Stochastic modelling of muscle recruitment during activity

Muscle forces can be selected from a space of muscle recruitment strategies that produce stable motion and variable muscle and joint forces. However, current optimization methods provide only a single muscle recruitment strategy. We modelled the spectrum of muscle recruitment strategies while walking. The equilibrium equations at the joints, muscle constraints, static optimization solutions and 15-channel electromyography (EMG) recordings for seven walking cycles were taken from earlier studies. The spectrum of muscle forces was calculated using Bayesian statistics and Markov chain Monte Carlo (MCMC) methods, whereas EMG-driven muscle forces were calculated using EMG-driven modelling. We calculated the differences between the spectrum and EMG-driven muscle force for 1–15 input EMGs, and we identified the muscle strategy that best matched the recorded EMG pattern. The best-fit strategy, static optimization solution and EMG-driven force data were compared using correlation analysis. Possible and plausible muscle forces were defined as within physiological boundaries and within EMG boundaries. Possible muscle and joint forces were calculated by constraining the muscle forces between zero and the peak muscle force. Plausible muscle forces were constrained within six selected EMG boundaries. The spectrum to EMG-driven force difference increased from 40 to 108 N for 1–15 EMG inputs. The best-fit muscle strategy better described the EMG-driven pattern (R2 = 0.94; RMSE = 19 N) than the static optimization solution (R2 = 0.38; RMSE = 61 N). Possible forces for 27 of 34 muscles varied between zero and the peak muscle force, inducing a peak hip force of 11.3 body-weights. Plausible muscle forces closely matched the selected EMG patterns; no effect of the EMG constraint was observed on the remaining muscle force ranges. The model can be used to study alternative muscle recruitment strategies in both physiological and pathophysiological neuromotor conditions

Inverse Modeling for MEG/EEG data

We provide an overview of the state-of-the-art for mathematical methods that are used to reconstruct brain activity from neurophysiological data. After a brief introduction on the mathematics of the forward problem, we discuss standard and recently proposed regularization methods, as well as Monte Carlo techniques for Bayesian inference. We classify the inverse methods based on the underlying source model, and discuss advantages and disadvantages. Finally we describe an application to the pre-surgical evaluation of epileptic patients.Comment: 15 pages, 1 figur

Analysis of the electromagnetic radiation generated by a multipactor discharge occurring within a microwave passive component

International audienceMultipactoring is a non-linear phenomenon that appears in highpower microwave equipments operating under vacuum conditions and causes several undesirable effects. In this manuscript, a theoretical and experimental study of the RF spectrum radiated by a multipactor discharge, occurring within a realistic microwave component based on rectangular waveguides, is reported. The electromagnetic coupling of a multipactor current to the fundamental propagative mode of a uniform waveguide has been analyzed in the context of the microwave network theory. The discharge produced under a single-carrier RF voltage regime has been approached as a shunt current source exciting such a mode in a transmission-line gap-region. By means of a simple equivalent circuit, this model allows predicting the harmonics generated by the discharge occurring in a realistic passive waveguide component. Power spectrum radiated by a third order multipactor discharge has been measured in an E-plane silver-plated waveguide transformer, thus validating qualitatively the presented theory to simulate the noise generated by a single-carrier multipactor discharge

Design, Manufacture and Characterization of an Acoustic Barrier Made of Multi-Phenomena Cylindrical Scatterers Arranged in a Fractal-Based Geometry

In this work we present the design and the manufacturing processes, as well as the acoustics standard-ization tests, of an acoustic barrier formed by a set of multi-phenomena cylindrical scatterers. Periodic arrangements of acoustic scatterers embedded in a fluid medium with different physical properties are usually called Sonic Crystals. The multiple scattering of waves inside these structures leads to attenuation bands related to the periodicity of the structure by means of Bragg scattering. In order to design the acoustic barrier, two strategies have been used: First, the arrangement of scatterers is based on fractal geometries to maximize the Bragg scattering; econd, multi-phenomena scatterers with several noise con- trol mechanisms, as resonances or absorption, are designed and used to construct the periodic array. The acoustic barrier reported in this work provides a high technological solution in the field of noise control.This work was supported by MCI Secretaria de Estado de Investigacion (Spanish government) and the FEDER funds, under Grant No. MAT2009-09438 and by Universitat Politecnica de Valencia (Programa INNOVA 2010) under grant "INNOVA 2010 PDC PANTALLA ACUSTICA". The authors would like to thank Applus+ (LGAI Technological Center S.A.) for their help. V.R.G. is grateful for the support of post-doctoral contracts of the UPV (CEI-01-11).Castiñeira Ibáñez, S.; Rubio Michavila, C.; Romero García, V.; Sánchez Pérez, JV.; García Raffi, LM. (2012). Design, Manufacture and Characterization of an Acoustic Barrier Made of Multi-Phenomena Cylindrical Scatterers Arranged in a Fractal-Based Geometry. Archives of Acoustics. 37(4):455-462. https://doi.org/10.2478/v10168-012-0057-9S45546237

Hierarchical Bayesian level set inversion

The level set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the 1990s. Re- cently it has been employed in the context of Bayesian inversion, allowing for the quantification of uncertainty within the reconstruction of interfaces. However the Bayesian approach is very sensitive to the length and amplitude scales in the prior probabilistic model. This paper demonstrates how the scale-sensitivity can be cir- cumvented by means of a hierarchical approach, using a single scalar parameter. Together with careful con- sideration of the development of algorithms which en- code probability measure equivalences as the hierar- chical parameter is varied, this leads to well-defined Gibbs based MCMC methods found by alternating Metropolis-Hastings updates of the level set function and the hierarchical parameter. These methods demon- strably outperform non-hierarchical Bayesian level set methods

Natural Killer Cell Signal Integration Balances Synapse Symmetry and Migration

Imaging immune surveillance by natural killer (NK) cells has revealed that integration of activating and inhibitory signals determines whether or not NK cells stop to kill the target cell or retain a migratory configuration

Remodelling of Cortical Actin Where Lytic Granules Dock at Natural Killer Cell Immune Synapses Revealed by Super-Resolution Microscopy

Super-resolution 3D imaging reveals remodeling of the cortical actin meshwork at the natural killer cell immune synapse, which is likely to be important for secretion of lytic granules

Cancer Genomics Identifies Regulatory Gene Networks Associated with the Transition from Dysplasia to Advanced Lung Adenocarcinomas Induced by c-Raf-1

Background: Lung cancer is a leading cause of cancer morbidity. To improve an understanding of molecular causes of disease a transgenic mouse model was investigated where targeted expression of the serine threonine kinase c-Raf to respiratory epithelium induced initialy dysplasia and subsequently adenocarcinomas. This enables dissection of genetic events associated with precancerous and cancerous lesions. Methodology/Principal Findings: By laser microdissection cancer cell populations were harvested and subjected to whole genome expression analyses. Overall 473 and 541 genes were significantly regulated, when cancer versus transgenic and non-transgenic cells were compared, giving rise to three distinct and one common regulatory gene network. At advanced stages of tumor growth predominately repression of gene expression was observed, but genes previously shown to be upregulated in dysplasia were also up-regulated in solid tumors. Regulation of developmental programs as well as epithelial mesenchymal and mesenchymal endothelial transition was a hall mark of adenocarcinomas. Additionaly, genes coding for cell adhesion, i.e. the integrins and the tight and gap junction proteins were repressed, whereas ligands for receptor tyrosine kinase such as epi- and amphiregulin were up-regulated. Notably, Vegfr- 2 and its ligand Vegfd, as well as Notch and Wnt signalling cascades were regulated as were glycosylases that influence cellular recognition. Other regulated signalling molecules included guanine exchange factors that play a role in an activation of the MAP kinases while several tumor suppressors i.e. Mcc, Hey1, Fat3, Armcx1 and Reck were significantly repressed. Finally, probable molecular switches forcing dysplastic cells into malignantly transformed cells could be identified. Conclusions/Significance: This study provides insight into molecular pertubations allowing dysplasia to progress further to adenocarcinoma induced by exaggerted c-Raf kinase activity