Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this ‘supervised’ approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes.

Astronomy & Astrophysics (A&A) is an international journal which publishes papers on all aspects of astronomy and astrophysics

Context. In hierarchical models of galaxy formation, stellar tidal streams are expected around most, if not all, galaxies. Although these features may provide useful diagnostics of the Λ CDM model, their observational properties remain poorly constrained because they are challenging to detect and interpret and have been studied in detail for only a sparse sampling of galaxy population. More quantitative, systematic approaches are required. We advocate statistical analysis of the counts and properties of such features in archival wide-field imaging surveys for a direct comparison against results from numerical simulations. Aims. We aim to study systematically the frequency of occurrence and other observational properties of tidal features around nearby galaxies. The sample we construct will act as a foundational dataset for statistical comparison with cosmological models of galaxy formation. Methods. Our approach is based on a visual classification of diffuse features around a volume-limited sample of nearby galaxies, using a post-processing of Sloan Digital Syk Survey (SDSS) imaging optimized for the detection of stellar structure with low surface brightness. Results. At a limiting surface brightness of 28 mag arcsec⁻², 14% of the galaxies in our sample exhibit evidence of diffuse features likely to have arisen from minor merging events. Our technique recovers all previously known streams in our sample and yields a number of new candidates. Consistent with previous studies, coherent arc-like features and shells are the most common type of tidal structures found in this study. We conclude that although some detections are ambiguous and could be corroborated or refuted with deeper imaging, our technique provides a reliable foundation for the statistical analysis of diffuse circumgalactic features in wide-area imaging surveys, and for the identification of targets for follow-up studies.

The Cepheid period–luminosity (PL) relation is the key tool for measuring astronomical distances and for establishing the extragalactic distance scale. In particular, the local value of the Hubble constant (H ₀) strongly depends on Cepheid distance measurements. The recent Gaia Data Releases and other parallax measurements from the Hubble Space Telescope (HST) already enabled us to improve the accuracy of the slope (α) and intercept (β) of the PL relation. However, the dependence of this law on metallicity is still largely debated. In this paper, we combine three samples of Cepheids in the Milky Way (MW), the Large Magellanic Cloud (LMC), and the Small Magellanic Cloud (SMC) in order to derive the metallicity term (hereafter γ) of the PL relation. The recent publication of extremely precise LMC and SMC distances based on late-type detached eclipsing binary systems provides a solid anchor for the Magellanic Clouds. In the MW, we adopt Cepheid parallaxes from the early third Gaia Data Release. We derive the metallicity effect in V, I, J, H, K _S , W _VI , and W _JK . In the K _S band we report a metallicity effect of −0.221 ± 0.051 mag dex⁻¹, the negative sign meaning that more metal-rich Cepheids are intrinsically brighter than their more metal-poor counterparts of the same pulsation period.

Any viable cosmological framework has to match the observed proportion of early- and late-type galaxies. In this contribution, we focus on the distribution of galaxy morphological types in the standard model of cosmology (Lambda cold dark matter, ΛCDM). Using the latest state-of-the-art cosmological ΛCDM simulations known as Illustris, IllustrisTNG, and EAGLE, we calculate the intrinsic and sky-projected aspect ratio distribution of the stars in subhalos with stellar mass M _* > 10¹⁰ M _⊙ at redshift z = 0. There is a significant deficit of intrinsically thin disk galaxies, which however comprise most of the locally observed galaxy population. Consequently, the sky-projected aspect ratio distribution produced by these ΛCDM simulations disagrees with the Galaxy And Mass Assembly (GAMA) survey and Sloan Digital Sky Survey at ≥12.52σ (TNG50-1) and ≥14.82σ (EAGLE50) confidence. The deficit of intrinsically thin galaxies could be due to a much less hierarchical merger-driven build-up of observed galaxies than is given by the ΛCDM framework. It might also arise from the implemented sub-grid models, or from the limited resolution of the above-mentioned hydrodynamical simulations. We estimate that an 8⁵ times better mass resolution realization than TNG50-1 would reduce the tension with GAMA to the 5.58σ level. Finally, we show that galaxies with fewer major mergers have a somewhat thinner aspect ratio distribution. Given also the high expected frequency of minor mergers in ΛCDM, the problem may be due to minor mergers. In this case, the angular momentum problem could be alleviated in Milgromian dynamics because of a reduced merger frequency arising from the absence of dynamical friction between extended dark matter halos.