246 research outputs found

    Matching Models Across Abstraction Levels with Gaussian Processes

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    Biological systems are often modelled at different levels of abstraction depending on the particular aims/resources of a study. Such different models often provide qualitatively concordant predictions over specific parametrisations, but it is generally unclear whether model predictions are quantitatively in agreement, and whether such agreement holds for different parametrisations. Here we present a generally applicable statistical machine learning methodology to automatically reconcile the predictions of different models across abstraction levels. Our approach is based on defining a correction map, a random function which modifies the output of a model in order to match the statistics of the output of a different model of the same system. We use two biological examples to give a proof-of-principle demonstration of the methodology, and discuss its advantages and potential further applications.Comment: LNCS forma

    Differential regulation of neurotrophin expression in human bronchial smooth muscle cells

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    BACKGROUND: Human bronchial smooth muscle cells (HBSMC) may regulate airway inflammation by secreting cytokines, chemokines and growth factors. The neurotrophins, including nerve growth factor (NGF), brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3), have been shown to be elevated during airway inflammation and evoke airway hyperresponsiveness. We studied if HBSMC may be a source of NGF, BDNF and NT-3, and if so, how inflammatory cytokines may influence their production. METHODS: Basal and cytokine (IL-1β, IFN-γ, IL-4)-stimulated neurotrophin expression in HBSMC cultured in vitro was quantified. The mRNA expression was quantified by real-time RT-PCR and the protein secretion into the cell culture medium by ELISA. RESULTS: We observed a constitutive NGF, BDNF and NT-3 expression. IL-1β stimulated a transient increase of NGF, while the increase of BDNF had a later onset and was more sustained. COX-inhibitors (indomethacin and NS-398) markedly decreased IL-1β-stimulated secretion of BDNF, but not IL-1β-stimulated NGF secretion. IFN-γ increased NGF expression, down-regulated BDNF expression and synergistically enhanced IL-1β-stimulated NGF expression. In contrast, IL-4 had no effect on basal NGF and BDNF expression, but decreased IL-1β-stimulated NGF expression. NT-3 was not altered by the tested cytokines. CONCLUSION: Taken together, our data indicate that, in addition to the contractile capacity, HBSMC can express NGF, BDNF and NT-3. The expression of these neurotrophins may be differently regulated by inflammatory cytokines, suggesting a dynamic interplay that might have a potential role in airway inflammation

    Ontogenetic De Novo Copy Number Variations (CNVs) as a Source of Genetic Individuality: Studies on Two Families with MZD Twins for Schizophrenia

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    Genetic individuality is the foundation of personalized medicine, yet its determinants are currently poorly understood. One issue is the difference between monozygotic twins that are assumed identical and have been extensively used in genetic studies for decades [1]. Here, we report genome-wide alterations in two nuclear families each with a pair of monozygotic twins discordant for schizophrenia evaluated by the Affymetrix 6.0 human SNP array. The data analysis includes characterization of copy number variations (CNVs) and single nucleotide polymorphism (SNPs). The results have identified genomic differences between twin pairs and a set of new provisional schizophrenia genes. Samples were found to have between 35 and 65 CNVs per individual. The majority of CNVs (∼80%) represented gains. In addition, ∼10% of the CNVs were de novo (not present in parents), of these, 30% arose during parental meiosis and 70% arose during developmental mitosis. We also observed SNPs in the twins that were absent from both parents. These constituted 0.12% of all SNPs seen in the twins. In 65% of cases these SNPs arose during meiosis compared to 35% during mitosis. The developmental mitotic origin of most CNVs that may lead to MZ twin discordance may also cause tissue differences within individuals during a single pregnancy and generate a high frequency of mosaics in the population. The results argue for enduring genome-wide changes during cellular transmission, often ignored in most genetic analyses

    Dynamic changes in eIF4F-mRNA interactions revealed by global analyses of environmental stress responses

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    BACKGROUND: Translation factors eIF4E and eIF4G form eIF4F, which interacts with the messenger RNA (mRNA) 5' cap to promote ribosome recruitment and translation initiation. Variations in the association of eIF4F with individual mRNAs likely contribute to differences in translation initiation frequencies between mRNAs. As translation initiation is globally reprogrammed by environmental stresses, we were interested in determining whether eIF4F interactions with individual mRNAs are reprogrammed and how this may contribute to global environmental stress responses. RESULTS: Using a tagged-factor protein capture and RNA-sequencing (RNA-seq) approach, we have assessed how mRNA associations with eIF4E, eIF4G1 and eIF4G2 change globally in response to three defined stresses that each cause a rapid attenuation of protein synthesis: oxidative stress induced by hydrogen peroxide and nutrient stresses caused by amino acid or glucose withdrawal. We find that acute stress leads to dynamic and unexpected changes in eIF4F-mRNA interactions that are shared among each factor and across the stresses imposed. eIF4F-mRNA interactions stabilised by stress are predominantly associated with translational repression, while more actively initiating mRNAs become relatively depleted for eIF4F. Simultaneously, other mRNAs are insulated from these stress-induced changes in eIF4F association. CONCLUSION: Dynamic eIF4F-mRNA interaction changes are part of a coordinated early translational control response shared across environmental stresses. Our data are compatible with a model where multiple mRNA closed-loop complexes form with differing stability. Hence, unexpectedly, in the absence of other stabilising factors, rapid translation initiation on mRNAs correlates with less stable eIF4F interactions

    Is every strong lens model unhappy in its own way? Uniform modelling of a sample of 13 quadruply+ imaged quasars

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    Strong-gravitational lens systems with quadruply imaged quasars (quads) are unique probes to address several fundamental problems in cosmology and astrophysics. Although they are intrinsically very rare, ongoing and planned wide-field deep-sky surveys are set to discover thousands of such systems in the next decade. It is thus paramount to devise a general framework to model strong-lens systems to cope with this large influx without being limited by expert investigator time. We propose such a general modelling framework (implemented with the publicly available software LENSTRONOMY) and apply it to uniformly model three-band Hubble Space Telescope Wide Field Camera 3 images of 13 quads. This is the largest uniformly modelled sample of quads to date and paves the way for a variety of studies. To illustrate the scientific content of the sample, we investigate the alignment between the mass and light distribution in the deflectors. The position angles of these distributions are well-aligned, except when there is strong external shear. However, we find no correlation between the ellipticity of the light and mass distributions. We also show that the observed flux-ratios between the images depart significantly from the predictions of simple smooth models. The departures are strongest in the bluest band, consistent with microlensing being the dominant cause in addition to millilensing. Future papers will exploit this rich data set in combination with ground-based spectroscopy and time delays to determine quantities such as the Hubble constant, the free streaming length of dark matter, and the normalization of the initial stellar mass function

    Tubulin isoform composition tunes microtubule dynamics

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    Microtubules polymerize and depolymerize stochastically, a behavior essential for cell division, motility and differentiation. While many studies advanced our understanding of how microtubule-associated proteins tune microtubule dynamics in trans, we have yet to understand how tubulin genetic diversity regulates microtubule functions. The majority of in vitro dynamics studies are performed with tubulin purified from brain tissue. This preparation is not representative of tubulin found in many cell types. Here we report the 4.2Å cryo-EM structure and in vitro dynamics parameters of α1B/βI+βIVb microtubules assembled from tubulin purified from a human embryonic kidney cell line with isoform composition characteristic of fibroblasts and many immortalized cell lines. We find that these microtubules grow faster and transition to depolymerization less frequently compared to brain microtubules. Cryo-EM reveals that the dynamic ends of α1B/βI+βIVb microtubules are less tapered and that these tubulin heterodimers display lower curvatures. Interestingly, analysis of EB1 distributions at dynamic ends suggests no differences in GTP cap sizes. Lastly, we show that the addition of recombinant α1A/βIII tubulin, a neuronal isotype overexpressed in many tumors, proportionally tunes the dynamics of α1B/βI+βIVb microtubules. Our study is an important step towards understanding how tubulin isoform composition tunes microtubule dynamics

    On the relative bias of void tracers in the Dark Energy Survey

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    Luminous tracers of large-scale structure are not entirely representative of the distribution of mass in our Universe. As they arise from the highest peaks in the matter density field, the spatial distribution of luminous objects is biased towards those peaks. On large scales, where density fluctuations are mild, this bias simply amounts to a constant offset in the clustering amplitude of the tracer, known as linear bias. In this work we focus on the relative bias between galaxies and galaxy clusters that are located inside and in the vicinity of cosmic voids, extended regions of relatively low density in the large-scale structure of the Universe. With the help of mock data we verify that the relation between galaxy and cluster overdensity around voids remains linear. Hence, the void-centric density profiles of different tracers can be linked by a single multiplicative constant. This amounts to the same value as the relative linear bias between tracers for the largest voids in the sample. For voids of small sizes, which typically arise in higher density regions, this constant has a higher value, possibly showing an environmental dependence similar to that observed for the linear bias itself. We confirm our findings by analysing data obtained during the first year of observations by the Dark Energy Survey. As a side product, we present the first catalogue of three-dimensional voids extracted from a photometric survey with a controlled photo-z uncertainty. Our results will be relevant in forthcoming analyses that attempt to use voids as cosmological probes

    Dark Energy Survey Year 1 results: the effect of intracluster light on photometric redshifts for weak gravitational lensing

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    We study the effect of diffuse intracluster light on the critical surface mass density estimated from photometric redshifts of lensing source galaxies, and the resulting bias in a weak lensing measurement of galaxy cluster mass. Under conservative assumptions, we find the bias to be negligible for imaging surveys like the Dark Energy Survey with a recommended scale cut of ≥200kpc distance from cluster centres. For significantly deeper lensing source galaxy catalogues from present and future surveys like the Large Synoptic Survey Telescope program, more conservative scale and source magnitude cuts or a correction of the effect may be necessary to achieve percent level lensing measurement accuracy, especially at the massive end of the cluster population

    Dark Energy Survey Year 1 results: validation of weak lensing cluster member contamination estimates from P(z) decomposition

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    Weak lensing source galaxy catalogues used in estimating the masses of galaxy clusters can be heavily contaminated by cluster members, prohibiting accurate mass calibration. In this study, we test the performance of an estimator for the extent of cluster member contamination based on decomposing the photometric redshift P(z) of source galaxies into contaminating and background components. We perform a full scale mock analysis on a simulated sky survey approximately mirroring the observational properties of the Dark Energy Survey Year One observations (DES Y1), and find excellent agreement between the true number profile of contaminating cluster member galaxies in the simulation and the estimated one. We further apply the method to estimate the cluster member contamination for the DES Y1 redMaPPer cluster mass calibration analysis, and compare the results to an alternative approach based on the angular correlation of weak lensing source galaxies. We find indications that the correlation based estimates are biased by the selection of the weak lensing sources in the cluster vicinity, which does not strongly impact the P(z) decomposition method. Collectively, these benchmarks demonstrate the strength of the P(z) decomposition method in alleviating membership contamination and enabling highly accurate cluster weak lensing studies without broad exclusion of source galaxies, thereby improving the total constraining power of cluster mass calibration via weak lensing
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