Five carbon- and nitrogen-bearing species in a hot giant planet's atmosphere

The atmospheres of gaseous giant exoplanets orbiting close to their parent stars (hot Jupiters) have been probed for nearly two decades. They allow us to investigate the chemical and physical properties of planetary atmospheres under extreme irradiation conditions. Previous observations of hot Jupiters as they transit in front of their host stars have revealed the frequent presence of water vapour and carbon monoxide in their atmospheres; this has been studied in terms of scaled solar composition under the usual assumption of chemical equilibrium. Both molecules as well as hydrogen cyanide were found in the atmosphere of HD 209458b, a well studied hot Jupiter (with equilibrium temperature around 1,500 kelvin), whereas ammonia was tentatively detected there and subsequently refuted. Here we report observations of HD 209458b that indicate the presence of water (H2O), carbon monoxide (CO), hydrogen cyanide (HCN), methane (CH4), ammonia (NH3) and acetylene (C2H2), with statistical significance of 5.3 to 9.9 standard deviations per molecule. Atmospheric models in radiative and chemical equilibrium that account for the detected species indicate a carbon-rich chemistry with a carbon-to-oxygen ratio close to or greater than 1, higher than the solar value (0.55). According to existing models relating the atmospheric chemistry to planet formation and migration scenarios, this would suggest that HD 209458b formed far from its present location and subsequently migrated inwards. Other hot Jupiters may also show a richer chemistry than has been previously found, which would bring into question the frequently made assumption that they have solar-like and oxygen-rich compositions.Comment: As part of the Springer Nature Content Sharing Initiative, it is possible to access a view-only version of this paper by using the following SharedIt link: https://rdcu.be/cifr

A chemical survey of exoplanets with ARIEL

Thousands of exoplanets have now been discovered with a huge range of masses, sizes and orbits: from rocky Earth-like planets to large gas giants grazing the surface of their host star. However, the essential nature of these exoplanets remains largely mysterious: there is no known, discernible pattern linking the presence, size, or orbital parameters of a planet to the nature of its parent star. We have little idea whether the chemistry of a planet is linked to its formation environment, or whether the type of host star drives the physics and chemistry of the planet’s birth, and evolution. ARIEL was conceived to observe a large number (~1000) of transiting planets for statistical understanding, including gas giants, Neptunes, super-Earths and Earth-size planets around a range of host star types using transit spectroscopy in the 1.25–7.8 μm spectral range and multiple narrow-band photometry in the optical. ARIEL will focus on warm and hot planets to take advantage of their well-mixed atmospheres which should show minimal condensation and sequestration of high-Z materials compared to their colder Solar System siblings. Said warm and hot atmospheres are expected to be more representative of the planetary bulk composition. Observations of these warm/hot exoplanets, and in particular of their elemental composition (especially C, O, N, S, Si), will allow the understanding of the early stages of planetary and atmospheric formation during the nebular phase and the following few million years. ARIEL will thus provide a representative picture of the chemical nature of the exoplanets and relate this directly to the type and chemical environment of the host star. ARIEL is designed as a dedicated survey mission for combined-light spectroscopy, capable of observing a large and well-defined planet sample within its 4-year mission lifetime. Transit, eclipse and phase-curve spectroscopy methods, whereby the signal from the star and planet are differentiated using knowledge of the planetary ephemerides, allow us to measure atmospheric signals from the planet at levels of 10–100 part per million (ppm) relative to the star and, given the bright nature of targets, also allows more sophisticated techniques, such as eclipse mapping, to give a deeper insight into the nature of the atmosphere. These types of observations require a stable payload and satellite platform with broad, instantaneous wavelength coverage to detect many molecular species, probe the thermal structure, identify clouds and monitor the stellar activity. The wavelength range proposed covers all the expected major atmospheric gases from e.g. H2O, CO2, CH4 NH3, HCN, H2S through to the more exotic metallic compounds, such as TiO, VO, and condensed species. Simulations of ARIEL performance in conducting exoplanet surveys have been performed – using conservative estimates of mission performance and a full model of all significant noise sources in the measurement – using a list of potential ARIEL targets that incorporates the latest available exoplanet statistics. The conclusion at the end of the Phase A study, is that ARIEL – in line with the stated mission objectives – will be able to observe about 1000 exoplanets depending on the details of the adopted survey strategy, thus confirming the feasibility of the main science objectives.Peer reviewedFinal Published versio

Impact of different exposure models and spatial resolution on the long-term effects of air pollution.

Abstract Long-term exposure to air pollution has been related to mortality in several epidemiological studies. The investigations have assessed exposure using various methods achieving different accuracy in predicting air pollutants concentrations. The comparison of the health effects estimates are therefore challenging. This paper aims to compare the effect estimates of the long-term effects of air pollutants (particulate matter with aerodynamic diameter less than 10 μm, PM10, and nitrogen dioxide, NO2) on cause-specific mortality in the Rome Longitudinal Study, using exposure estimates obtained with different models and spatial resolutions. Annual averages of NO2 and PM10 were estimated for the year 2015 in a large portion of the Rome urban area (12 × 12 km2) applying three modelling techniques available at increasing spatial resolution: 1) a chemical transport model (CTM) at 1km resolution; 2) a land-use random forest (LURF) approach at 200m resolution; 3) a micro-scale Lagrangian particle dispersion model (PMSS) taking into account the effect of buildings structure at 4 m resolution with results post processed at different buffer sizes (12, 24, 52, 100 and 200 m). All the exposures were assigned at the residential addresses of 482,259 citizens of Rome 30+ years of age who were enrolled on 2001 and followed-up till 2015. The association between annual exposures and natural-cause, cardiovascular (CVD) and respiratory (RESP) mortality were estimated using Cox proportional hazards models adjusted for individual and area-level confounders. We found different distributions of both NO2 and PM10 concentrations, across models and spatial resolutions. Natural cause and CVD mortality outcomes were all positively associated with NO2 and PM10 regardless of the model and spatial resolution when using a relative scale of the exposure such as the interquartile range (IQR): adjusted Hazard Ratios (HR), and 95% confidence intervals (CI), of natural cause mortality, per IQR increments in the two pollutants, ranged between 1.012 (1.004, 1.021) and 1.018 (1.007, 1.028) for the different NO2 estimates, and between 1.010 (1.000, 1.020) and 1.020 (1.008, 1.031) for PM10, with a tendency of larger effect for lower resolution exposures. The latter was even stronger when a fixed value of 10 μg/m3 is used to calculate HRs. Long-term effects of air pollution on mortality in Rome were consistent across different models for exposure assessment, and different spatial resolutions

The HADES RV programme with HARPS-N at TNG. XI. GJ 685 b: a warm super-Earth around an active M dwarf

Context. Small rocky planets seem to be very abundant around low-mass M-type stars. Their actual planetary population is however not yet precisely understood. Currently, several surveys aim to expand the statistics with intensive detection campaigns, both photometric and spectroscopic. Aims: The HADES program aims to improve the current statistics through the in-depth analysis of accurate radial-velocity (RV) monitoring in a narrow range of spectral sub-types, with the precision needed to detect small planets with a few Earth masses. Methods: We analyse 106 spectroscopic HARPS-N observations of the active M0-type star GJ 685 taken over the past five years. We combine these data with photometric measurements from different observatories to accurately model the stellar rotation and disentangle its signals from genuine Doppler planetary signals in the RV data. We run an MCMC analysis on the RV and activity index time series to model the planetary and stellar signals present in the data, applying Gaussian Process regression technique to deal with the stellar activity signals. Results: We identify three periodic signals in the RV time series, with periods of 9, 24, and 18 d. Combining the analyses of the photometry of the star with the activity indexes derived from the HARPS-N spectra, we identify the 18 d and 9 d signals as activity-related, corresponding to the stellar rotation period and its first harmonic, respectively. The 24 d signal shows no relation to any activity proxy, and therefore we identify it as a genuine planetary signal. We find the best-fit model describing the Doppler signal of the newly found planet, GJ 685 b, corresponding to an orbital period Pb = 24.160-0.047+0.061 d and a minimum mass MP sin i = 9.0-1.8+1.7 M⊕. We also study a sample of 70 RV-detected M-dwarf planets, and present new statistical evidence of a difference in mass distribution between the populations of single- and multi-planet systems, which can shed new light on the formation mechanisms of low-mass planets around late-type stars. Based on observations made with the Italian Telescopio Nazionale Galileo (TNG), operated on the island of La Palma by the INAF - Fundación Galileo Galilei at the Roche de Los Muchachos Observatory of the Instituto de Astrofísica de Canarias (IAC); photometric observations made with the APACHE array located at the Astronomical Observatory of the Aosta Valley; photometric observations made with the robotic telescope APT2 (within the EXORAP programme) located at Serra La Nave on Mt. Etna

Assessment of Brain Age in Posttraumatic Stress Disorder: Findings from the ENIGMA PTSD and Brain Age Working Groups

Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Lipoprotein(a) Genotype Influences the Clinical Diagnosis of Familial Hypercholesterolemia

: Background Evidence suggests that LPA risk genotypes are a possible contributor to the clinical diagnosis of familial hypercholesterolemia (FH). This study aimed at determining the prevalence of LPA risk variants in adult individuals with FH enrolled in the Italian LIPIGEN (Lipid Transport Disorders Italian Genetic Network) study, with (FH/M+) or without (FH/M-) a causative genetic variant. Methods and Results An lp(a) [lipoprotein(a)] genetic score was calculated by summing the number risk-increasing alleles inherited at rs3798220 and rs10455872 variants. Overall, in the 4.6% of 1695 patients with clinically diagnosed FH, the phenotype was not explained by a monogenic or polygenic cause but by genotype associated with high lp(a) levels. Among 765 subjects with FH/M- and 930 subjects with FH/M+, 133 (17.4%) and 95 (10.2%) were characterized by 1 copy of either rs10455872 or rs3798220 or 2 copies of either rs10455872 or rs3798220 (lp(a) score ≥1). Subjects with FH/M- also had lower mean levels of pretreatment low-density lipoprotein cholesterol than individuals with FH/M+ (t test for difference in means between FH/M- and FH/M+ groups <0.0001); however, subjects with FH/M- and lp(a) score ≥1 had higher mean (SD) pretreatment low-density lipoprotein cholesterol levels (223.47 [50.40] mg/dL) compared with subjects with FH/M- and lp(a) score=0 (219.38 [54.54] mg/dL for), although not statistically significant. The adjustment of low-density lipoprotein cholesterol levels based on lp(a) concentration reduced from 68% to 42% the proportion of subjects with low-density lipoprotein cholesterol level ≥190 mg/dL (or from 68% to 50%, considering a more conservative formula). Conclusions Our study supports the importance of measuring lp(a) to perform the diagnosis of FH appropriately and to exclude that the observed phenotype is driven by elevated levels of lp(a) before performing the genetic test for FH

VizieR Online Data Catalog: Code to compute spectral line profile indicators (Lanza+, 2018)

A computer code (procedure) written in Interactive Data Language (IDL) to compute the spectral line profile indicators used in the above research article starting from the fits files provided by the data reduction software (DRS) of HARPS or HARPS-N. The procedure takes the cross-correlation function (CCF) files provided by the DRS as an input. An example for the input files and the corresponding output file is provided with the sole purpose of allowing to test the proper compilation and running of the procedure. Details on an auxiliary source file (mpfit.pro) required for compilation are provided in the header of the procedure file and in Appendix A of the above mentioned article. Interested users are warmly recommended to read them before compiling and running the procedure. (Notes: 4 data files)

The GAPS Programme with HARPS-N at TNG. XII. Characterization of the planetary system around HD 108874

In order to understand the observed physical and orbital diversity of extrasolar planetary systems, a full investigation of these objects and of their host stars is necessary. Within this field, one of the main purposes of the GAPS observing project with HARPS-N at TNG is to provide a more detailed characterization of already known systems. In this framework we monitored the star, hosting two giant planets, HD 108874, with HARPS-N for three years in order to refine the orbits, to improve the dynamical study and to search for additional low-mass planets in close orbits. We subtracted the radial velocity (RV) signal due to the known outer planets, finding a clear modulation of 40.2 d period. We analysed the correlation between RV residuals and the activity indicators and modelled the magnetic activity with a dedicated code. Our analysis suggests that the 40.2 d periodicity is a signature of the rotation period of the star. A refined orbital solution is provided, revealing that the system is close to a mean motion resonance of about 9:2, in a stable configuration over 1 Gyr. Stable orbits for low-mass planets are limited to regions very close to the star or far from it. Our data exclude super-Earths with Msini ≳ 5M⊕ within 0.4 AU and objects with Msini ≳ 2M⊕ with orbital periods of a few days. Finally we put constraints on the habitable zone of the system, assuming the presence of an exomoon orbiting the inner giant planet. Based on observations made with the Italian Telescopio Nazionale Galileo (TNG) operated on the island of La Palma by the Fundación Galileo Galilei of the INAF at the Spanish Observatorio del Roque de los Muchachos of the IAC in the frame of the programme Global Architecture of Planetary Systems (GAPS).Table A.1 is also available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/599/A90</A

Enabling planetary science across light-years. Ariel Definition Study Report

Ariel, the Atmospheric Remote-sensing Infrared Exoplanet Large-survey, was adopted as the fourth medium-class mission in ESA's Cosmic Vision programme to be launched in 2029. During its 4-year mission, Ariel will study what exoplanets are made of, how they formed and how they evolve, by surveying a diverse sample of about 1000 extrasolar planets, simultaneously in visible and infrared wavelengths. It is the first mission dedicated to measuring the chemical composition and thermal structures of hundreds of transiting exoplanets, enabling planetary science far beyond the boundaries of the Solar System. The payload consists of an off-axis Cassegrain telescope (primary mirror 1100 mm x 730 mm ellipse) and two separate instruments (FGS and AIRS) covering simultaneously 0.5-7.8 micron spectral range. The satellite is best placed into an L2 orbit to maximise the thermal stability and the field of regard. The payload module is passively cooled via a series of V-Groove radiators; the detectors for the AIRS are the only items that require active cooling via an active Ne JT cooler. The Ariel payload is developed by a consortium of more than 50 institutes from 16 ESA countries, which include the UK, France, Italy, Belgium, Poland, Spain, Austria, Denmark, Ireland, Portugal, Czech Republic, Hungary, the Netherlands, Sweden, Norway, Estonia, and a NASA contribution