Kelch proteins: emerging roles in skeletal muscle development and diseases

Our understanding of genes that cause skeletal muscle disease has increased tremendously over the past three decades. Advances in approaches to genetics and genomics have aided in the identification of new pathogenic mechanisms in rare genetic disorders and have opened up new avenues for therapeutic interventions by identification of new molecular pathways in muscle disease. Recent studies have identified mutations of several Kelch proteins in skeletal muscle disorders. The Kelch superfamily is one of the largest evolutionary conserved gene families. The 66 known family members all possess a Kelch-repeat containing domain and are implicated in diverse biological functions. In skeletal muscle development, several Kelch family members regulate the processes of proliferation and/or differentiation resulting in normal functioning of mature muscles. Importantly, many Kelch proteins function as substrate-specific adaptors for Cullin E3 ubiquitin ligase (Cul3), a core component of the ubiquitin-proteasome system to regulate the protein turnover. This review discusses the emerging roles of Kelch proteins in skeletal muscle function and disease

Finite difference time domain modeling of steady state scattering from jet engines with moving turbine blades

The approach chosen to model steady state scattering from jet engines with moving turbine blades is based upon the Finite Difference Time Domain (FDTD) method. The FDTD method is a numerical electromagnetic program based upon the direct solution in the time domain of Maxwell's time dependent curl equations throughout a volume. One of the strengths of this method is the ability to model objects with complicated shape and/or material composition. General time domain functions may be used as source excitations. For example, a plane wave excitation may be specified as a pulse containing many frequencies and at any incidence angle to the scatterer. A best fit to the scatterer is accomplished using cubical cells in the standard cartesian implementation of the FDTD method. The material composition of the scatterer is determined by specifying its electrical properties at each cell on the scatterer. Thus, the FDTD method is a suitable choice for problems with complex geometries evaluated at multiple frequencies. It is assumed that the reader is familiar with the FDTD method

Periodic Neural Activity Induced by Network Complexity

We study a model for neural activity on the small-world topology of Watts and Strogatz and on the scale-free topology of Barab\'asi and Albert. We find that the topology of the network connections may spontaneously induce periodic neural activity, contrasting with chaotic neural activities exhibited by regular topologies. Periodic activity exists only for relatively small networks and occurs with higher probability when the rewiring probability is larger. The average length of the periods increases with the square root of the network size.Comment: 4 pages, 5 figure

Scaling law for the transient behavior of type-II neuron models

We study the transient regime of type-II biophysical neuron models and determine the scaling behavior of relaxation times $\tau$ near but below the repetitive firing critical current, $\tau \simeq C (I_c-I)^{-\Delta}$. For both the Hodgkin-Huxley and Morris-Lecar models we find that the critical exponent is independent of the numerical integration time step and that both systems belong to the same universality class, with $\Delta = 1/2$. For appropriately chosen parameters, the FitzHugh-Nagumo model presents the same generic transient behavior, but the critical region is significantly smaller. We propose an experiment that may reveal nontrivial critical exponents in the squid axon.Comment: 6 pages, 9 figures, accepted for publication in Phys. Rev.

Genomic organization and single-nucleotide polymorphism map of desmuslin, a novel intermediate filament protein on chromosome 15q26.3

BACKGROUND: Desmuslin is an α-dystrobrevin-interacting protein expressed primarily in heart and skeletal muscle. The desmuslin protein interacts with and is closely related to desmin, a protein encoded by a locus mutated in some forms of hereditary distal myopathy. As a muscle-specific intermediate filament protein, desmuslin is also a candidate for myopathies of unknown etiology. RESULTS: The desmuslin gene was localized to chromosome 15q26.3 by electronic screening of the human DNA sequence database. Primer pairs were designed to amplify the 5 exons of the desmuslin gene in 11 overlapping DNA segments. The desmuslin gene was screened for mutations in 71 patients with various forms of myopathy for which there was no known cause. In this analysis, 10 common and 2 rare amino acid altering single-nucleotide polymorphisms were identified, all of which were seen in a control population of individuals thus making these unlikely causes of the phenotype. Interestingly, one of the single-nucleotide polymorphisms found in a patient resulted in a premature stop codon in the first exon. The nonsense mutation was also detected in the patient's unaffected father and one unaffected control; it was detected in 0.44% (2/454) of unrelated chromosomes and is therefore predicted to have a homozygous frequency of 0.002%. CONCLUSION: No causative mutations were found in the desmuslin gene. However, the single-nucleotide polymorphisms mapped in this study represent a well-mapped group that can be used for disequilibrium studies of this region of chromosome 15q26.3

Does the 1/f frequency-scaling of brain signals reflect self-organized critical states?

Many complex systems display self-organized critical states characterized by 1/f frequency scaling of power spectra. Global variables such as the electroencephalogram, scale as 1/f, which could be the sign of self-organized critical states in neuronal activity. By analyzing simultaneous recordings of global and neuronal activities, we confirm the 1/f scaling of global variables for selected frequency bands, but show that neuronal activity is not consistent with critical states. We propose a model of 1/f scaling which does not rely on critical states, and which is testable experimentally.Comment: 3 figures, 6 page

Wireless Local Area Network Performance Inside Aircraft Passenger Cabins

An examination of IEEE 802.11 wireless network performance within an aircraft fuselage is performed. This examination measured the propagated RF power along the length of the fuselage, and the associated network performance: the link speed, total throughput, and packet losses and errors. A total of four airplanes: one single-aisle and three twin-aisle airplanes were tested with 802.11a, 802.11b, and 802.11g networks

Self-Organized Criticality model for Brain Plasticity

Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Here we present a model based on self-organized criticality and taking into account brain plasticity, which is able to reproduce the spectrum of electroencephalograms (EEG). The model consists in an electrical network with threshold firing and activity-dependent synapse strenghts. The system exhibits an avalanche activity power law distributed. The analysis of the power spectra of the electrical signal reproduces very robustly the power law behaviour with the exponent 0.8, experimentally measured in EEG spectra. The same value of the exponent is found on small-world lattices and for leaky neurons, indicating that universality holds for a wide class of brain models.Comment: 4 pages, 3 figure

TERC polymorphisms are associated both with susceptibility to colorectal cancer and with longer telomeres.

Shorter telomeres have been associated with increased risk of malignancy, including colorectal cancer (CRC). Telomere length is heritable and may be an intermediate phenotype linked to genetic susceptibility to CRC

Self-organization without conservation: Are neuronal avalanches generically critical?

Recent experiments on cortical neural networks have revealed the existence of well-defined avalanches of electrical activity. Such avalanches have been claimed to be generically scale-invariant -- i.e. power-law distributed -- with many exciting implications in Neuroscience. Recently, a self-organized model has been proposed by Levina, Herrmann and Geisel to justify such an empirical finding. Given that (i) neural dynamics is dissipative and (ii) there is a loading mechanism "charging" progressively the background synaptic strength, this model/dynamics is very similar in spirit to forest-fire and earthquake models, archetypical examples of non-conserving self-organization, which have been recently shown to lack true criticality. Here we show that cortical neural networks obeying (i) and (ii) are not generically critical; unless parameters are fine tuned, their dynamics is either sub- or super-critical, even if the pseudo-critical region is relatively broad. This conclusion seems to be in agreement with the most recent experimental observations. The main implication of our work is that, if future experimental research on cortical networks were to support that truly critical avalanches are the norm and not the exception, then one should look for more elaborate (adaptive/evolutionary) explanations, beyond simple self-organization, to account for this.Comment: 28 pages, 11 figures, regular pape