Biomedical research models in the science of fracture healing - Pitfalls & promises.

Development of intervention strategies to stimulate fracture healing has long been a focus of musculoskeletal research. Considerable investment in empirical research has led to the discovery of several genes and signaling pathways that are involved in skeletal development and regeneration. However, there are currently very few biologic interventions that can efficiently be used to enhance fracture healing in clinical practice. This translational barrier is due in part to experimental barriers to mechanism discovery. Animal models, biomechanical models, finite element models, and mathematical models are a few examples of models that aid in the discovery of mechanisms. Understanding the advantages, limitations, and specialized uses of each model type is critical to our ability to interpret mechanistic insights from such research and to help bridge the translation gap between pre-clinical research and clinical practice. In this review, we look at specific modeling methods used in the study of the fracture healing mechanism. We also discuss the strength and limitations to translation of each method, hopefully leading to a better understanding of how we can use models to advance the study of fracture healing.

Nocturnal torpor by superb fairy-wrens: a key mechanism for reducing winter daily energy expenditure.

Many passerine birds are small and require a high mass-specific rate of resting energy expenditure, especially in the cold. The energetics of thermoregulation is, therefore, an important aspect of their ecology, yet few studies have quantified thermoregulatory patterns in wild passerines. We used miniature telemetry to record the skin temperature ( Tskin) of free-living superb fairy-wrens ( Malurus cyaneus, 8.6 g; n = 6 birds over N = 7-22 days) and determine the importance of controlled reductions in body temperature during resting to their winter energy budgets. Fairy-wrens routinely exhibited large daily fluctuations in Tskin between maxima of 41.9 ± 0.6°C and minima of 30.4 ± 0.7°C, with overall individual minima of 27.4 ± 1.1°C (maximum daily range: 14.7 ± 0.9°C). These results provide strong evidence of nocturnal torpor in this small passerine, which we calculated to provide a 42% reduction in resting metabolic rate at a Ta of 5°C compared to active-phase Tskin. A capacity for energy-saving torpor has important consequences for understanding the behaviour and life-history ecology of superb fairy-wrens. Moreover, our novel field data suggest that torpor could be more widespread and important than previously thought within passerines, the most diverse order of birds.

Novel wave intensity analysis of arterial pulse wave propagation accounting for peripheral reflections.

We present a novel analysis of arterial pulse wave propagation that combines traditional wave intensity analysis with identification of Windkessel pressures to account for the effect on the pressure waveform of peripheral wave reflections. Using haemodynamic data measured in vivo in the rabbit or generated numerically in models of human compliant vessels, we show that traditional wave intensity analysis identifies the timing, direction and magnitude of the predominant waves that shape aortic pressure and flow waveforms in systole, but fails to identify the effect of peripheral reflections. These reflections persist for several cardiac cycles and make up most of the pressure waveform, especially in diastole and early systole. Ignoring peripheral reflections leads to an erroneous indication of a reflection-free period in early systole and additional error in the estimates of (i) pulse wave velocity at the ascending aorta given by the PU-loop method (9.5% error) and (ii) transit time to a dominant reflection site calculated from the wave intensity profile (27% error). These errors decreased to 1.3% and 10%, respectively, when accounting for peripheral reflections. Using our new analysis, we investigate the effect of vessel compliance and peripheral resistance on wave intensity, peripheral reflections and reflections originating in previous cardiac cycles.

Haemodynamics in the mouse aortic arch computed from MRI-derived velocities at the aortic root.

Mice are widely used to investigate atherogenesis, which is known to be influenced by stresses related to blood flow. However, numerical characterization of the haemodynamic environment in the commonly studied aortic arch has hitherto been based on idealizations of inflow into the aorta. Our purpose in this work was to numerically characterize the haemodynamic environment in the mouse aortic arch using measured inflow velocities, and to relate the resulting shear stress patterns to known locations of high- and low-lesion prevalence. Blood flow velocities were measured in the aortic root of C57/BL6 mice using phase-contrast MRI. Arterial geometries were obtained by micro-CT of corrosion casts. These data were used to compute blood flow and wall shear stress (WSS) patterns in the arch. WSS profiles computed using realistic and idealized aortic root velocities differed significantly. An unexpected finding was that average WSS in the high-lesion-probability region on the inner wall was actually higher than the WSS in the low-probability region on the outer wall. Future studies of mouse aortic arch haemodynamics should avoid the use of idealized inflow velocity profiles. Lesion formation does not seem to uniquely associate with low or oscillating WSS in this segment, suggesting that other factors may also play a role in lesion localization.

Modelling pulse wave propagation in the rabbit systemic circulation to assess the effects of altered nitric oxide synthesis.

Pulse wave propagation in the mature rabbit systemic circulation was simulated using the one-dimensional equations of blood flow in compliant vessels. A corrosion cast of the rabbit circulation was manufactured to obtain arterial lengths and diameters. Pulse wave speeds and inflow and outflow boundary conditions were derived from in vivo data. Numerical results captured the main features of in vivo pressure and velocity pulse waveforms in the aorta, brachiocephalic artery and central ear artery. This model was used to elucidate haemodynamic mechanisms underlying changes in peripheral pulse waveforms observed in vivo after administering drugs that alter nitric oxide synthesis in the endothelial cells lining blood vessels. According to our model, these changes can be explained by single or combined alterations of blood viscosity, peripheral resistance and compliance, and the elasticity of conduit arteries.

Accuracy of popular automatic QT interval algorithms assessed by a 'gold standard' and comparison with a Novel method: computer simulation study.

BACKGROUND: Accurate measurement of the QT interval is very important from a clinical and pharmaceutical drug safety screening perspective. Expert manual measurement is both imprecise and imperfectly reproducible, yet it is used as the reference standard to assess the accuracy of current automatic computer algorithms, which thus produce reproducible but incorrect measurements of the QT interval. There is a scientific imperative to evaluate the most commonly used algorithms with an accurate and objective 'gold standard' and investigate novel automatic algorithms if the commonly used algorithms are found to be deficient. METHODS: This study uses a validated computer simulation of 8 different noise contaminated ECG waveforms (with known QT intervals of 461 and 495 ms), generated from a cell array using Luo-Rudy membrane kinetics and the Crank-Nicholson method, as a reference standard to assess the accuracy of commonly used QT measurement algorithms. Each ECG contaminated with 39 mixtures of noise at 3 levels of intensity was first filtered then subjected to three threshold methods (T1, T2, T3), two T wave slope methods (S1, S2) and a Novel method. The reproducibility and accuracy of each algorithm was compared for each ECG. RESULTS: The coefficient of variation for methods T1, T2, T3, S1, S2 and Novel were 0.36, 0.23, 1.9, 0.93, 0.92 and 0.62 respectively. For ECGs of real QT interval 461 ms the methods T1, T2, T3, S1, S2 and Novel calculated the mean QT intervals(standard deviations) to be 379.4(1.29), 368.5(0.8), 401.3(8.4), 358.9(4.8), 381.5(4.6) and 464(4.9) ms respectively. For ECGs of real QT interval 495 ms the methods T1, T2, T3, S1, S2 and Novel calculated the mean QT intervals(standard deviations) to be 396.9(1.7), 387.2(0.97), 424.9(8.7), 386.7(2.2), 396.8(2.8) and 493(0.97) ms respectively. These results showed significant differences between means at >95% confidence level. Shifting ECG baselines caused large errors of QT interval with T1 and T2 but no error with Novel. CONCLUSION: The algorithms T2, T1 and Novel gave low coefficients of variation for QT measurement. The Novel technique gave the most accurate measurement of QT interval, T3 (a differential threshold method) was the next most accurate by a large margin. The objective and accurate 'gold standard' presented in this paper may be useful to assess new QT measurement algorithms. The Novel algorithm may prove to be more accurate and reliable method to measure the QT interval.

T Wave Alternans in high arrhythmic risk patients: analysis in time and frequency domains: a pilot study.

BACKGROUND: T wave alternans (TA) is a repolarisation phenomenon manifesting as a microvolt beat to beat change in the amplitude of the T wave and ST segment. TA has been shown to be a predictor of arrhythmic risk in unselected myocardial infarction populations. TA has not been used to differentiate risk within the ischaemic cardiomyopathy population. METHODS: The subjects investigated comprised, Group 1: 7 stable patients with remote (>20 months) extensive myocardial scarring and no arrhythmic events (NYHA 3 and 4). Group2: 9 post infarction patients with malignant arrhythmia and implantable defibrillator. During breath holding, 20 continuous QRST complexes from each patients X, Y and Z leads were digitally recorded. Time domain, resultant absolute difference vectors (ATA), were calculated for alternate resultant T wave sequences. Group differences between the magnitude and temporal distribution of mean ATAs and their spectral and cross-spectral analysis were compared. RESULTS: Group 1 v Group 2 mean ATAs were 10.7 (7.17) v 11.7 (8.48) respectively, not significant. Each group had a homogenous temporal distribution of ATAs. Both group's largest mean ATA frequency components were between 0 to 25 Hz, the largest ATA component being at the DC frequency. Cross spectral analysis showed no significant differences in group ATA frequency content. CONCLUSION: The frequency content and microvolt magnitude of T wave alternans was not significantly different in these two groups. The specificity of T wave alternans for differentiating arrhythmic risk in post infarction scarring and heart failure needs investigation.