Strong HI Lyman-α\alpha variations from the 11 Gyr-old host star Kepler-444: a planetary origin ?

Kepler-444 provides a unique opportunity to probe the atmospheric composition and evolution of a compact system of exoplanets smaller than the Earth. Five planets transit this bright K star at close orbital distances, but they are too small for their putative lower atmosphere to be probed at optical/infrared wavelengths. We used the Space Telescope Imaging Spectrograph instrument onboard the Hubble Space Telescope to search for the signature of the planet's upper atmospheres at six independent epochs in the Ly-$\alpha$ line. We detect significant flux variations during the transits of both Kepler-444e and f (~20%), and also at a time when none of the known planets was transiting (~40%). Variability in the transition region and corona of the host star might be the source of these variations. Yet, their amplitude over short time scales (~2-3 hours) is surprisingly strong for this old (11.2+-1.0Gyr) and apparently quiet main-sequence star. Alternatively, we show that the in-transits variations could be explained by absorption from neutral hydrogen exospheres trailing the two outer planets (Kepler-444e and f). They would have to contain substantial amounts of water to replenish such hydrogen exospheres, which would reveal them as the first confirmed ocean-planets. The out-of-transit variations, however, would require the presence of a yet-undetected Kepler-444g at larger orbital distance, casting doubt on the planetary origin scenario. Using HARPS-N observations in the sodium doublet, we derived the properties of two Interstellar Medium clouds along the line-of-sight toward Kepler-444. This allowed us to reconstruct the stellar Ly-$\alpha$ line profile and to estimate the XUV irradiation from the star, which would still allow for a moderate mass loss from the outer planets after 11.2Gyr. Follow-up of the system at XUV wavelengths will be required to assess this tantalizing possibility.Comment: Accepted for publication in A&A Name of the system added to the title in most recent versio

Higher-order block-structured hex meshing of tubular structures

Numerical simulations of the cardiovascular system are growing in popularity due to the increasing availability of computational power, and their proven contribution to the understanding of pathodynamics and validation of medical devices with in-silico trials as a potential future breakthrough. Such simulations are performed on volumetric meshes reconstructed from patient-specific imaging data. These meshes are most often unstructured, and result in a brutally large amount of elements, significantly increasing the computational complexity of the simulations, whilst potentially adversely affecting their accuracy. To reduce such complexity, we introduce a new approach for fully automatic generation of higher-order, structured hexahedral meshes of tubular structures, with a focus on healthy blood vessels. The structures are modeled as skeleton-based convolution surfaces. From the same skeleton, the topology is captured by a block-structure, and the geometry by a higher-order surface mesh. Grading may be induced to obtain tailored refinement, thus resolving, e.g., boundary layers. The volumetric meshing is then performed via transfinite mappings. The resulting meshes are of arbitrary order, their elements are of good quality, while the spatial resolution may be as coarse as needed, greatly reducing computing time. Their suitability for practical applications is showcased by a simulation of physiological blood flow modelled by a generalised Newtonian fluid in the human aorta

The Sensitivity and Specificity of Markers for Event Times

The statistical literature on assessing the accuracy of risk factors or disease markers as diagnostic tests deals almost exclusively with settings where the test, Y, is measured concurrently with disease status D. In practice, however, disease status may vary over time and there is often a time lag between when the marker is measured and the occurrence of disease. One example concerns the Framingham Risk Score as a marker for the future risk of cardiovascular events, events that occur after the score is ascertained. To evaluate such a marker, one needs to take the time lag into account since the accuracy may be higher when the marker is measured closer to the time of disease occurrence. We therefore consider inference for sensitivity and specificity functions that are defined as functions of time. Semi-parametric regression models are proposed. Data from a cohort study are used to estimate model parameters. One issue that arises in practice is that event times may be censored. In this research, we extend the work by Leisenring, Pepe and Longton (1997) that dealt only with binary tests, parametric models to continuous tests, semi-parametric models and censored data. Asymptotic distribution theory for parameter estimates is produced and procedures for making statistical inference are evaluated with simulation studies. We illustrate our methods with a dataset from the Cardiovascular Health Study, relating the Framingham risk score measured at enrollment to subsequent risk of cardiovascular events

Fast and accurate modelling of longitudinal and repeated measures neuroimaging data

Despite the growing importance of longitudinal data in neuroimaging, the standard analysis methods make restrictive or unrealistic assumptions (e.g., assumption of Compound Symmetry—the state of all equal variances and equal correlations—or spatially homogeneous longitudinal correlations). While some new methods have been proposed to more accurately account for such data, these methods are based on iterative algorithms that are slow and failure-prone. In this article, we propose the use of the Sandwich Estimator (SwE) method which first estimates the parameters of interest with a simple Ordinary Least Square model and second estimates variances/covariances with the “so-called” SwE which accounts for the within-subject correlation existing in longitudinal data. Here, we introduce the SwE method in its classic form, and we review and propose several adjustments to improve its behaviour, specifically in small samples. We use intensive Monte Carlo simulations to compare all considered adjustments and isolate the best combination for neuroimaging data. We also compare the SwE method to other popular methods and demonstrate its strengths and weaknesses. Finally, we analyse a highly unbalanced longitudinal dataset from the Alzheimer's Disease Neuroimaging Initiative and demonstrate the flexibility of the SwE method to fit within- and between-subject effects in a single model. Software implementing this SwE method has been made freely available at http://warwick.ac.uk/tenichols/SwE

Chapter 12: Systematic Review of Prognostic Tests

A number of new biological markers are being studied as predictors of disease or adverse medical events among those who already have a disease. Systematic reviews of this growing literature can help determine whether the available evidence supports use of a new biomarker as a prognostic test that can more accurately place patients into different prognostic groups to improve treatment decisions and the accuracy of outcome predictions. Exemplary reviews of prognostic tests are not widely available, and the methods used to review diagnostic tests do not necessarily address the most important questions about prognostic tests that are used to predict the time-dependent likelihood of future patient outcomes. We provide suggestions for those interested in conducting systematic reviews of a prognostic test. The proposed use of the prognostic test should serve as the framework for a systematic review and to help define the key questions. The outcome probabilities or level of risk and other characteristics of prognostic groups are the most salient statistics for review and perhaps meta-analysis. Reclassification tables can help determine how a prognostic test affects the classification of patients into different prognostic groups, hence their treatment. Review of studies of the association between a potential prognostic test and patient outcomes would have little impact other than to determine whether further development as a prognostic test might be warranted

Three red suns in the sky: A transiting, terrestrial planet in a triple M-dwarf system at 6.9 pc

We present the discovery from Transiting Exoplanet Survey Satellite (TESS) data of LTT 1445Ab. At a distance of 6.9 pc, it is the second nearest transiting exoplanet system found to date, and the closest one known for which the primary is an M dwarf. The host stellar system consists of three mid-to-late M dwarfs in a hierarchical configuration, which are blended in one TESS pixel. We use MEarth data and results from the Science Processing Operations Center data validation report to determine that the planet transits the primary star in the system. The planet has a radius of ${1.38}_{-0.12}^{+0.13}$ ${R}_{\oplus }$, an orbital period of ${5.35882}_{-0.00031}^{+0.00030}$ days, and an equilibrium temperature of ${433}_{-27}^{+28}$ K. With radial velocities from the High Accuracy Radial Velocity Planet Searcher, we place a 3σ upper mass limit of 8.4 ${M}_{\oplus }$ on the planet. LTT 1445Ab provides one of the best opportunities to date for the spectroscopic study of the atmosphere of a terrestrial world. We also present a detailed characterization of the host stellar system. We use high-resolution spectroscopy and imaging to rule out the presence of any other close stellar or brown dwarf companions. Nineteen years of photometric monitoring of A and BC indicate a moderate amount of variability, in agreement with that observed in the TESS light-curve data. We derive a preliminary astrometric orbit for the BC pair that reveals an edge-on and eccentric configuration. The presence of a transiting planet in this system hints that the entire system may be co-planar, implying that the system may have formed from the early fragmentation of an individual protostellar core.Accepted manuscrip