Neuromuscular junction morphology, fiber-type proportions, and satellite-cell proliferation rates are altered in MyoD(-/-) mice

Gene compensation by members of the myogenic regulatory factor (MRF) family has been proposed to explain the apparent normal adult phenotype of MyoD(-/-) mice. Nerve and field stimulation were used to investigate contraction properties of muscle from MyoD(-/-) mice, and molecular approaches were used to investigate satellite-cell behavior. We demonstrate that MyoD deletion results in major alterations in the organization of the neuromuscular junction, which have a dramatic influence on the physiological contractile properties of skeletal muscle. Second, we show that the lineage progression of satellite cells (especially initial proliferation) in the absence of MyoD is abnormal and linked to perturbations in the nuclear localization of beta-catenin, a key readout of canonical Wnt signaling. These results show that MyoD has unique functions in both developing and adult skeletal muscle that are not carried out by other members of the MRF family.

Double-gyroid morphology of a polystyrene-block-poly(ferrocenylethylmethylsilane) diblock copolymer: a route to ordered bicontinuous nanoscale architectures

A polystyrene-block-poly(ferrocenylethylmethylsilane) diblock copolymer, displaying a double-gyroid morphology when self-assembled in the solid state, has been prepared with a PFEMS volume fraction phi(PFMS)=0.39 and a total molecular weight of 64 000 Da by sequential living anionic polymerisation. A block copolymer with a metal-containing block with iron and silicon in the main chain was selected due to its plasma etch resistance compared to the organic block. Self-assembly of the diblock copolymer in the bulk showed a stable, double-gyroid morphology as characterised by TEM. SAXS confirmed that the structure belonged to the Ia3d space group.

Relation between neuronal morphology and electrophysiology in the Kainate lesion model of Alzheimer's Disease

This paper describes a computational and statistical study of the influence of morphological changes on the electrophysiological response of neurons from an animal model of Alzheimer's Disease (AD). We combined experimental morphological data from rat hippocampal CA1 pyramidal cells with a well-established model of active membrane properties. Dendritic morphology and the somatic response to simulated current clamp conditions were then compared for cells from the control and the AD group. The computational approach allowed us to single out the influences of neuromorphology on neuronal response by eliminating the effects of active channel variability. The results did not reveal a simple relationship between morphological changes associated with AD and changes in neural response. However, they did suggest the existence of more complex than anticipated relationships between dendritic morphology and single-cell electrophysiology.

Generation, description and storage of dendritic morphology data

It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.

Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study

We investigated the effect of morphological differences on neuronal firing behavior within the hippocampal CA3 pyramidal cell family by using three-dimensional reconstructions of dendritic morphology in computational simulations of electrophysiology. In this paper, we report for the first time that differences in dendritic structure within the same morphological class can have a dramatic influence on the firing rate and firing mode (spiking versus bursting and type of bursting). Our method consisted of converting morphological measurements from three-dimensional neuroanatomical data of CA3 pyramidal cells into a computational simulator format. In the simulation, active channels were distributed evenly across the cells so that the electrophysiological differences observed in the neurons would only be due to morphological differences. We found that differences in the size of the dendritic tree of CA3 pyramidal cells had a significant qualitative and quantitative effect on the electrophysiological response. Cells with larger dendritic trees: (1) had a lower burst rate, but a higher spike rate within a burst, (2) had higher thresholds for transitions from quiescent to bursting and from bursting to regular spiking and (3) tended to burst with a plateau. Dendritic tree size alone did not account for all the differences in electrophysiological responses. Differences in apical branching, such as the distribution of branch points and terminations per branch order, appear to effect the duration of a burst. These results highlight the importance of considering the contribution of morphology in electrophysiological and simulation studies.

Evolution of coronal mass ejection morphology with increasing heliocentric distance. II. In Situ observations

Interplanetary coronal mass ejections (ICMEs) are often observed to travel much faster than the ambient solar wind. If the relative speed between the two exceeds the fast magnetosonic velocity, then a shock wave will form. The Mach number and the shock standoff distance ahead of the ICME leading edge is measured to infer the vertical size of an ICME in a direction that is perpendicular to the solar wind flow. We analyze the shock standoff distance for 45 events varying between 0.5 AU and 5.5 AU in order to infer their physical dimensions. We find that the average ratio of the inferred vertical size to measured radial width, referred to as the aspect ratio, of an ICME is 2.8 ± 0.5. We also compare these results to the geometrical predictions from Paper I that forecast an aspect ratio between 3 and 6. The geometrical solution varies with heliocentric distance and appears to provide a theoretical maximum for the aspect ratio of ICMEs. The minimum aspect ratio appears to remain constant at 1 (i.e., a circular cross section) for all distances. These results suggest that possible distortions to the leading edge of ICMEs are frequent. But, these results may also indicate that the constants calculated in the empirical relationship correlating the different shock front need to be modified; or perhaps both distortions and a change in the empirical formulae are required.

Reading Derrida on mathematics

This article engages with the claims of Anne Brubaker that “[n]ow that the dust has settled after the so-called ‘Science Wars’ […] it is an opportune time to reassess the ways in which poststructural theory both argues persuasively for mathematics as a culturally embedded practice – a method as opposed to a metaphysics – and, at the same time, reinscribes realist notions of mathematics as a noise-free description of a mind independent reality.” Through a close re-reading of Jacques Derrida’s work I argue, in alliance with Vicki Kirby’s critique of the work of Brian Rotman, not only that Brubaker misunderstands Derrida’s “writing” but also that her argument constitutes a typical instance of much wider misreadings of Derrida and “poststructuralism” across a range of disciplines in terms of the ways in which her text re-institutes the very stabilities it itself attributes to Derrida’s texts.