The effect of realistic geometries on the susceptibility-weighted MR signal in white matter

Purpose: To investigate the effect of realistic microstructural geometry on the susceptibility-weighted magnetic resonance (MR) signal in white matter (WM), with application to demyelination. Methods: Previous work has modeled susceptibility-weighted signals under the assumption that axons are cylindrical. In this work, we explore the implications of this assumption by considering the effect of more realistic geometries. A three-compartment WM model incorporating relevant properties based on literature was used to predict the MR signal. Myelinated axons were modeled with several cross-sectional geometries of increasing realism: nested circles, warped/elliptical circles and measured axonal geometries from electron micrographs. Signal simulations from the different microstructural geometries were compared to measured signals from a Cuprizone mouse model with varying degrees of demyelination. Results: Results from simulation suggest that axonal geometry affects the MR signal. Predictions with realistic models were significantly different compared to circular models under the same microstructural tissue properties, for simulations with and without diffusion. Conclusion: The geometry of axons affects the MR signal significantly. Literature estimates of myelin susceptibility, which are based on fitting biophysical models to the MR signal, are likely to be biased by the assumed geometry, as will any derived microstructural properties.Comment: Accepted March 4 2017, in publication at Magnetic Resonance in Medicin

Diffusion Tensor Imaging: on the assessment of data quality - a preliminary bootstrap analysis

In the field of nuclear magnetic resonance imaging, diffusion tensor imaging (DTI) has proven an important method for the characterisation of ultrastructural tissue properties. Yet various technical and biological sources of signal uncertainty may prolong into variables derived from diffusion weighted images and thus compromise data validity and reliability. To gain an objective quality rating of real raw data we aimed at implementing the previously described bootstrap methodology (Efron, 1979) and investigating its sensitivity to a selection of extraneous influencing factors. We applied the bootstrap method on real DTI data volumes of six volunteers which were varied by different acquisition conditions, smoothing and artificial noising. In addition a clinical sample group of 46 Multiple Sclerosis patients and 24 healthy controls were investigated. The response variables (RV) extracted from the histogram of the confidence intervals of fractional anisotropy were mean width, peak position and height. The addition of noising showed a significant effect when exceeding about 130% of the original background noise. The application of an edge-preserving smoothing algorithm resulted in an inverse alteration of the RV. Subject motion was also clearly depicted whereas its prevention by use of a vacuum device only resulted in a marginal improvement. We also observed a marked gender-specific effect in a sample of 24 healthy control subjects the causes of which remained unclear. In contrary to this the mere effect of a different signal intensity distribution due to illness (MS) did not alter the response variables

An enhanced fresh cadaveric model for reconstructive microsurgery training

Open access via Springer Compact Acknowledgements The generosity of the people of the North East of Scotland who donated their bodies to the University of Aberdeen for anatomical study is recognised. Their contribution is appreciated and valued. Funding The authors received no financial support for the research, authorship, and/or publication of this article.Peer reviewedPublisher PD

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

The evolution of genetic architectures underlying quantitative traits

In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in QTL mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher's blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions to qualitative trends in the genetics of human traits, and to systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis of traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.Comment: Minor changes in the text; Added supplementary materia

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 187

This supplement to Aerospace Medicine and Biology lists 247 reports, articles and other documents announced during November 1978 in Scientific and Technical Aerospace Reports (STAR) or in International Aerospace Abstracts (IAA). In its subject coverage, Aerospace Medicine and Biology concentrates on the biological, physiological, psychological, and environmental effects to which man is subjected during and following simulated or actual flight in the earth's atmosphere or in interplanetary space. References describing similar effects of biological organisms of lower order are also included. Emphasis is placed on applied research, but reference to fundamental studies and theoretical principles related to experimental development also qualify for inclusion. Each entry in the bibliography consists of a bibliographic citation accompanied in most cases by an abstract

Using Numerical Simulation to Better Understand Fixation Rates, and Establishment of a New Principle: Haldane’s Ratchet

In 1957, Haldane first described a fundamental problem with evolutionary theory. This problem eventually became widely known as “Haldane’s Dilemma”. The essence of this problem is that even given a steady supply of beneficial mutations plus deep time, the rate that such mutations reach fixation is too slow to achieve meaningful evolution. After more than 50 years, this fundamental problem remains unresolved. ReMine has gone far beyond Haldane’s original mathematical analysis, and has developed “cost theory analysis” which strongly supports Haldane’s thesis. Here we examine this long-standing problem using an entirely different approach. We employ advanced numerical simulation of the mutation/selection process to empirically measure the fixation rates of beneficial, neutral, and deleterious mutations. We do this employing both realistic and optimized population parameters. In our numerical simulations, each new mutation is tracked through time until it is either lost due to drift or becomes fixed in the population. We first confirm that our numerical simulations correctly tallying the fixation of neutral mutations. We show that neutral mutations go to fixation just as predicted by conventional theory (i.e., over deep time the fixation rate approached the gametic mutation rate). We also show that the reason the vast majority of neutral mutant alleles fail to go to fixation, is because they lost due to drift, and this rate of loss rapidly approached 100% as population size is increased. We then show that given realistic distributions of mutation fitness affects, the vast majority of all mutations (including deleterious and beneficial mutations), are similarly lost due to random drift. In terms of fixations, deleterious mutations went to fixation only slightly slower, while beneficial mutations went to fixation only slightly faster, than neutral mutations. We then perform large-scale experiments to examine the feasibility of the ape-to-man scenario over a six million year period. We analyze neutral and beneficial fixations separately (realistic Proceedings of the Seventh International Conference on Creationism. Pittsburgh, PA: Creation Science Fellowship rates of deleterious mutations could not be studied in deep time due to extinction). Using realistic parameter settings we only observe a few hundred selection-induced beneficial fixations after 300,000 generations (6 million years). Even when using highly optimal parameter settings (i.e., favorable for fixation of beneficials), we only see a few thousand selection-induced fixations. This is significant because the ape-to-man scenario requires tens of millions of selective nucleotide substitutions in the human lineage. Our empirically-determined rates of beneficial fixation are in general agreement with the fixation rate estimates derived by Haldane and ReMine using their mathematical analyses. We have therefore independently demonstrated that the findings of Haldane and ReMine are for the most part correct, and that the fundamental evolutionary problem historically known as “Haldane’s Dilemma” is very real. Previous analyses have focused exclusively on beneficial mutations. When deleterious mutations were included in our simulations, using a realistic ratio of beneficial to deleterious mutation rate, deleterious fixations vastly outnumbered beneficial fixations. Because of this, the net effect of mutation fixation should clearly create a ratchet-type mechanism which should cause continuous loss of information and decline in the size of the functional genome. We name this phenomenon “Haldane’s Ratchet”

Biomechanical behavior of bioprosthetic heart valve heterograft tissues: characterization, simulation, and performance

The use of replacement heart valves continues to grow due to the increased prevalence of valvular heart disease resulting from an ageing population. Since bioprosthetic heart valves (BHVs) continue to be the preferred replacement valve, there continues to be a strong need to develop better and more reliable BHVs through and improved the general understanding of BHV failure mechanisms. The major technological hurdle for the lifespan of the BHV implant continues to be the durability of the constituent leaflet biomaterials, which if improved can lead to substantial clinical impact. In order to develop improved solutions for BHV biomaterials, it is critical to have a better understanding of the inherent biomechanical behaviors of the leaflet biomaterials, including chemical treatment technologies, the impact of repetitive mechanical loading, and the inherent failure modes. This review seeks to provide a comprehensive overview of these issues, with a focus on developing insight on the mechanisms of BHV function and failure. Additionally, this review provides a detailed summary of the computational biomechanical simulations that have been used to inform and develop a higher level of understanding of BHV tissues and their failure modes. Collectively, this information should serve as a tool not only to infer reliable and dependable prosthesis function, but also to instigate and facilitate the design of future bioprosthetic valves and clinically impact cardiology