Ultrasound entropy may be a new non-invasive measure of pre-clinical vascular damage in young hypertensive patients

Background: The identification of pre-clinical microvascular damage in hypertension by non-invasive techniques has proved frustrating for clinicians. This proof of concept study investigated whether entropy, a novel summary measure for characterizing blood velocity waveforms, is altered in participants with hypertension and may therefore be useful in risk stratification.

Methods: Doppler ultrasound waveforms were obtained from the carotid and retrobulbar circulation in 42 participants with uncomplicated grade 1 hypertension (mean systolic/diastolic blood pressure (BP) 142/92 mmHg), and 26 healthy controls (mean systolic/diastolic BP 116/69 mmHg). Mean wavelet entropy was derived from flow-velocity data and compared with traditional haemodynamic measures of microvascular function, namely the resistive and pulsatility indices.

Results: Entropy, was significantly higher in control participants in the central retinal artery (CRA) (differential mean 0.11 (standard error 0.05 cms(-1)), CI 0.009 to 0.219, p 0.017) and ophthalmic artery (0.12 (0.05), CI 0.004 to 0.215, p 0.04). In comparison, the resistive index (0.12 (0.05), CI 0.005 to 0.226, p 0.029) and pulsatility index (0.96 (0.38), CI 0.19 to 1.72, p 0.015) showed significant differences between groups in the CRA alone. Regression analysis indicated that entropy was significantly influenced by age and systolic blood pressure (r values 0.4-0.6). None of the measures were significantly altered in the larger conduit vessel.

Conclusion: This is the first application of entropy to human blood velocity waveform analysis and shows that this new technique has the ability to discriminate health from early hypertensive disease, thereby promoting the early identification of cardiovascular disease in a young hypertensive population.

High speed DSC (hyper-DSC) as a tool to measure the solubility of a drug within a solid or semi-solid matrix

Conventional differential scanning calorimetry (DSC) techniques are commonly used to quantify the solubility of drugs within polymeric-controlled delivery systems. However, the nature of the DSC experiment, and in particular the relatively slow heating rates employed, limit its use to the measurement of drug solubility at the drug's melting temperature. Here, we describe the application of hyper-DSC (HDSC), a variant of DSC involving extremely rapid heating rates, to the calculation of the solubility of a model drug, metronidazole, in silicone elastomer, and demonstrate that the faster heating rates permit the solubility to be calculated under non-equilibrium conditions such that the solubility better approximates that at the temperature of use. At a heating rate of 400 degrees C/min (HDSC), metronidazole solubility was calculated to be 2.16 mg/g compared with 6.16 mg/g at 20 degrees C/min. (C) 2005 Elsevier B.V. All rights reserved.

Selecting a measure of health-related quality of life.

Quality of life is becoming recognized increasingly as an important outcome measure which needs to be considered by social workers. However, there does not appear to be a clear consensus about the definition of quality of life. In addition, social workers are likely to experience difficulties choosing and applying an appropriate instrument with which to measure quality of life because of the many available instruments purporting to assess quality of life. This paper discusses the definition of health-related quality of life and explains the main measurement properties of an instrument that must be appraised when considering whether or not an instrument is appropriate. The paper will assist social workers to make an informed choice about measures of health-related quality of life.

Mis-measure of animal contests.

Contests between rivals placing similar value on the resource at stake are commonly won by the rival having greater 'resource holding potential' (RHP). Mutual assessment of RHP difference between rivals is usually expected as an economical means of resolution; weaker rivals can retreat when they detect their relative inferiority, thereby avoiding costly, futile persistence. Models of contest resolution that entail retreat decisions based on estimates of RHP difference predict that contest duration diminishes as RHP difference between rivals increases because the asymmetry is more readily detected. This prediction appears to have been fulfilled in contests of diverse taxa, generating widespread support for assessment of RHP differences in contests. But few studies have considered alternatives in which each rival simply persists in accord with its own RHP ('own RHP-dependent persistence'). In contests decided by own RHP-dependent persistence, in which costs accrue only through each rival's own actions, weaker rivals retreat first because they are inherently less persistent, and contest duration depends primarily on the weaker (losing) rival's RHP rather than RHP difference between the rivals. We show here that the analyses most commonly used to detect effects of RHP difference cannot discriminate between these alternatives. Because RHP difference between rivals tends to be correlated with RHP of the weaker rival in a pair, a negative relation between RHP difference and contest duration may be generated even when decisions of retreat are not based on estimated RHP difference. Many studies purporting to show a negative relation between RHP difference and contest duration may actually reflect an incidental association between weaker rival RHP and RHP difference. We suggest statistical and experimental approaches that may help to discriminate between effects of weaker rival RHP and true effects of RHP difference. We also discuss whether 'true' negative effects of RHP difference on contest duration always reflect retreat decisions based on estimated RHP differences. Copyright 2003 Published by Elsevier Science Ltd on behalf of The Association for the Study of Animal Behaviour.

A content analysis method to measure critical thinking in face-to-face and computer supported group learning

This paper gives a detailed account of the content analysis method developed at Queen's University Belfast to measure critical thinking during group learning, as used in our controlled comparisons between learning in face-to-face and computer conference seminars. From Garrison's 5 stages of critical thinking, and Henri's cognitive skills needed in CMC, we have developed two research instruments: a student questionnaire and this content analysis method. The content analysis relies on identifying, within transcripts, examples of indicators of obviously critical and obviously uncritical thinking, from which several critical thinking ratios can be calculated.

Development of a technique to measure the residual strength of woodworm infested timber

This paper presents a study of the residual strength of Pinus sylvestris, which has been subject to attack by the furniture beetle (Anobium punctatum). It is relatively easy to stop the infestation, but difficult to assess the structural soundness of the remaining timber. Removal and replacement of affected structural elements is usually difficult and expensive, particularly in buildings of historic interest. Current on-site assessment procedures are limited. The main object of the study was to develop an on-site test of timber quality: a test which can be carried out on the surface and also at varying depths into the timber. It is based on a probe pull-out technique using a portable load-measuring device. Pull-out force values have been correlated with both strength and energy absorbed as measured by compression testing on laboratory samples of both sound and infested timber. These two relationships are significant and could be used to assess whether remedial work is needed. In addition, work on the use of artificial borings to simulate the natural worming of timber is presented and the findings discussed.

Introduction of a Nonlinearity Measure for Principal Component Models

This is the first paper that introduces a nonlinearity test for principal component models. The methodology involves the division of the data space into disjunct regions that are analysed using principal component analysis using the cross-validation principle. Several toy examples have been successfully analysed and the nonlinearity test has subsequently been applied to data from an internal combustion engine.