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

Primary cilia elongation in response to interleukin-1 mediates the inflammatory response

Primary cilia are singular, cytoskeletal organelles present in the majority of mammalian cell types where they function as coordinating centres for mechanotransduction, Wnt and hedgehog signalling. The length of the primary cilium is proposed to modulate cilia function, governed in part by the activity of intraflagellar transport (IFT). In articular cartilage, primary cilia length is increased and hedgehog signaling activated in osteoarthritis (OA). Here, we examine primary cilia length with exposure to the quintessential inflammatory cytokine interleukin-1 (IL-1), which is up-regulated in OA. We then test the hypothesis that the cilium is involved in mediating the downstream inflammatory response. Primary chondrocytes treated with IL-1 exhibited a 50 % increase in cilia length after 3 h exposure. IL-1-induced cilia elongation was also observed in human fibroblasts. In chondrocytes, this elongation occurred via a protein kinase A (PKA)-dependent mechanism. G-protein coupled adenylate cyclase also regulated the length of chondrocyte primary cilia but not downstream of IL-1. Chondrocytes treated with IL-1 exhibit a characteristic increase in the release of the inflammatory chemokines, nitric oxide and prostaglandin E2. However, in cells with a mutation in IFT88 whereby the cilia structure is lost, this response to IL-1 was significantly attenuated and, in the case of nitric oxide, completely abolished. Inhibition of IL-1-induced cilia elongation by PKA inhibition also attenuated the chemokine response. These results suggest that cilia assembly regulates the response to inflammatory cytokines. Therefore, the cilia proteome may provide a novel therapeutic target for the treatment of inflammatory pathologies, including OA

Gravitational Waves from Gravitational Collapse

Gravitational wave emission from the gravitational collapse of massive stars has been studied for more than three decades. Current state of the art numerical investigations of collapse include those that use progenitors with realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non--axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with advanced ground--based and future space--based interferometric observatories.Comment: 68 pages including 13 figures; revised version accepted for publication in Living Reviews in Relativity (http://www.livingreviews.org

Mesoscale modeling and simulation of microstructure evolution during dynamic recrystallization of a Ni-based superalloy

Microstructural evolution and plastic flow characteristics of a Ni-based superalloy were investigated using a simulative model that couples the basic metallurgical principle of dynamic recrystallization (DRX) with the twodimensional (2D) cellular automaton (CA). Variation of dislocation density with local strain of deformation is considered for accurate determination of the microstructural evolution during DRX. The grain topography, the grain size and the recrystallized fraction can be well predicted by using the developed CA model, which enables to the establishment of the relationship between the flow stress, dislocation density, recrystallized fraction volume, recrystallized grain size and the thermomechanical parameters

Satellite remote sensing data can be used to model marine microbial metabolite turnover

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Cesarean Delivery Impacts Infant Brain Development

Background and purposeThe cesarean delivery rate has increased globally in the past few decades. Neurodevelopmental outcomes associated with cesarean delivery are still unclear. This study investigated whether cesarean delivery has any effect on the brain development of offspring.Materials and methodsA total of 306 healthy children were studied retrospectively. We included 3 cohorts: 2-week-old neonates (cohort 1, n = 32/11 for vaginal delivery/cesarean delivery) and 8-year-old children (cohort 2, n = 37/23 for vaginal delivery/cesarean delivery) studied at Arkansas Children's Hospital, and a longitudinal cohort of 3-month to 5-year-old children (cohort 3, n = 164/39 for vaginal delivery/cesarean delivery) studied independently at Brown University. Diffusion tensor imaging, myelin water fraction imaging, voxel-based morphometry, and/or resting-state fMRI data were analyzed to evaluate white matter integrity, myelination, gray matter volume, and/or functional connectivity, respectively.ResultsWhile not all MR imaging techniques were shared across the institutions/cohorts, post hoc analyses showed similar results of potential effects of cesarean delivery. The cesarean delivery group in cohort 1 showed significantly lower white matter development in widespread brain regions and significantly lower functional connectivity in the brain default mode network, controlled for a number of potential confounders. No group differences were found in cohort 2 in white matter integrity or gray matter volume. Cohort 3 had significantly different trajectories of white matter myelination between groups, with those born by cesarean delivery having reduced myelin in infancy but normalizing with age.ConclusionsCesarean delivery may influence infant brain development. The impact may be transient because similar effects were not observed in older children. Further prospective and longitudinal studies may be needed to confirm these novel findings

TDP-43 induces p53-mediated cell death of cortical progenitors and immature neurons

TAR DNA-binding protein 43 (TDP-43) is a key player in neurodegenerative diseases including frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS). Accumulation of TDP-43 is associated with neuronal death in the brain. How increased and disease-causing mutant forms of TDP-43 induce cell death remains unclear. Here we addressed the role of TDP-43 during neural development and show that reduced TDP-43 causes defects in neural stem/progenitor cell proliferation but not cell death. However, overexpression of wild type and TDP-43A315T proteins induce p53-dependent apoptosis of neural stem/progenitors and human induced pluripotent cell (iPS)-derived immature cortical neurons. We show that TDP-43 induces expression of the proapoptotic BH3-only genes Bbc3 and Bax, and that p53 inhibition rescues TDP-43 induced cell death of embryonic mouse, and human cortical neurons, including those derived from TDP-43G298S ALS patient iPS cells. Hence, an increase in wild type and mutant TDP-43 induces p53-dependent cell death in neural progenitors developing neurons and this can be rescued. These findings may have important implications for accumulated or mutant TDP-43 induced neurodegenerative diseases

Defining functional diversity for lignocellulose degradation in a microbial community using multi-omics studies

Abstract\ud \ud Background\ud Lignocellulose is one of the most abundant forms of fixed carbon in the biosphere. Current industrial approaches to the degradation of lignocellulose employ enzyme mixtures, usually from a single fungal species, which are only effective in hydrolyzing polysaccharides following biomass pre-treatments. While the enzymatic mechanisms of lignocellulose degradation have been characterized in detail in individual microbial species, the microbial communities that efficiently breakdown plant materials in nature are species rich and secrete a myriad of enzymes to perform “community-level” metabolism of lignocellulose. Single-species approaches are, therefore, likely to miss important aspects of lignocellulose degradation that will be central to optimizing commercial processes.\ud \ud \ud Results\ud Here, we investigated the microbial degradation of wheat straw in liquid cultures that had been inoculated with wheat straw compost. Samples taken at selected time points were subjected to multi-omics analysis with the aim of identifying new microbial mechanisms for lignocellulose degradation that could be applied in industrial pre-treatment of feedstocks. Phylogenetic composition of the community, based on sequenced bacterial and eukaryotic ribosomal genes, showed a gradual decrease in complexity and diversity over time due to microbial enrichment. Taxonomic affiliation of bacterial species showed dominance of Bacteroidetes and Proteobacteria and high relative abundance of genera Asticcacaulis, Leadbetterella and Truepera. The eukaryotic members of the community were enriched in peritrich ciliates from genus Telotrochidium that thrived in the liquid cultures compared to fungal species that were present in low abundance. A targeted metasecretome approach combined with metatranscriptomics analysis, identified 1127 proteins and showed the presence of numerous carbohydrate-active enzymes extracted from the biomass-bound fractions and from the culture supernatant. This revealed a wide array of hydrolytic cellulases, hemicellulases and carbohydrate-binding modules involved in lignocellulose degradation. The expression of these activities correlated to the changes in the biomass composition observed by FTIR and ssNMR measurements.\ud \ud \ud Conclusions\ud A combination of mass spectrometry-based proteomics coupled with metatranscriptomics has enabled the identification of a large number of lignocellulose degrading enzymes that can now be further explored for the development of improved enzyme cocktails for the treatment of plant-based feedstocks. In addition to the expected carbohydrate-active enzymes, our studies reveal a large number of unknown proteins, some of which may play a crucial role in community-based lignocellulose degradation.This work was funded by Biotechnology and Biological Sciences Research\ud Council (BBSRC) Grants BB/1018492/1, BB/K020358/1 and BB/P027717/1, the\ud BBSRC Network in Biotechnology and Bioenergy BIOCATNET and São Paulo\ud Research Foundation (FAPESP) Grant 10/52362-5. ERdA thanks EMBRAPA\ud Instrumentation São Carlos and Dr. Luiz Alberto Colnago for providing the\ud NMR facility and CNPq Grant 312852/2014-2. The authors would like to thank\ud Deborah Rathbone and Susan Heywood from the Biorenewables Develop‑\ud ment Centre for technical assistance in rRNA amplicon sequencing