155 resultados para Synthetic biology


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The major components of blood vessels are the vascular endothelium and its supporting smooth muscle. Significant strides have been made in the understanding of the cellular and molecular biology of these two cell types and in particular their interactions have been the subject of much interest and debate over the past two decades. The vascular endothelium is now known to profoundly influence the synthetic and motor functions of the underlying smooth muscle and participate in the pathogenesis of all the major vascular disorders. Similarly, the vascular smooth muscle has important effects on the overlying endothelium, and any disruption in the cellular physiology of either cell type can result in dysfunction with important effects on blood flow and vascular permeability The majority of this accumulated knowledge relates to the vascular cells of the macrocirculation. Pericytes are the supporting cells of the microvasculature and a body of evidence is now available to show that similar regulatory mechanisms and vessel-wall cross-talk exists between these cells and the microvascular endothelium. Nowhere are these interactions more important than in the retinal microcirculation where autoregulation is vital for the maintenance of smooth and uninterrrupted blood flow. This review focuses on the interactions between retinal microvascular endothelial cells and their associated pericytes and examines the role of the endothelial cell and the pericyte in the pathogenesis of disease.

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Tryptophyllins are a group of small (4–14 amino acids), heterogenous peptides, mostly from the skins of hylid frogs from the genera, Phyllomedusa and Litoria. To date, more than forty TPHs have been discovered in species from these two genera. Here, we describe the identification of a novel tryptophyllin type 3 peptide, PhT-3, from the extracts of skin of the orange-legged monkey frog, Phyllomedusa hypochondrialis, and molecular cloning of its precursor-encoding cDNA from a cDNA library constructed from the same skin sample. Full primary structural characterization was achieved using a combination of direct Edman degradation, mass spectrometry and deduction from cloned skin-derived cDNA. The open-reading frame of the precursor cDNA was found to consist of 63 amino acid residues. The mature peptide arising from this precursor contains a post-translationally modified N-terminal pyroglutamate (pGlu) residue, formed from acid-mediated cyclization of an N-terminal Gln (Q) residue, and with the structure: pGlu-Asp-Lys-Pro-Phe-Trp-Pro-Pro-Pro-Ile-Tyr-Pro-Met. Pharmacological assessment of a synthetic replicate of this peptide on phenylephrine preconstricted rat tail artery segments, revealed a reduction in relaxation induced by bradykinin. PhT-3 was also found to mediate antiproliferative effects on human prostate cancer cell lines.

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We investigate whether pure deflagration models ofChandrasekhar-mass carbon-oxygen white dwarf stars can account for one or more subclass of the observed population of Type Ia supernova (SN Ia) explosions. We compute a set of 3D full-star hydrodynamic explosion models, in which the deflagration strength is parametrized using the multispot ignition approach. For each model, we calculate detailed nucleosynthesis yields in a post-processing step with a 384 nuclide nuclear network. We also compute synthetic observables with our 3D Monte Carlo radiative transfer code for comparison with observations. For weak and intermediate deflagration strengths (energy release E {less-than or approximate} 1.1 × 10 erg), we find that the explosion leaves behind a bound remnant enriched with 3 to 10 per cent (by mass) of deflagration ashes. However, we do not obtain the large kick velocities recently reported in the literature. We find that weak deflagrations with E ~ 0.5 × 10 erg fit well both the light curves and spectra of 2002cx-like SNe Ia, and models with even lower explosion energies could explain some of the fainter members of this subclass. By comparing our synthetic observables with the properties of SNe Ia, we can exclude the brightest, most vigorously ignited models as candidates for any observed class of SN Ia: their B-V colours deviate significantly from both normal and 2002cx-like SNe Ia and they are too bright to be candidates for other subclasses.

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In a companion paper, Seitenzahl et al. have presented a set of three-dimensional delayed detonation models for thermonuclear explosions of near-Chandrasekhar-mass white dwarfs (WDs). Here,we present multidimensional radiative transfer simulations that provide synthetic light curves and spectra for those models. The model sequence explores both changes in the strength of the deflagration phase (which is controlled by the ignition configuration in our models) and the WD central density. In agreement with previous studies, we find that the strength of the deflagration significantly affects the explosion and the observables. Variations in the central density also have an influence on both brightness and colour, but overall it is a secondary parameter in our set of models. In many respects, the models yield a good match to the observed properties of normal Type Ia supernovae (SNe Ia): peak brightness, rise/decline time-scales and synthetic spectra are all in reasonable agreement. There are, however, several differences. In particular, the models are systematically too red around maximum light, manifest spectral line velocities that are a little too high and yield I-band light curves that do not match observations. Although some of these discrepancies may simply relate to approximations made in the modelling, some pose real challenges to the models. If viewed as a complete sequence, our models do not reproduce the observed light-curve width- luminosity relation (WLR) of SNe Ia: all our models show rather similar B-band decline rates, irrespective of peak brightness. This suggests that simple variations in the strength of the deflagration phase in Chandrasekhar-mass deflagration-to-detonation models do not readily explain the observed diversity of normal SNe Ia. This may imply that some other parameter within the Chandrasekhar-mass paradigm is key to the WLR, or that a substantial fraction of normal SNe Ia arise from an alternative explosion scenario.

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This work presents the possibility of optimising 3D Organised Mesoporous Silica (OMS) coated with both iron and aluminium oxides for the optimal removal of As(III) and As(V) from synthetic contaminated water. The materials developed were fully characterised and were tested for removing arsenic in batch experiments. The effect of total Al to Fe oxides coating on the selective removal of As(III) and As(V) was studied. It was shown that 8% metal coating was the optimal configuration for the coated OMS materials in removing arsenic. The effect of arsenic initial concentration and pH, kinetics and diffusion mechanisms was studied, modelled and discussed. It was shown that the advantage of an organised material over an un-structured sorbent was very limited in terms of kinetic and diffusion under the experimental conditions. It was shown that physisorption was the main adsorption process involved in As removal by the coated OMS. Maximum adsorption capacity of 55 mg As(V).g-1 was noticed at pH 5 for material coated with 8% Al oxides while 35 mg As(V).g-1 was removed at pH 4 for equivalent material coated with Fe oxides.

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Mapped topographic features are important for understanding processes that sculpt the Earth’s surface. This paper presents maps that are the primary product of an exercise that brought together 27 researchers with an interest in landform mapping wherein the efficacy and causes of variation in mapping were tested using novel synthetic DEMs containing drumlins. The variation between interpreters (e.g. mapping philosophy, experience) and across the study region (e.g. woodland prevalence) opens these factors up to assessment. A priori known answers in the synthetics increase the number and strength of conclusions that may be drawn with respect to a traditional comparative study. Initial results suggest that overall detection rates are relatively low (34–40%), but reliability of mapping is higher (72–86%). The maps form a reference dataset.

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Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms.

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Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ∼2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

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Background: Oncology is a field that profits tremendously from the genomic data generated by high-throughput technologies, including next-generation sequencing. However, in order to exploit, integrate, visualize and interpret such high-dimensional data efficiently, non-trivial computational and statistical analysis methods are required that need to be developed in a problem-directed manner.

Discussion: For this reason, computational cancer biology aims to fill this gap. Unfortunately, computational cancer biology is not yet fully recognized as a coequal field in oncology, leading to a delay in its maturation and, as an immediate consequence, an under-exploration of high-throughput data for translational research.

Summary: Here we argue that this imbalance, favoring 'wet lab-based activities', will be naturally rectified over time, if the next generation of scientists receives an academic education that provides a fair and competent introduction to computational biology and its manifold capabilities. Furthermore, we discuss a number of local educational provisions that can be implemented on university level to help in facilitating the process of harmonization.