treated with an iv bolus of either 10 mL of 23% saturated hypertonic saline, 30 mL of 7.5% hypertonic saline, or 30 mL of 7.5% saline with 6% dextran 70, each containing similar osmolar loads of 80, 80, and 100 mosM, respectively. All three solutions raised systolic blood pressure within 5 min (mean pretreatment systolic blood pressure, 87 mm Hg; mean posttreatment systolic blood pressure, 101 mm Hg; P < 0.05). The magnitude of the increase was greater with saturated hypertonic saline (15 mm Hg) and dextran 70 (17 mm Hg) compared with that with hypertonic saline (9 mm Hg; P < 0.05). At 10 min, dialysis-induced hypotension was less frequent with saturated hypertonic saline (incidence, 9%) compared with hypertonic saline (45%). Beyond 10 min, however, there was a trend toward a lower incidence of further dialysis-induced hypotension with dextran 70. There were no side effects. Given equal osmole loads, the more concentrated solution produced a greater increase in systolic blood pressure. The addition of an oncotic agent such as dextran may prolong the blood pressure response beyond 10 min. It was concluded that hypertonic saline solutions safely and effectively treat dialysis-induced hypotension.     

Modeling deformable surfaces with level sets

This article describes how to use level sets to represent and compute deformable surfaces. A deformable surface is a sequence of surface models obtained by taking an initial model and incrementally modifying its shape. Typically, we can parameterize the deformation over time, and thus we can imagine that a surface moves or flows under the influence of a vector field. The surface flow, v, can be determined as a function of spatial position (and time), or it can depend on the shape of the surface itself. The latter is called a geometric flow. Deformable surfaces have been used to solve a variety of problems in image processing, computer vision, visualization, and graphics. In graphics, for instance, deformable surface models have been used to form sequences of shapes that animate the morphing of one object into another. They have also been used to denoise or smooth surface models derived from a set of noisy 3D measurements.     

Multianalyte single-cell analysis with multiple cell lines using a fiber-optic array

A single-cell drug screening method is described that produces rich single-cell data and discriminates between single-cell responses from clonal populations stimulated with different agonists. Ligand-induced receptor activation is commonly detected by observing intracellular Ca2+ oscillations using high-throughput screening (HTS) methods. In most cases, HTS results in an average signal from several cells and is not sensitive enough to enable the identification of population outliers or population variance. In order to obtain this information, many individual cells must be analyzed simultaneously. We have developed a novel system using a specialized fiber-optic platform and have combined it with statistical analysis, to simultaneously analyze the dynamics of Ca2+ oscillations in a large number of single cells. Mammalian cells ectopically expressing different human GPCR receptors were stimulated, and Ca2+ changes in numerous single cells were recorded over time using a fluorescent microscope and a CCD camera. We determined the percentage of live cells in a population responding to stimuli, the distribution of responses within a population of clonal cells, and the number of outliers. By employing principal component analysis and K-nearest neighbor modeling, we classified the time-resolved Ca2+ traces of single cells as a function of the stimulus type with high certainty for a population of cells. This method is potentially a powerful tool for identifying new drug targets or for investigating the single-cell behavior of an existing target or known receptor. The development of this single-cell drug screening method is presented, and fluorescent and statistical analyses of single-cell dynamic responses are discussed.     

Rethinking the design of virtual machine monitors

A virtual machine monitor is a software system that partitions a single physical machine into multiple virtual machines. Traditionally, VMMs have created a precise replica of the underlying physical machine. Through faithful emulation, VMMs support the execution of legacy guest operating systems such as Windows or Linux without modifications. However, traditional VMMs suffer from poor scalability and extensibility. To overcome the poor scalability and extensibility of traditional virtual machine monitors that partition a single physical machine into multiple virtual machines, the Denali VMM uses paravirtualization to promote scalability and hardware interposition to promote extensibility.     

A case-study on naïve labelling for the nearest mean and the linear discriminant classifiers

The abundance of unlabelled data alongside limited labelled data has provoked significant interest in semi-supervised learning methods. “Naïve labelling” refers to the following simple strategy for using unlabelled data in on-line classification. A new data point is first labelled by the current classifier and then added to the training set together with the assigned label. The classifier is updated before seeing the subsequent data point. Although the danger of a run-away classifier is obvious, versions of naïve labelling pervade in on-line adaptive learning. We study the asymptotic behaviour of naïve labelling in the case of two Gaussian classes and one variable. The analysis shows that if the classifier model assumes correctly the underlying distribution of the problem, naïve labelling will drive the parameters of the classifier towards their optimal values. However, if the model is not guessed correctly, the benefits are outweighed by the instability of the labelling strategy (run-away behaviour of the classifier). The results are based on exact calculations of the point of convergence, simulations, and experiments with 25 real data sets. The findings in our study are consistent with concerns about general use of unlabelled data, flagged up in the recent literature.     

Ultrafast response of superconducting transmission lines

The authors report investigations of picosecond transient propagation on normal and superconducting transmission lines and results of a variety of lines that include YBa₂Cu₃O_7-x (YBCO) coplanar lines, a superconducting coaxial cable, and a dielectric-matched gold-line structure. A previously developed algorithm for analyzing transient propagation was used to identify the dominant mechanisms for signal distortion in most of these cases, and the essential properties of all tested to date are summarized for a direct comparison     

GDSS' formative fundaments

A hermeneutic analysis of current group decision support systems (GDSS) is undertaken, interpreting their functionality, motivations, and usage to uncover theoretical/philosophical bases. GDSS treat decision making as a rational aggregation-and-selection of options (take a given) and support it as a production task conducted as if participants were remotely distributed. Employing avenue framework, this is analyzed as evidence for consistent, fundamentalcognitivism andobjectivism deriving from relevant historical influences. The contextualization and dialogic interaction (give and take) undervalued or ignored in current GDSS are identified as key issues for work toward constructively augmenting such systems.This interpretive analysis, originally appearing as Chapter 2 in Whitaker (1992), was developed at Umeå Universitet (Sweden) with guidance (and insightful challenges) from Professor Kristo Ivanov and Professor Emeritus Hans-Erik Nissen, to whom the author is grateful. The transformation of that material into a standalone article was greatly facilitated by the cogent comments of this journal's reviewers, to whom this author is similarly grateful.     

The peak in the thermal conductivity of Cu-O superconductors: Electronic or phononic origin?

The thermal conductivity of hole-doped Cu-O plane high-T _c perovskites exhibits a dramatic increase belowT _c which results in a pronounced peak nearT _c /2. The origin of this peak was initially thought to arise from an enhancement in the mean-free path of phonons as the charge carriers undergo condensation. Indeed, excellent fits to the data can be obtained with physically reasonable parameters using the conventional theory of lattice conduction in superconductors. In contrast, a recently observed sharp decrease in the quasiparticle scattering rate of YBCO single crystals belowT _c has motivated proposals for an electronic origin of the thermal conductivity peak. We shall critically examine experimental evidence and highlight relative advantages and shortcomings of the two contrasting interpretations. Furthermore, we shall draw attention to recently available data on the relaxation time of out-of-equilibrium carriers in Cu-O superconductors obtained using pump-probe femtosecond laser studies and what new light they shed on the controversy.     

Adaptive SPECT

Adaptive imaging systems alter their data-acquisition configuration or protocol in response to the image information received. An adaptive pinhole single-photon emission computed tomography (SPECT) system might acquire an initial scout image to obtain preliminary information about the radiotracer distribution and then adjust the configuration or sizes of the pinholes, the magnifications, or the projection angles in order to improve performance. This paper briefly describes two small-animal SPECT systems that allow this flexibility and then presents a framework for evaluating adaptive systems in general, and adaptive SPECT systems in particular. The evaluation is in terms of the performance of linear observers on detection or estimation tasks. Expressions are derived for the ideal linear (Hotelling) observer and the ideal linear (Wiener) estimator with adaptive imaging. Detailed expressions for the performance figures of merit are given, and possible adaptation rules are discussed.