The assessment of circulating volume using inferior vena cava collapse index and carotid Doppler velocity time integral in healthy volunteers: a pilot study.

BACKGROUND: Assessment of circulating volume and the requirement for fluid replacement are fundamental to resuscitation but remain largely empirical. Passive leg raise (PLR) may determine fluid responders while avoiding potential fluid overload. We hypothesised that inferior vena cava collapse index (IVCCI) and carotid artery blood flow would change predictably in response to PLR, potentially providing a non-invasive tool to assess circulating volume and identifying fluid responsive patients. METHODS: We conducted a prospective proof of concept pilot study on fasted healthy volunteers. One operator measured IVC diameter during quiet respiration and sniff, and carotid artery flow. Stroke volume (SV) was also measured using suprasternal Doppler. Our primary endpoint was change in IVCCI after PLR. We also studied changes in IVCCI after "sniff", and correlation between carotid artery flow and SV. RESULTS: Passive leg raise was associated with significant reduction in the mean inferior vena cava collapsibility index from 0.24 to 0.17 (p < 0.01). Mean stroke volume increased from 56.0 to 69.2 mL (p < 0.01). There was no significant change in common carotid artery blood flow. Changes in physiology consequent upon passive leg raise normalised rapidly. DISCUSSION: Passive leg raise is associated with a decrease of IVCCI and increase in stroke volume. However, the wide range of values observed suggests that factors other than circulating volume predominate in determining the proportion of collapse with respiration. CONCLUSION: In contrast to other studies, we did not find that carotid blood flow increased with passive leg raise. Rapid normalisation of post-PLR physiology may account for this.

Sensitivity of rabbit ventricular action potential and Ca²âº dynamics to small variations in membrane currents and ion diffusion coefficients.

Little is known about how small variations in ionic currents and Ca²âº and Na⁺ diffusion coefficients impact action potential and Ca²âº dynamics in rabbit ventricular myocytes. We applied sensitivity analysis to quantify the sensitivity of Shannon et al. model (Biophys. J., 2004) to 5%-10% changes in currents conductance, channels distribution, and ion diffusion in rabbit ventricular cells. We found that action potential duration and Ca²âº peaks are highly sensitive to 10% increase in L-type Ca²âº current; moderately influenced by 10% increase in Na⁺-Ca²âº exchanger, Na⁺-K⁺ pump, rapid delayed and slow transient outward K⁺ currents, and Cl⁻ background current; insensitive to 10% increases in all other ionic currents and sarcoplasmic reticulum Ca²âº fluxes. Cell electrical activity is strongly affected by 5% shift of L-type Ca²âº channels and Na⁺-Ca²âº exchanger in between junctional and submembrane spaces while Ca²âº-activated Cl⁻-channel redistribution has the modest effect. Small changes in submembrane and cytosolic diffusion coefficients for Ca²âº, but not in Na⁺ transfer, may alter notably myocyte contraction. Our studies highlight the need for more precise measurements and further extending and testing of the Shannon et al. model. Our results demonstrate usefulness of sensitivity analysis to identify specific knowledge gaps and controversies related to ventricular cell electrophysiology and Ca²âº signaling.

Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations.

Gamma oscillations are thought to be critical for a number of behavioral functions, they occur in many regions of the brain and through a variety of mechanisms. Fast repetitive bursting (FRB) neurons in layer 2 of the cortex are able to drive gamma oscillations over long periods of time. Even though the oscillation is driven by FRB neurons, strong feedback within the rest of the cortex must modulate properties of the oscillation such as frequency and power. We used a highly detailed model of the cortex to determine how a cohort of 33 parameters controlling synaptic drive might modulate gamma oscillation properties. We were interested in determining not just the effects of parameters individually, but we also wanted to reveal interactions between parameters beyond additive effects. To prevent a combinatorial explosion in parameter combinations that might need to be simulated, we used a fractional factorial design (FFD) that estimated the effects of individual parameters and two parameter interactions. This experiment required only 4096 model runs. We found that the largest effects on both gamma power and frequency came from a complex interaction between efficacy of synaptic connections from layer 2 inhibitory neurons to layer 2 excitatory neurons and the parameter for the reciprocal connection. As well as the effect of the individual parameters determining synaptic efficacy, there was an interaction between these parameters beyond the additive effects of the parameters alone. The magnitude of this effect was similar to that of the individual parameters, predicting that it is physiologically important in setting gamma oscillation properties.

Leveraging e-Science infrastructure for electrochemical research.

As in many scientific disciplines, modern chemistry involves a mix of experimentation and computer-supported theory. Historically, these skills have been provided by different groups, and range from traditional 'wet' laboratory science to advanced numerical simulation. Increasingly, progress is made by global collaborations, in which new theory may be developed in one part of the world and applied and tested in the laboratory elsewhere. e-Science, or cyber-infrastructure, underpins such collaborations by providing a unified platform for accessing scientific instruments, computers and data archives, and collaboration tools. In this paper we discuss the application of advanced e-Science software tools to electrochemistry research performed in three different laboratories--two at Monash University in Australia and one at the University of Oxford in the UK. We show that software tools that were originally developed for a range of application domains can be applied to electrochemical problems, in particular Fourier voltammetry. Moreover, we show that, by replacing ad-hoc manual processes with e-Science tools, we obtain more accurate solutions automatically.

Minor head injury in the Republic of Ireland: evaluation of written information given at discharge from emergency departments.

Most patients presenting to the emergency department with minor head injuries are discharged with written information. Here the quality of minor head injury discharge leaflets in the Republic of Ireland is evaluated against a nationally accepted template. There was great variability in leaflet content. Most provided minimal information on emergency symptoms but 60% contained no information on post-concussional symptoms. No leaflet was available in audio-format or languages other than English. Information provided in minor head injury leaflets should be improved and standardised across Ireland.

A global sensitivity tool for cardiac cell modeling: Application to ionic current balance and hypertrophic signaling.

Cardiovascular diseases are the major cause of death in the developed countries. Identifying key cellular processes involved in generation of the electrical signal and in regulation of signal transduction pathways is essential for unraveling the underlying mechanisms of heart rhythm behavior. Computational cardiac models provide important insights into cardiovascular function and disease. Sensitivity analysis presents a key tool for exploring the large parameter space of such models, in order to determine the key factors determining and controlling the underlying physiological processes. We developed a new global sensitivity analysis tool which implements the Morris method, a global sensitivity screening algorithm, onto a Nimrod platform, which is a distributed resources software toolkit. The newly developed tool has been validated using the model of IP3-calcineurin signal transduction pathway model which has 30 parameters. The key driving factors of the IP3 transient behaviour have been calculated and confirmed to agree with previously published data. We next demonstrated the use of this method as an assessment tool for characterizing the structure of cardiac ionic models. In three latest human ventricular myocyte models, we examined the contribution of transmembrane currents to the shape of the electrical signal (i.e. on the action potential duration). The resulting profiles of the ionic current balance demonstrated the highly nonlinear nature of cardiac ionic models and identified key players in different models. Such profiling suggests new avenues for development of methodologies to predict drug action effects in cardiac cells.

High-throughput cardiac science on the Grid.

Cardiac electrophysiology is a mature discipline, with the first model of a cardiac cell action potential having been developed in 1962. Current models range from single ion channels, through very complex models of individual cardiac cells, to geometrically and anatomically detailed models of the electrical activity in whole ventricles. A critical issue for model developers is how to choose parameters that allow the model to faithfully reproduce observed physiological effects without over-fitting. In this paper, we discuss the use of a parametric modelling toolkit, called Nimrod, that makes it possible both to explore model behaviour as parameters are changed and also to tune parameters by optimizing model output. Importantly, Nimrod leverages computers on the Grid, accelerating experiments by using available high-performance platforms. We illustrate the use of Nimrod with two case studies, one at the cardiac tissue level and one at the cellular level.