Inflammatory responses in primary muscle cell cultures in Atlantic salmon (Salmo salar)

Peer reviewedPublisher PD

Estimation of age-stratified contact rates during the COVID-19 pandemic using a novel inference algorithm

Well parameterized epidemiological models including accurate representation of contacts are fundamental to controlling epidemics. However, age-stratified contacts are typically estimated from pre-pandemic/peace-time surveys, even though interventions and public response likely alter contacts. Here, we fit age-stratified models, including re-estimation of relative contact rates between age classes, to public data describing the 2020–2021 COVID-19 outbreak in England. This data includes age-stratified population size, cases, deaths, hospital admissions and results from the Coronavirus Infection Survey (almost 9000 observations in all). Fitting stochastic compartmental models to such detailed data is extremely challenging, especially considering the large number of model parameters being estimated (over 150). An efficient new inference algorithm ABC-MBP combining existing approximate Bayesian computation (ABC) methodology with model-based proposals (MBPs) is applied. Modified contact rates are inferred alongside time-varying reproduction numbers that quantify changes in overall transmission due to pandemic response, and age-stratified proportions of asymptomatic cases, hospitalization rates and deaths. These inferences are robust to a range of assumptions including the values of parameters that cannot be estimated from available data. ABC-MBP is shown to enable reliable joint analysis of complex epidemiological data yielding consistent parametrization of dynamic transmission models that can inform data-driven public health policy and interventions. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'

Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission

BACKGROUND: The spread of infectious diseases in populations is controlled by the susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection), and recoverability (propensity to recover/die) of individuals. Estimating genetic risk factors for these three underlying host epidemiological traits can help reduce disease spread through genetic control strategies. Previous studies have identified important ‘disease resistance single nucleotide polymorphisms (SNPs)’, but how these affect the underlying traits is an unresolved question. Recent advances in computational statistics make it now possible to estimate the effects of SNPs on host traits from epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known about how to effectively design disease transmission experiments or field studies to maximise the precision with which these effects can be estimated. RESULTS: In this paper, we develop and validate analytical expressions for the precision of the estimates of SNP effects on the three above host traits for a disease transmission experiment with one or more non-interacting contact groups. Maximising these expressions leads to three distinct ‘experimental’ designs, each specifying a different set of ideal SNP genotype compositions across groups: (a) appropriate for a single contact-group, (b) a multi-group design termed “pure”, and (c) a multi-group design termed “mixed”, where ‘pure’ and ‘mixed’ refer to groupings that consist of individuals with uniformly the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than estimates for infectivity. Whereas the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferred because it uses information from naturally-occurring rather than artificial infections. The same design principles apply to estimates of the epidemiological impact of other categorical fixed effects, such as breed, line, family, sex, or vaccination status. Estimation of SNP effect precisions from a given experimental setup is implemented in an online software tool SIRE-PC. CONCLUSIONS: Methodology was developed to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables that underlie host susceptibility, infectivity and recoverability. Designs that maximize the precision of estimates were derived. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12711-022-00747-1

TRES predicts transcription control in embryonic stem cells.

SUMMARY: Unraveling transcriptional circuits controlling embryonic stem cell maintenance and fate has great potential for improving our understanding of normal development as well as disease. To facilitate this, we have developed a novel web tool called 'TRES' that predicts the likely upstream regulators for a given gene list. This is achieved by integrating transcription factor (TF) binding events from 187 ChIP-sequencing and ChIP-on-chip datasets in murine and human embryonic stem (ES) cells with over 1000 mammalian TF sequence motifs. Using 114 TF perturbation gene sets, as well as 115 co-expression clusters in ES cells, we validate the utility of this approach. AVAILABILITY AND IMPLEMENTATION: TRES is freely available at http://www.tres.roslin.ed.ac.uk. CONTACT: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.This work was supported by a University of Edinburgh Chancellors Fellowship awarded to AJ and strategic funding from the BBSRC. CP was funded by the Scottish Government through the Strategic Partnership for Animal Science Excellence (SPASE). The Gottgens’ lab is supported by LLR, the MRC, BBSRC, Cancer Research UK, and Wellcome Trust core support to the Cambridge Institute for Medical Research and Wellcome Trust–MRC Cambridge Stem Cell Institute.This version is the author accepted manuscript. The published advanced access version can be viewed on the journals website at: http://bioinformatics.oxfordjournals.org/content/early/2014/06/23/bioinformatics.btu399.full.pdf+htm

Long Term Radio Monitoring of SN 1993J

We present our observations of the radio emission from supernova (SN) 1993J, in M 81 (NGC 3031), made with the VLA, from 90 to 0.7 cm, as well as numerous measurements from other telescopes. The combined data set constitutes probably the most detailed set of measurements ever established for any SN outside of the Local Group in any wavelength range. Only SN 1987A in the LMC has been the subject of such an intensive observational program. The radio emission evolves regularly in both time and frequency, and the usual interpretation in terms of shock interaction with a circumstellar medium (CSM) formed by a pre-SN stellar wind describes the observations rather well considering the complexity of the phenomenon. However: 1) The 85 - 110 GHz measurements at early times are not well fitted by the parameterization, unlike the cm wavelength measurements. 2) At mid-cm wavelengths there is some deviation from the fitted radio light curves. 3) At a time ~3100 days after shock breakout, the decline rate of the radio emission steepens without change in the spectral index. This decline is best described as an exponential decay starting at day 3100 with an e-folding time of ~1100 days. 4) The best overall fit to all of the data is a model including both non-thermal synchrotron self-absorption (SSA) and a thermal free-free absorbing (FFA) components at early times, evolving to a constant spectral index, optically thin decline rate, until the break in that decline rate. Moreover, neither a purely SSA nor a purely FFA absorbing models can provide a fit that simultaneously reproduces the light curves, the spectral index evolution, and the brightness temperature evolution. 5) The radio and X-ray light curves exhibit similar behavior and suggest a sudden drop in the SN progenitor mass-loss rate at ~8000 years prior to shock breakout.Comment: 45 pages, 13 figures, accepted for Ap

The Transverse Peculiar Velocity of the Q2237+0305 Lens Galaxy and the Mean Mass of Its Stars

Using 11-years of OGLE V-band photometry of Q2237+0305, we measure the transverse velocity of the lens galaxy and the mean mass of its stars. We can do so because, for the first time, we fully include the random motions of the stars in the lens galaxy in the analysis of the light curves. In doing so, we are also able to correctly account for the Earth's parallax motion and the rotation of the lens galaxy, further reducing systematic errors. We measure a lower limit on the transverse speed of the lens galaxy, v_t > 338 km/s (68% confidence) and find a preferred direction to the East. The mean stellar mass estimate including a well-defined velocity prior is 0.12 <= 1.94 at 68% confidence, with a median of 0.52 Msun. We also show for the first time that analyzing subsets of a microlensing light curve, in this case the first and second halves of the OGLE V-band light curve, give mutually consistent physical results.Comment: 11 pages, 9 figures, 1 table; animated magnification pattern video can be found at http://www.astronomy.ohio-state.edu/~sdp/animation.avi; accepted for publication in Ap

Estimating individuals’ genetic and non-genetic effects underlying infectious disease transmission from temporal epidemic data

Individuals differ widely in their contribution to the spread of infection within and across populations. Three key epidemiological host traits affect infectious disease spread: susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection to others) and recoverability (propensity to recover quickly). Interventions aiming to reduce disease spread may target improvement in any one of these traits, but the necessary statistical methods for obtaining risk estimates are lacking. In this paper we introduce a novel software tool called SIRE (standing for "Susceptibility, Infectivity and Recoverability Estimation"), which allows for the first time simultaneous estimation of the genetic effect of a single nucleotide polymorphism (SNP), as well as non-genetic influences on these three unobservable host traits. SIRE implements a flexible Bayesian algorithm which accommodates a wide range of disease surveillance data comprising any combination of recorded individual infection and/or recovery times, or disease diagnostic test results. Different genetic and non-genetic regulations and data scenarios (representing realistic recording schemes) were simulated to validate SIRE and to assess their impact on the precision, accuracy and bias of parameter estimates. This analysis revealed that with few exceptions, SIRE provides unbiased, accurate parameter estimates associated with all three host traits. For most scenarios, SNP effects associated with recoverability can be estimated with highest precision, followed by susceptibility. For infectivity, many epidemics with few individuals give substantially more statistical power to identify SNP effects than the reverse. Importantly, precise estimates of SNP and other effects could be obtained even in the case of incomplete, censored and relatively infrequent measurements of individuals' infection or survival status, albeit requiring more individuals to yield equivalent precision. SIRE represents a new tool for analysing a wide range of experimental and field disease data with the aim of discovering and validating SNPs and other factors controlling infectious disease transmission

The Optical, Ultraviolet, and X-ray Structure of the Quasar HE 0435-1223

Microlensing has proven an effective probe of the structure of the innermost regions of quasars, and an important test of accretion disk models. We present light curves of the lensed quasar HE 0435-1223 in the R band and in the ultraviolet, and consider them together with X-ray light curves in two energy bands that are presented in a companion paper. Using a Bayesian Monte Carlo method, we constrain the size of the accretion disk in the rest-frame near- and far-UV, and constrain for the first time the size of the X-ray emission regions in two X-ray energy bands. The R-band scale size of the accretion disk is about 10^15.23 cm (~23 r_g), slightly smaller than previous estimates, but larger than would be predicted from the quasar flux. In the UV, the source size is weakly constrained, with a strong prior dependence. The UV to R-band size ratio is consistent with the thin disk model prediction, with large error bars. In soft and hard X-rays, the source size is smaller than ~10^14.8 cm (~10 r_g) at 95% confidence. We do not find evidence of structure in the X-ray emission region, as the most likely value for the ratio of the hard X-ray size to the soft X-ray size is unity. Finally, we find that the most likely value for the mean mass of stars in the lens galaxy is ~0.3 M_sun, consistent with other studies.Comment: 13 pages, 7 figures. Replaced with version accepted to Ap

Impact of vaccination and selective breeding on the transmission of Infectious salmon anemia virus

publishedVersio

X-ray Monitoring of Gravitational Lenses With Chandra

We present \emph{Chandra} monitoring data for six gravitationally lensed quasars: QJ 0158$-$4325, HE 0435$-$1223, HE 1104$-$1805, SDSS 0924+0219, SDSS 1004+4112, and Q 2237+0305. We detect X-ray microlensing variability in all six lenses with high confidence. We detect energy dependent microlensing in HE 0435$-$1223, SDSS 1004+4112, SDSS 0924+0219 and Q 2237+0305. We present a detailed spectral analysis for each lens, and find that simple power-law models plus Gaussian emission lines give good fits to the spectra. We detect intrinsic spectral variability in two epochs of Q 2237+0305. We detect differential absorption between images in four lenses. We also detect the \feka\ emission line in all six lenses, and the Ni XXVII K$\alpha$ line in two images of Q 2237+0305. The rest frame equivalent widths of the \feka\ lines are measured to be 0.4--1.2 keV, significantly higher than those measured in typical active galactic nuclei of similar X-ray luminosities. This suggests that the \feka\ emission region is more compact or centrally concentrated than the continuum emission region.Comment: 55 pages, 22 figure