Functional modularity of nuclear hormone receptors in a Caenorhabditis elegans metabolic gene regulatory network

We present the first gene regulatory network (GRN) that pertains to post-developmental gene expression. Specifically, we mapped a transcription regulatory network of Caenorhabditis elegans metabolic gene promoters using gene-centered yeast one-hybrid assays. We found that the metabolic GRN is enriched for nuclear hormone receptors (NHRs) compared with other gene-centered regulatory networks, and that these NHRs organize into functional network modules.The NHR family has greatly expanded in nematodes; C. elegans has 284 NHRs, whereas humans have only 48. We show that the NHRs in the metabolic GRN have metabolic phenotypes, suggesting that they do not simply function redundantly.The mediator subunit MDT-15 preferentially interacts with NHRs that occur in the metabolic GRN.We describe an NHR circuit that responds to nutrient availability and propose a model for the evolution and organization of NHRs in C. elegans metabolic regulatory networks

Stellar Inversion Techniques

Stellar seismic inversions have proved to be a powerful technique for probing the internal structure of stars, and paving the way for a better understanding of the underlying physics by revealing some of the shortcomings in current stellar models. In this lecture, we provide an introduction to this topic by explaining kernel-based inversion techniques. Specifically, we explain how various kernels are obtained from the pulsation equations, and describe inversion techniques such as the Regularised Least-Squares (RLS) and Optimally Localised Averages (OLA) methods.Comment: 20 pages, 8 figures. Lecture presented at the IVth Azores International Advanced School in Space Sciences on "Asteroseismology and Exoplanets: Listening to the Stars and Searching for New Worlds" (arXiv:1709.00645), which took place in Horta, Azores Islands, Portugal in July 201

Constraining warm dark matter with cosmic shear power spectra

We investigate potential constraints from cosmic shear on the dark matter particle mass, assuming all dark matter is made up of light thermal relic particles. Given the theoretical uncertainties involved in making cosmological predictions in such warm dark matter scenarios we use analytical fits to linear warm dark matter power spectra and compare (i) the halo model using a mass function evaluated from these linear power spectra and (ii) an analytical fit to the non-linear evolution of the linear power spectra. We optimistically ignore the competing effect of baryons for this work. We find approach (ii) to be conservative compared to approach (i). We evaluate cosmological constraints using these methods, marginalising over four other cosmological parameters. Using the more conservative method we find that a Euclid-like weak lensing survey together with constraints from the Planck cosmic microwave background mission primary anisotropies could achieve a lower limit on the particle mass of 2.5 keV.Comment: 26 pages, 9 figures, minor changes to match the version accepted for publication in JCA

Constraining primordial non-Gaussianity with cosmological weak lensing: shear and flexion

We examine the cosmological constraining power of future large-scale weak lensing surveys on the model of \emph{Euclid}, with particular reference to primordial non-Gaussianity. Our analysis considers several different estimators of the projected matter power spectrum, based on both shear and flexion, for which we review the covariances and Fisher matrices. The bounds provided by cosmic shear alone for the local bispectrum shape, marginalized over $\sigma_8$, are at the level of $\Delta f_\mathrm{NL} \sim 100$. We consider three additional bispectrum shapes, for which the cosmic shear constraints range from $\Delta f_\mathrm{NL}\sim 340$ (equilateral shape) up to $\Delta f_\mathrm{NL}\sim 500$ (orthogonal shape). The competitiveness of cosmic flexion constraints against cosmic shear ones depends on the galaxy intrinsic flexion noise, that is still virtually unconstrained. Adopting the very high value that has been occasionally used in the literature results in the flexion contribution being basically negligible with respect to the shear one, and for realistic configurations the former does not improve significantly the constraining power of the latter. Since the flexion noise decreases with decreasing scale, by extending the analysis up to $\ell_\mathrm{max} = 20,000$ cosmic flexion, while being still subdominant, improves the shear constraints by $\sim 10$ when added. However on such small scales the highly non-linear clustering of matter and the impact of baryonic physics make any error estimation uncertain. By considering lower, and possibly more realistic, values of the flexion intrinsic shape noise results in flexion constraining power being a factor of $\sim 2$ better than that of shear, and the bounds on $\sigma_8$ and $f_\mathrm{NL}$ being improved by a factor of $\sim 3$ upon their combination. (abridged)Comment: 30 pages, 4 figures, 4 tables. To appear on JCA

Toward an internally consistent astronomical distance scale

Accurate astronomical distance determination is crucial for all fields in astrophysics, from Galactic to cosmological scales. Despite, or perhaps because of, significant efforts to determine accurate distances, using a wide range of methods, tracers, and techniques, an internally consistent astronomical distance framework has not yet been established. We review current efforts to homogenize the Local Group's distance framework, with particular emphasis on the potential of RR Lyrae stars as distance indicators, and attempt to extend this in an internally consistent manner to cosmological distances. Calibration based on Type Ia supernovae and distance determinations based on gravitational lensing represent particularly promising approaches. We provide a positive outlook to improvements to the status quo expected from future surveys, missions, and facilities. Astronomical distance determination has clearly reached maturity and near-consistency.Comment: Review article, 59 pages (4 figures); Space Science Reviews, in press (chapter 8 of a special collection resulting from the May 2016 ISSI-BJ workshop on Astronomical Distance Determination in the Space Age

B cell activity is impaired in human and mouse obesity and is responsive to an essential fatty acid upon murine influenza infection

Obesity is associated with increased risk for infections and poor responses to vaccinations, which may be due to compromised B cell function. However, there is limited information about the influence of obesity on B cell function and underlying factors that modulate B cell responses. Therefore, we studied B cell cytokine secretion and/or Ab production across obesity models. In obese humans, B cell IL-6 secretion was lowered and IgM levels were elevated upon ex vivo anti-BCR/TLR9 stimulation. In murine obesity induced by a high fat diet, ex vivo IgM and IgG were elevated with unstimulated B cells. Furthermore, the high fat diet lowered bone marrow B cell frequency accompanied by diminished transcripts of early lymphoid commitment markers. Murine B cell responses were subsequently investigated upon influenza A/Puerto Rico/8/34 infection using a Western diet model in the absence or presence of docosahexaenoic acid (DHA). DHA, an essential fatty acid with immunomodulatory properties, was tested because its plasma levels are lowered in obesity. Relative to controls, mice consuming theWestern diet had diminished Ab titers whereas theWestern diet plus DHA improved titers. Mechanistically, DHA did not directly target B cells to elevate Ab levels. Instead, DHA increased the concentration of the downstream specialized proresolving lipid mediators (SPMs) 14-hydroxydocosahexaenoic acid, 17-hydroxydocosahexaenoic acid, and protectin DX. All three SPMs were found to be effective in elevating murine Ab levels upon influenza infection. Collectively, the results demonstrate that B cell responses are impaired across human and mouse obesity models and show that essential fatty acid status is a factor influencing humoral immunity, potentially through an SPM-mediated mechanism

Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns

Folate is vital for fetal development. Periconceptional folic acid supplementation and food fortification are recommended to prevent neural tube defects. Mechanisms whereby periconceptional folate influences normal development and disease are poorly understood: epigenetics may be involved. We examine the association between maternal plasma folate during pregnancy and epigenome-wide DNA methylation using Illumina" s HumanMethyl450 Beadchip in 1,988 newborns from two European cohorts. Here we report the combined covariate-adjusted results using meta-analysis and employ pathway and gene expression analyses. Four-hundred forty-three CpGs (320 genes) are significantly associated with maternal plasma folate levels during pregnancy (false discovery rate 5%); 48 are significant after Bonferroni correction. Most genes are not known for folate biology, including APC2, GRM8, SLC16A12, OPCML, PRPH, LHX1, KLK4 and PRSS21. Some relate to birth defects other than neural tube defects, neurological functions or varied aspects of embryonic development. These findings may inform how maternal folate impacts the developing epigenome and health outcomes in offspring

A novel coupling of noise reduction algorithms for particle flow simulations

Proper orthogonal decomposition (POD) and its extension based on time-windows have been shown to greatly improve the effectiveness of recovering smooth ensemble solutions from noisy particle data. However, to successfully de-noise any molecular system, a large number of measurements still need to be provided. In order to achieve a better efficiency in processing time-dependent fields, we have combined POD with a well-established signal processing technique, wavelet-based thresholding. In this novel hybrid procedure, the wavelet filtering is applied within the POD domain and referred to as WAVinPOD. The algorithm exhibits promising results when applied to both synthetically generated signals and particle data. In this work, the simulations compare the performance of our new approach with standard POD or wavelet analysis in extracting smooth profiles from noisy velocity and density fields. Numerical examples include molecular dynamics and dissipative particle dynamics simulations of unsteady force- and shear-driven liquid flows, as well as phase separation phenomenon. Simulation results confirm that WAVinPOD preserves the dimensionality reduction obtained using POD, while improving its filtering properties through the sparse representation of data in wavelet basis. This paper shows that WAVinPOD outperforms the other estimators for both synthetically generated signals and particle-based measurements, achieving a higher signal-to-noise ratio from a smaller number of samples. The new filtering methodology offers significant computational savings, particularly for multi-scale applications seeking to couple continuum informations with atomistic models. It is the first time that a rigorous analysis has compared de-noising techniques for particle-based fluid simulations