Context.
Beyond the choice of wavefront control systems or coronographs, advanced data processing methods play a crucial role in disentangling potential planetary signals from bright quasi-static ...speckles. Among these methods, angular differential imaging (ADI) for data sets obtained in pupil tracking mode (ADI sequences) is one of the foremost research avenues, considering the many observing programs performed with ADI-based techniques and the associated discoveries.
Aims.
Inspired by the field of econometrics, here we propose a new detection algorithm for ADI sequences, deriving from the regime-switching model first proposed in the 1980s.
Methods.
The proposed model is very versatile as it allows the use of PSF-subtracted data sets (residual cubes) provided by various ADI-based techniques, separately or together, to provide a single detection map. The temporal structure of the residual cubes is used for the detection as the model is fed with a concatenated series of pixel-wise time sequences. The algorithm provides a detection probability map by considering two possible regimes for concentric annuli, the first one accounting for the residual noise and the second one for the planetary signal in addition to the residual noise.
Results.
The algorithm performance is tested on data sets from two instruments, VLT/NACO and VLT/SPHERE. The results show an overall better performance in the receiver operating characteristic space when compared with standard signal-to-noise-ratio maps for several state-of-the-art ADI-based post-processing algorithms.
Context.
Most of the high-contrast imaging (HCI) data-processing techniques used over the last 15 years have relied on the angular differential imaging (ADI) observing strategy, along with ...subtraction of a reference point spread function (PSF) to generate exoplanet detection maps. Recently, a new algorithm called regime switching model (RSM) map has been proposed to take advantage of these numerous PSF-subtraction techniques; RSM uses several of these techniques to generate a single probability map. Selection of the optimal parameters for these PSF-subtraction techniques as well as for the RSM map is not straightforward, is time consuming, and can be biased by assumptions made as to the underlying data set.
Aims.
We propose a novel optimisation procedure that can be applied to each of the PSF-subtraction techniques alone, or to the entire RSM framework.
Methods.
The optimisation procedure consists of three main steps: (i) definition of the optimal set of parameters for the PSF-subtraction techniques using the contrast as performance metric, (ii) optimisation of the RSM algorithm, and (iii) selection of the optimal set of PSF-subtraction techniques and ADI sequences used to generate the final RSM probability map.
Results.
The optimisation procedure is applied to the data sets of the exoplanet imaging data challenge, which provides tools to compare the performance of HCI data-processing techniques. The data sets consist of ADI sequences obtained with three state-of-the-art HCI instruments: SPHERE, NIRC2, and LMIRCam. The results of our analysis demonstrate the interest of the proposed optimisation procedure, with better performance metrics compared to the earlier version of RSM, as well as to other HCI data-processing techniques.
Context
.
In the past decade, high contrast imaging allowed the detection and characterisation of exoplanets, brown dwarfs, and circumstellar disks. Large surveys provided new insights about the ...frequency and properties of massive sub-stellar companions with separations from 5 to 300 au.
Aims
.
In this context, our study aims to detect and characterise potential exoplanets and brown dwarfs within debris disks, considering a diverse population of stars with respect to stellar age and spectral type. We present in this paper the analysis of a set of
H
-band images taken by the VLT/SPHERE instrument in the context of the SHARDDS survey. This survey gathers 55 main-sequence stars within 100 pc, known to host a high-infrared-excess debris disk, allowing us to potentially better understand the complex interactions between substellar companions and disks.
Methods
.
We rely on the Auto-RSM framework to perform an in-depth analysis of the considered targets, via the computation of detection maps and contrast curves. A clustering approach is used to divide the set of targets into multiple subsets, in order to reduce the computation time by estimating a single optimal parametrisation for each considered subset. Detection maps generated with different approaches are used along with contrast curves to identify potential planetary companions. Planet detection and planet occurrence frequencies are derived from the generated contrast curves, relying on two well-known evolutionary models, namely AMES-DUSTY and AMES-COND. Finally, we study the influence of the observing conditions and observing sequence characteristics on the performance measured in terms of contrast.
Results
.
The use of Auto-RSM allows us to reach high contrast at short separations, with a median contrast of 10
5
at 300 mas, for a completeness level of 95%. A new planetary characterisation algorithm, based on the RSM framework, is developed and tested successfully, showing a higher astrometric and photometric precision for faint sources compared to standard approaches. Apart from the already known companion of HD 206893 and two point-like sources around HD 114082 which are most likely background stars, we did not detect any new companion around other stars. A correlation study between achievable contrasts and parameters characterising high contrast imaging sequences highlights the importance of the Strehl ratio, wind speed at a height of 30 meters, and presence of wind-driven halo to define the quality of high contrast images. Finally, planet detection and occurrence rate maps are generated and show, for the SHARDDS survey, a high sensitivity between 10 and 100 au for substellar companions with masses >10
M
J
.
Context.
High-contrast imaging is one of the most challenging techniques for exoplanet detection. It relies on sophisticated data processing to reach high contrasts at small angular separations. Most ...data processing techniques of this type are based on the angular differential imaging observing strategy to perform the subtraction of a reference point spread function (PSF). In addition, such techniques generally make use of signal-to-noise (S/N) maps to infer the existence of planetary signals via thresholding.
Aims.
An alternative method for generating the final detection map was recently proposed with the regime-switching model (RSM) map, which uses a regime-switching framework to generate a probability map based on cubes of residuals generated by different PSF subtraction techniques. In this paper, we present several improvements to the original RSM map, focusing on novel PSF subtraction techniques and their optimal combinations, as well as a new procedure for estimating the probabilities involved.
Methods.
We started by implementing two forward-model versions of the RSM map algorithm based on the LOCI and KLIP PSF subtraction techniques. We then addressed the question of optimally selecting the PSF subtraction techniques to optimise the overall performance of the RSM map. A new forward-backward approach was also implemented to take into account both past and future observations to compute the RSM map probabilities, leading to improved precision in terms of astrometry and lowering the background speckle noise.
Results.
We tested the ability of these various improvements to increase the performance of the RSM map based on data sets obtained with three different instruments: VLT/NACO, VLT/SPHERE, and LBT/LMIRCam via a computation of receiver operating characteristic curves. These results demonstrate the benefits of these proposed improvements. Finally, we present a new framework to generate contrast curves based on probability maps. The contrast curves highlight the higher performance of the RSM map compared to a standard S/N map at small angular separations.
Context
. Supervised deep learning was recently introduced in high-contrast imaging (HCI) through the SODINN algorithm, a con-volutional neural network designed for exoplanet detection in angular ...differential imaging (ADI) datasets. The benchmarking of HCI algorithms within the Exoplanet Imaging Data Challenge (EIDC) showed that (i) SODINN can produce a high number of false positives in the final detection maps, and (ii) algorithms processing images in a more local manner perform better.
Aims
. This work aims to improve the SODINN detection performance by introducing new local processing approaches and adapting its learning process accordingly.
Methods
. We propose NA-SODINN, a new deep learning binary classifier based on a convolutional neural network (CNN) that better captures image noise correlations in ADI-processed frames by identifying noise regimes. The identification of these noise regimes is based on a novel technique, named PCA-pmaps, which allowed us to estimate the distance from the star in the image from which background noise started to dominate over residual speckle noise. NA-SODINN was also fed with local discriminators, such as signal-to-noise ratio (S/N) curves, which complement spatio-temporal feature maps during the model’s training.
Results
. Our new approach was tested against its predecessor, as well as two SODINN-based hybrid models and a more standard annular-PCA approach, through local receiving operating characteristics (ROC) analysis of ADI sequences from the VLT/SPHERE and Keck/NIRC-2 instruments. Results show that NA-SODINN enhances SODINN in both sensitivity and specificity, especially in the speckle-dominated noise regime. NA-SODINN is also benchmarked against the complete set of submitted detection algorithms in EIDC, in which we show that its final detection score matches or outperforms the most powerful detection algorithms.
Conclusions
. Throughout the supervised machine learning case, this study illustrates and reinforces the importance of adapting the task of detection to the local content of processed images.
Context. High-contrast imaging is one of the most challenging techniques for exoplanet detection. It relies on sophisticated data processing to reach high contrasts at small angular separations. Most ...data processing techniques of this type are based on the angular differential imaging observing strategy to perform the subtraction of a reference point spread function (PSF). In addition, such techniques generally make use of signal-to-noise (S/N) maps to infer the existence of planetary signals via thresholding. Aims. An alternative method for generating the final detection map was recently proposed with the regime-switching model (RSM) map, which uses a regime-switching framework to generate a probability map based on cubes of residuals generated by different PSF subtraction techniques. In this paper, we present several improvements to the original RSM map, focusing on novel PSF subtraction techniques and their optimal combinations, as well as a new procedure for estimating the probabilities involved. Methods. We started by implementing two forward-model versions of the RSM map algorithm based on the LOCI and KLIP PSF subtraction techniques. We then addressed the question of optimally selecting the PSF subtraction techniques to optimise the overall performance of the RSM map. A new forward-backward approach was also implemented to take into account both past and future observations to compute the RSM map probabilities, leading to improved precision in terms of astrometry and lowering the background speckle noise. Results. We tested the ability of these various improvements to increase the performance of the RSM map based on data sets obtained with three different instruments: VLT/NACO, VLT/SPHERE, and LBT/LMIRCam via a computation of receiver operating characteristic curves. These results demonstrate the benefits of these proposed improvements. Finally, we present a new framework to generate contrast curves based on probability maps. The contrast curves highlight the higher performance of the RSM map compared to a standard S/N map at small angular separations.
There is growing evidence of shared risk alleles for complex traits (pleiotropy), including autoimmune and neuropsychiatric diseases. This might be due to sharing among all individuals (whole-group ...pleiotropy) or a subset of individuals in a genetically heterogeneous cohort (subgroup heterogeneity). Here we describe the use of a well-powered statistic, BUHMBOX, to distinguish between those two situations using genotype data. We observed a shared genetic basis for 11 autoimmune diseases and type 1 diabetes (T1D; P < 1 × 10(-4)) and for 11 autoimmune diseases and rheumatoid arthritis (RA; P < 1 × 10(-3)). This sharing was not explained by subgroup heterogeneity (corrected PBUHMBOX > 0.2; 6,670 T1D cases and 7,279 RA cases). Genetic sharing between seronegative and seropostive RA (P < 1 × 10(-9)) had significant evidence of subgroup heterogeneity, suggesting a subgroup of seropositive-like cases within seronegative cases (PBUHMBOX = 0.008; 2,406 seronegative RA cases). We also observed a shared genetic basis for major depressive disorder (MDD) and schizophrenia (P < 1 × 10(-4)) that was not explained by subgroup heterogeneity (PBUHMBOX = 0.28; 9,238 MDD cases).
Biological sex impacts human immune responses, modulating susceptibility and severity to immune-related diseases. Females generally mount more robust immune responses than males, resulting in lower ...infection severity and greater autoimmunity incidence. Here, we addressed the contribution of testosterone to human immune function by analyzing a cohort of subjects undergoing gender-affirming testosterone treatment. We performed systems-level immunomonitoring through mass cytometry, scRNA and scATAC-Sequencing, and proteome profiling of blood samples at baseline and following 3 and 12 months of treatment. Testosterone treatment was associated with a low-grade inflammatory profile, evidenced by upregulation of proinflammatory plasma proteome (e.g., EN-RAGE, OSM, TNF), and induction of an inflammatory transcriptional program associated with NFkB signaling, and TNF signaling. Following testosterone treatment, higher NFkB activity was revealed in CD4 T, CD8 T, and NK cells in scATACseq analyses. Further, testosterone increased monocytic inflammatory responses upon bacterial stimulation in vitro. Although testosterone was associated with this inflammatory profile, it also exerted negative effects on antiviral immunity. Firstly, the percentage of plasmacytoid dendritic cells (pDC) decreased over transition, with pDC also displaying phenotypic changes associated with lower IFN responses. Secondly, bulk transcriptomics analyses show an overall reduction of IFNa responses. Thirdly, testosterone treatment led to reduced IFNa production upon PBMCs stimulation with a viral agonist. Our results show that testosterone has broad effects on the human immune system, and significantly modulates important players in antiviral immunity and inflammatory response. Identifying pathways involved in immune sexual dimorphism will help define novel targets for effective prevention and treatment of immune-mediated diseases.
Context:
Patients with hypopituitarism have an increased standardized mortality rate. The basis for this has not been fully clarified.
Objective:
To investigate in detail the cause of death in a ...large cohort of patients with hypopituitarism subjected to long-term follow-up.
Design and Methods:
All-cause and cause-specific mortality in 1286 Swedish patients with hypopituitarism prospectively monitored in KIMS (Pfizer International Metabolic Database) 1995–2009 were compared to general population data in the Swedish National Cause of Death Registry. In addition, events reported in KIMS, medical records, and postmortem reports were reviewed.
Main Outcome Measures:
Standardized mortality ratios (SMR) were calculated, with stratification for gender, attained age, and calendar year during follow-up.
Results:
An excess mortality was found, 120 deaths vs 84.3 expected, SMR 1.42 (95% confidence interval: 1.18–1.70). Infections, brain cancer, and sudden death were associated with significantly increased SMRs (6.32, 9.40, and 4.10, respectively). Fifteen patients, all ACTH-deficient, died from infections. Eight of these patients were considered to be in a state of adrenal crisis in connection with death (medical reports and post-mortem examinations). Another 8 patients died from de novo malignant brain tumors, 6 of which had had a benign pituitary lesion at baseline. Six of these 8 subjects had received prior radiation therapy.
Conclusion:
Two important causes of excess mortality were identified: first, adrenal crisis in response to acute stress and intercurrent illness; second, increased risk of a late appearance of de novo malignant brain tumors in patients who previously received radiotherapy. Both of these causes may be in part preventable by changes in the management of pituitary disease.
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