A multiscale active structural model of the arterial wall accounting for smooth muscle dynamics

Arterial wall dynamics arise from the synergy of passive mechano-elastic properties of the vascular tissue and the active contractile behaviour of smooth muscle cells (SMCs) that form the media layer of vessels. We have developed a computational framework that incorporates both these components to account for vascular responses to mechanical and pharmacological stimuli. To validate the proposed framework and demonstrate its potential for testing hypotheses on the pathogenesis of vascular disease, we have employed a number of pharmacological probes that modulate the arterial wall contractile machinery by selectively inhibiting a range of intracellular signalling pathways. Experimental probes used on ring segments from the rabbit central ear artery are: phenylephrine, a selective α1-adrenergic receptor agonist that induces vasoconstriction; cyclopiazonic acid (CPA), a specific inhibitor of sarcoplasmic/endoplasmic reticulum Ca2+-ATPase; and ryanodine, a diterpenoid that modulates Ca2+ release from the sarcoplasmic reticulum. These interventions were able to delineate the role of membrane versus intracellular signalling, previously identified as main factors in smooth muscle contraction and the generation of vessel tone. Each SMC was modelled by a system of nonlinear differential equations that account for intracellular ionic signalling, and in particular Ca2+ dynamics. Cytosolic Ca2+ concentrations formed the catalytic input to a cross-bridge kinetics model. Contractile output from these cellular components forms the input to the finite-element model of the arterial rings under isometric conditions that reproduces the experimental conditions. The model does not account for the role of the endothelium, as the nitric oxide production was suppressed by the action of L-NAME, and also due to the absence of shear stress on the arterial ring, as the experimental set-up did not involve flow. Simulations generated by the integrated model closely matched experimental observations qualitatively, as well as quantitatively within a range of physiological parametric values. The model also illustrated how increased intercellular coupling led to smooth muscle coordination and the genesis of vascular tone

The spectral variability of FSRQs

The optical variability of 29 flat spectrum radio quasars in SDSS Stripe 82 region are investigated by using DR7 released multi-epoch data. All FSRQs show variations with overall amplitude ranging from 0.24 mag to 3.46 mag in different sources. About half of FSRQs show a bluer-when-brighter trend, which is commonly observed for blazars. However, only one source shows a redder-when-brighter trend, which implies it is rare in FSRQs. In this source, the thermal emission may likely be responsible for the spectral behavior.Comment: 4 pages, 1 figure, to be published in Journal of Astrophysics and Astronomy, as a proceeding paper of the conference "Multiwavelength Variability of Blazars", Guangzhou, China, September 22-24, 201

HCN ice in Titan's high-altitude southern polar cloud

Titan's middle atmosphere is currently experiencing a rapid change of season after northern spring arrived in 2009. A large cloud was observed for the first time above Titan's southern pole in May 2012, at an altitude of 300 km. This altitude previously showed a temperature maximum and condensation was not expected for any of Titan's atmospheric gases. Here we show that this cloud is composed of micron-sized hydrogen cyanide (HCN) ice particles. The presence of HCN particles at this altitude, together with new temperature determinations from mid-infrared observations, indicate a very dramatic cooling of Titan's atmosphere inside the winter polar vortex in early 2012. Such a cooling is completely contrary to previously measured high-altitude warming in the polar vortex, and temperatures are a hundred degrees colder than predicted by circulation models. Besides elucidating the nature of Titan's mysterious polar cloud, these results thus show that post-equinox cooling at the winter pole is much more efficient than previously thought.Comment: Published in Nature on 2 October 2014. This is the author version, before final editing by Natur

Reservists and veterans: Viewed from within and without

This chapter describes two important groups relative to military service – reservists and veterans. Definitions are provided regarding who is a member of each group. A summary of past and current research findings for each group is provided. The summary is organized by investigative topics or themes, which provide the current scope of the field for reservists and for veterans. Finally, approaches to the study of reservists and veterans are described, along with challenges – both substantively and methodologically – for future research studies. These serve as fertile areas for improvements and investigations in future research studies

A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

<p>Abstract</p> <p>Background</p> <p>Autoregressive regression coefficients for <it>Anopheles arabiensis </it>aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of <it>An. arabiensis </it>aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of <it>An. arabiensis </it>aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled <it>Anopheles </it>aquatic habitat covariates. A test for diagnostic checking error residuals in an <it>An. arabiensis </it>aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature.</p> <p>Methods</p> <p>Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4^®was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS^®database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3^®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix.</p> <p>Results</p> <p>By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with <it>An. arabiensis </it>aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled <it>An. arabiensis </it>aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat.</p> <p>Conclusion</p> <p>An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific <it>An. arabiensis </it>aquatic habitats based on larval/pupal productivity.</p

Prospecting environmental mycobacteria: combined molecular approaches reveal unprecedented diversity

Background: Environmental mycobacteria (EM) include species commonly found in various terrestrial and aquatic environments, encompassing animal and human pathogens in addition to saprophytes. Approximately 150 EM species can be separated into fast and slow growers based on sequence and copy number differences of their 16S rRNA genes. Cultivation methods are not appropriate for diversity studies; few studies have investigated EM diversity in soil despite their importance as potential reservoirs of pathogens and their hypothesized role in masking or blocking M. bovis BCG vaccine. Methods: We report here the development, optimization and validation of molecular assays targeting the 16S rRNA gene to assess diversity and prevalence of fast and slow growing EM in representative soils from semi tropical and temperate areas. New primer sets were designed also to target uniquely slow growing mycobacteria and used with PCR-DGGE, tag-encoded Titanium amplicon pyrosequencing and quantitative PCR. Results: PCR-DGGE and pyrosequencing provided a consensus of EM diversity; for example, a high abundance of pyrosequencing reads and DGGE bands corresponded to M. moriokaense, M. colombiense and M. riyadhense. As expected pyrosequencing provided more comprehensive information; additional prevalent species included M. chlorophenolicum, M. neglectum, M. gordonae, M. aemonae. Prevalence of the total Mycobacterium genus in the soil samples ranged from 2.3×107 to 2.7×108 gene targets g−1; slow growers prevalence from 2.9×105 to 1.2×107 cells g−1. Conclusions: This combined molecular approach enabled an unprecedented qualitative and quantitative assessment of EM across soil samples. Good concordance was found between methods and the bioinformatics analysis was validated by random resampling. Sequences from most pathogenic groups associated with slow growth were identified in extenso in all soils tested with a specific assay, allowing to unmask them from the Mycobacterium whole genus, in which, as minority members, they would have remained undetected

Application of Photogrammetry in Biomedical Science

Peer reviewedPostprin

Melanoma cells break down LPA to establish local gradients that drive chemotactic dispersal.

The high mortality of melanoma is caused by rapid spread of cancer cells, which occurs unusually early in tumour evolution. Unlike most solid tumours, thickness rather than cytological markers or differentiation is the best guide to metastatic potential. Multiple stimuli that drive melanoma cell migration have been described, but it is not clear which are responsible for invasion, nor if chemotactic gradients exist in real tumours. In a chamber-based assay for melanoma dispersal, we find that cells migrate efficiently away from one another, even in initially homogeneous medium. This dispersal is driven by positive chemotaxis rather than chemorepulsion or contact inhibition. The principal chemoattractant, unexpectedly active across all tumour stages, is the lipid agonist lysophosphatidic acid (LPA) acting through the LPA receptor LPAR1. LPA induces chemotaxis of remarkable accuracy, and is both necessary and sufficient for chemotaxis and invasion in 2-D and 3-D assays. Growth factors, often described as tumour attractants, cause negligible chemotaxis themselves, but potentiate chemotaxis to LPA. Cells rapidly break down LPA present at substantial levels in culture medium and normal skin to generate outward-facing gradients. We measure LPA gradients across the margins of melanomas in vivo, confirming the physiological importance of our results. We conclude that LPA chemotaxis provides a strong drive for melanoma cells to invade outwards. Cells create their own gradients by acting as a sink, breaking down locally present LPA, and thus forming a gradient that is low in the tumour and high in the surrounding areas. The key step is not acquisition of sensitivity to the chemoattractant, but rather the tumour growing to break down enough LPA to form a gradient. Thus the stimulus that drives cell dispersal is not the presence of LPA itself, but the self-generated, outward-directed gradient

γ-Glutamylcysteine detoxifies reactive oxygen species by acting as glutathione peroxidase-1 cofactor

Reactive oxygen species regulate redox-signaling processes, but in excess they can cause cell damage, hence underlying the aetiology of several neurological diseases. Through its ability to down modulate reactive oxygen species, glutathione is considered an essential thiol-antioxidant derivative, yet under certain circumstances it is dispensable for cell growth and redox control. Here we show, by directing the biosynthesis of γ-glutamylcysteine—the immediate glutathione precursor—to mitochondria, that it efficiently detoxifies hydrogen peroxide and superoxide anion, regardless of cellular glutathione concentrations. Knocking down glutathione peroxidase-1 drastically increases superoxide anion in cells synthesizing mitochondrial γ-glutamylcysteine. In vitro, γ-glutamylcysteine is as efficient as glutathione in disposing of hydrogen peroxide by glutathione peroxidase-1. In primary neurons, endogenously synthesized γ-glutamylcysteine fully prevents apoptotic death in several neurotoxic paradigms and, in an in vivo mouse model of neurodegeneration, γ-glutamylcysteine protects against neuronal loss and motor impairment. Thus, γ-glutamylcysteine takes over the antioxidant and neuroprotective functions of glutathione by acting as glutathione peroxidase-1 cofactor

TRAIL Death Receptor-4, Decoy Receptor-1 and Decoy Receptor-2 Expression on CD8+ T Cells Correlate with the Disease Severity in Patients with Rheumatoid Arthritis

BACKGROUND: Rheumatoid Arthritis (RA) is a chronic autoimmune inflammatory disorder. Although the pathogenesis of disease is unclear, it is well known that T cells play a major role in both development and perpetuation of RA through activating macrophages and B cells. Since the lack of TNF-Related Apoptosis Inducing Ligand (TRAIL) expression resulted in defective thymocyte apoptosis leading to an autoimmune disease, we explored evidence for alterations in TRAIL/TRAIL receptor expression on peripheral T lymphocytes in the molecular mechanism of RA development. METHODS: The expression of TRAIL/TRAIL receptors on T cells in 20 RA patients and 12 control individuals were analyzed using flow cytometry. The correlation of TRAIL and its receptor expression profile was compared with clinical RA parameters (RA activity scored as per DAS28) using Spearman Rho Analysis. RESULTS: While no change was detected in the ratio of CD4+ to CD8+ T cells between controls and RA patient groups, upregulation of TRAIL and its receptors (both death and decoy) was detected on both CD4+ and CD8+ T cells in RA patients compared to control individuals. Death Receptor-4 (DR4) and the decoy receptors DcR1 and DcR2 on CD8+ T cells, but not on CD4+ T cells, were positively correlated with patients' DAS scores. CONCLUSIONS: Our data suggest that TRAIL/TRAIL receptor expression profiles on T cells might be important in revelation of RA pathogenesis