Regularized autoregressive model preserving spatial discontinuities for analysis of radio-frequency (RF) signals in echographic images

Cet article traite de l'estimation spectrale locale à partir de signaux radio-fréquence obtenus en imagerie médicale par échographie ultrasonore. Du fait de la nature particulière des signaux RF (signaux aléatoires fortement bruités et non-stationnaires et présence de plusieurs milieux tissulaires), l'objectif principal est de régulariser l'estimation paramétrique locale tout en préservant d'éventuelles discontinuités. Nous proposons un shéma de régularisation 2D basé sur les modèles autorégressifs, introduit dans un cadre Bayesien où l'a-priori de continuité spatiale est exprimé par l'intermédiaire des champs de Markov. L'utilisation de fonctions non quadratiques (phi-fonctions) dans le terme d'a-priori permet de preserver les discontinuités. Nous appliquons tout d'abord cette méthode sur des simulations où des discontinuités spectrales ont été générées par un décalage de la fréquence centrale entre 2 milieux. Nous montrons comment le shéma de régularisation permet d'améliorer considérablement l'estimation des coefficients AR. De plus, l'utilisation des Phi-fonctions s'avère très efficace pour préserver les discontinuités. Enfin, nous appliquons cette méthode sur des signaux radio-fréquence acquis à l'Université de Leuven avec un système développé pour l'acqisition de tels signaux et adapté à un échographe conventionnel. Ces résultats montrent l'intérêt de cette méthode pour l'étude de signaux réels acquis in-vivo sur des tissus biologiques en conditions cliniques

Treatment- and Population-Dependent Activity Patterns of Behavioral and Expression QTLs

Genetic control of gene expression and higher-order phenotypes is almost invariably dependent on environment and experimental conditions. We use two families of recombinant inbred strains of mice (LXS and BXD) to study treatment- and genotype-dependent control of hippocampal gene expression and behavioral phenotypes. We analyzed responses to all combinations of two experimental perturbations, ethanol and restraint stress, in both families, allowing for comparisons across 8 combinations of treatment and population. We introduce the concept of QTL activity patterns to characterize how associations between genomic loci and traits vary across treatments. We identified several significant behavioral QTLs and many expression QTLs (eQTLs). The behavioral QTLs are highly dependent on treatment and population. We classified eQTLs into three groups: cis-eQTLs (expression variation that maps to within 5 Mb of the cognate gene), syntenic trans-eQTLs (the gene and the QTL are on the same chromosome but not within 5 Mb), and non-syntenic trans-eQTLs (the gene and the QTL are on different chromosomes). We found that most non-syntenic trans-eQTLs were treatment-specific whereas both classes of syntenic eQTLs were more conserved across treatments. We also found there was a correlation between regions along the genome enriched for eQTLs and SNPs that were conserved across the LXS and BXD families. Genes with eQTLs that co-localized with the behavioral QTLs and displayed similar QTL activity patterns were identified as potential candidate genes associated with the phenotypes, yielding identification of novel genes as well as genes that have been previously associated with responses to ethanol

Intermediate filament cytoskeleton of the liver in health and disease

Intermediate filaments (IFs) represent the largest cytoskeletal gene family comprising ~70 genes expressed in tissue specific manner. In addition to scaffolding function, they form complex signaling platforms and interact with various kinases, adaptor, and apoptotic proteins. IFs are established cytoprotectants and IF variants are associated with >30 human diseases. Furthermore, IF-containing inclusion bodies are characteristic features of several neurodegenerative, muscular, and other disorders. Acidic (type I) and basic keratins (type II) build obligatory type I and type II heteropolymers and are expressed in epithelial cells. Adult hepatocytes contain K8 and K18 as their only cytoplasmic IF pair, whereas cholangiocytes express K7 and K19 in addition. K8/K18-deficient animals exhibit a marked susceptibility to various toxic agents and Fas-induced apoptosis. In humans, K8/K18 variants predispose to development of end-stage liver disease and acute liver failure (ALF). K8/K18 variants also associate with development of liver fibrosis in patients with chronic hepatitis C. Mallory-Denk bodies (MDBs) are protein aggregates consisting of ubiquitinated K8/K18, chaperones and sequestosome1/p62 (p62) as their major constituents. MDBs are found in various liver diseases including alcoholic and non-alcoholic steatohepatitis and can be formed in mice by feeding hepatotoxic substances griseofulvin and 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC). MDBs also arise in cell culture after transfection with K8/K18, ubiquitin, and p62. Major factors that determine MDB formation in vivo are the type of stress (with oxidative stress as a major player), the extent of stress-induced protein misfolding and resulting chaperone, proteasome and autophagy overload, keratin 8 excess, transglutaminase activation with transamidation of keratin 8 and p62 upregulation

What does an interferometer really measure? Including instrument and data characteristics in the reconstruction of the 21cm power spectrum

Combining the visibilities measured by an interferometer to form a cosmological power spectrum is a complicated process in which the window functions play a crucial role. In a delay-based analysis, the mapping between instrumental space, made of per-baseline delay spectra, and cosmological space is not a one-to-one relation. Instead, neighbouring modes contribute to the power measured at one point, with their respective contributions encoded in the window functions. To better understand the power spectrum measured by an interferometer, we assess the impact of instrument characteristics and analysis choices on the estimator by deriving its exact window functions, outside of the delay approximation. Focusing on HERA as a case study, we find that observations made with long baselines tend to correspond to enhanced low-k tails of the window functions, which facilitate foreground leakage outside the wedge, whilst the choice of bandwidth and frequency taper can help narrow them down. With the help of simple test cases and more realistic visibility simulations, we show that, apart from tracing mode mixing, the window functions can accurately reconstruct the power spectrum estimator of simulated visibilities. We note that the window functions depend strongly on the chromaticity of the beam, and less on its spatial structure - a Gaussian approximation, ignoring side lobes, is sufficient. Finally, we investigate the potential of asymmetric window functions, down-weighting the contribution of low-k power to avoid foreground leakage. The window functions presented in this work correspond to the latest HERA upper limits for the full Phase I data. They allow an accurate reconstruction of the power spectrum measured by the instrument and can be used in future analyses to confront theoretical models and data directly in cylindrical space.Comment: 18 pages, 18 figures, submitted to MNRAS. Comments welcome

Improved Constraints on the 21 cm EoR Power Spectrum and the X-Ray Heating of the IGM with HERA Phase I Observations

We report the most sensitive upper limits to date on the 21 cm epoch of reionization power spectrum using 94 nights of observing with Phase I of the Hydrogen Epoch of Reionization Array (HERA). Using similar analysis techniques as in previously reported limits (HERA Collaboration 2022a), we find at 95% confidence that $\Delta^2(k = 0.34$ $h$ Mpc$^{-1}$) $\leq 457$ mK$^2$ at $z = 7.9$ and that $\Delta^2 (k = 0.36$ $h$ Mpc$^{-1}) \leq 3,496$ mK$^2$ at $z = 10.4$, an improvement by a factor of 2.1 and 2.6 respectively. These limits are mostly consistent with thermal noise over a wide range of $k$ after our data quality cuts, despite performing a relatively conservative analysis designed to minimize signal loss. Our results are validated with both statistical tests on the data and end-to-end pipeline simulations. We also report updated constraints on the astrophysics of reionization and the cosmic dawn. Using multiple independent modeling and inference techniques previously employed by HERA Collaboration (2022b), we find that the intergalactic medium must have been heated above the adiabatic cooling limit at least as early as $z = 10.4$, ruling out a broad set of so-called "cold reionization" scenarios. If this heating is due to high-mass X-ray binaries during the cosmic dawn, as is generally believed, our result's 99% credible interval excludes the local relationship between soft X-ray luminosity and star formation and thus requires heating driven by evolved low-metallicity stars.Comment: 57 pages, 37 figures. Updated to match the accepted ApJ version. Corresponding author: Joshua S. Dillo

Direct Optimal Mapping Image Power Spectrum and its Window Functions

The key to detecting neutral hydrogen during the epoch of reionization (EoR) is to separate the cosmological signal from the dominating foreground radiation. We developed direct optimal mapping (Xu et al. 2022) to map interferometric visibilities; it contains only linear operations, with full knowledge of point spread functions from visibilities to images. Here we present an FFT-based image power spectrum and its window functions based on direct optimal mapping. We use noiseless simulation, based on the Hydrogen Epoch of Reionization Array (HERA) Phase I configuration, to study the image power spectrum properties. The window functions show $<10^{-11}$ power leakage from the foreground-dominated region into the EoR window; the 2D and 1D power spectra also verify the separation between the foregrounds and the EoR. Furthermore, we simulated visibilities from a $uv$-complete array and calculated its image power spectrum. The result shows that the foreground--EoR leakage is further suppressed below $10^{-12}$, dominated by the tapering function sidelobes; the 2D power spectrum does not show signs of the horizon wedge. The $uv$-complete result provides a reference case for future 21cm cosmology array designs.Comment: Submitted to Ap

Euclid preparation. TBD. Forecast impact of super-sample covariance on 3x2pt analysis with Euclid

Deviations from Gaussianity in the distribution of the fields probed by large-scale structure surveys generate additional terms in the data covariance matrix, increasing the uncertainties in the measurement of the cosmological parameters. Super-sample covariance (SSC) is among the largest of these non-Gaussian contributions, with the potential to significantly degrade constraints on some of the parameters of the cosmological model under study -- especially for weak lensing cosmic shear. We compute and validate the impact of SSC on the forecast uncertainties on the cosmological parameters for the Euclid photometric survey, obtained with a Fisher matrix analysis, both considering the Gaussian covariance alone and adding the SSC term -- computed through the public code PySSC. The photometric probes are considered in isolation and combined in the `3$\times$2pt' analysis. We find the SSC impact to be non-negligible -- halving the Figure of Merit of the dark energy parameters ($w_0$, $w_a$) in the 3$\times$2pt case and substantially increasing the uncertainties on $\Omega_{{\rm m},0}, w_0$, and $\sigma_8$ for cosmic shear; photometric galaxy clustering, on the other hand, is less affected due to the lower probe response. The relative impact of SSC does not show significant changes under variations of the redshift binning scheme, while it is smaller for weak lensing when marginalising over the multiplicative shear bias nuisance parameters, which also leads to poorer constraints on the cosmological parameters. Finally, we explore how the use of prior information on the shear and galaxy bias changes the SSC impact. Improving shear bias priors does not have a significant impact, while galaxy bias must be calibrated to sub-percent level to increase the Figure of Merit by the large amount needed to achieve the value when SSC is not included.Comment: 22 pages, 13 figure

Targeting Huntington’s disease through histone deacetylases

Huntington’s disease (HD) is a debilitating neurodegenerative condition with significant burdens on both patient and healthcare costs. Despite extensive research, treatment options for patients with this condition remain limited. Aberrant post-translational modification (PTM) of proteins is emerging as an important element in the pathogenesis of HD. These PTMs include acetylation, phosphorylation, methylation, sumoylation and ubiquitination. Several families of proteins are involved with the regulation of these PTMs. In this review, I discuss the current evidence linking aberrant PTMs and/or aberrant regulation of the cellular machinery regulating these PTMs to HD pathogenesis. Finally, I discuss the evidence suggesting that pharmacologically targeting one of these protein families the histone deacetylases may be of potential therapeutic benefit in the treatment of HD