Apport du test de mémoire sémantique 42 items (TMS-42) en consultation mémoire

International audienc

Assessment of semantic memory with the SMT-42

International audienc

Euclid preparation : XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models

We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid. The proposed method combines a control on galaxy shape parameters offered by analytic models with realistic surface brightness distributions learned from real Hubble Space Telescope observations by deep generative models. We simulate a galaxy field of 0.4x2006;deg(2) as it will be seen by the Euclid visible imager VIS, and we show that galaxy structural parameters are recovered to an accuracy similar to that for pure analytic Sersic profiles. Based on these simulations, we estimate that the Euclid Wide Survey (EWS) will be able to resolve the internal morphological structure of galaxies down to a surface brightness of 22.5x2006;magx2006;arcsec(-2), and the Euclid Deep Survey (EDS) down to 24.9x2006;magx2006;arcsec(-2). This corresponds to approximately 250 million galaxies at the end of the mission and a 50% complete sample for stellar masses above 10(10.6)M(circle dot) (resp. 10(9.6)M(circle dot)) at a redshift zx2004;similar to 0.5 for the EWS (resp. EDS). The approach presented in this work can contribute to improving the preparation of future high-precision cosmological imaging surveys by allowing simulations to incorporate more realistic galaxies.Peer reviewe

A phenotype of atypical apraxia of speech in a family carrying SQSTM1 mutation.

SQSTM1 mutations, coding for the p62 protein, were identified as a monogenic cause of Paget disease of bone and of amyotrophic lateral sclerosis. More recently, SQSTM1 mutations were identified in few families with frontotemporal dementia. We report a new family carrying SQSTM1 mutation and presenting with a clinical phenotype of speech apraxia or atypical behavioral disorders, associated with early visuo-contructional deficits. This study further supports the implication of SQSTM1 in frontotemporal dementia, and enlarges the phenotypic spectrum associated with SQSTM1 mutations

Démences : où sont les corps de Lewy ?

La démence à corps de Lewy (DCL) est la deuxième cause de démence dégénérative du sujet âgé, dans les grandes séries autopsiques. Dans la réalité quotidienne des centres mémoire pourtant, la DCL représente une faible proportion des diagnostics cliniques, avec une forte disparité entre les centres. Plusieurs raisons peuvent rendre compte de la faible sensibilité du diagnostic de DCL : l’imprécision et la subjectivité des critères diagnostiques existants ; la place insuffisante donnée à certains signes non-moteurs (troubles du comportement en sommeil paradoxal, dysautonomie) ; enfin et surtout l’association quasi constante de la pathologie de Lewy à une pathologie de type Alzheimer, qui domine rapidement le phénotype clinique. À l’heure de l’essor des thérapies ciblées contre les agrégats protéiques, de nouvelles échelles cliniques permettant d’appréhender la coexistence de la pathologie de Lewy dans la maladie d’Alzheimer sont plus que jamais nécessaires

Euclid preparation. XXVI. The Euclid Morphology Challenge: Towards structural parameters for billions of galaxies

The various Euclid imaging surveys will become a reference for studies of galaxy morphology by delivering imaging over an unprecedented area of 15 000 square degrees with high spatial resolution. In order to understand the capabilities of measuring morphologies from Euclid-detected galaxies and to help implement measurements in the pipeline of the Organisational Unit MER of the Euclid Science Ground Segment, we have conducted the Euclid Morphology Challenge, which we present in two papers. While the companion paper focusses on the analysis of photometry, this paper assesses the accuracy of the parametric galaxy morphology measurements in imaging predicted from within the Euclid Wide Survey. We evaluate the performance of five state-of-the-art surface-brightness-fitting codes, , , , and , on a sample of about 1.5 million simulated galaxies (350 000 above 5σ) resembling reduced observations with the Euclid VIS and NIR instruments. The simulations include analytic Sérsic profiles with one and two components, as well as more realistic galaxies generated with neural networks. We find that, despite some code-specific differences, all methods tend to achieve reliable structural measurements (< 10% scatter on ideal Sérsic simulations) down to an apparent magnitude of about I$_{E}$ = 23 in one component and I$_{E}$ = 21 in two components, which correspond to a signal-to-noise ratio of approximately 1 and 5, respectively. We also show that when tested on non-analytic profiles, the results are typically degraded by a factor of 3, driven by systematics. We conclude that the official Euclid Data Releases will deliver robust structural parameters for at least 400 million galaxies in the Euclid Wide Survey by the end of the mission. We find that a key factor for explaining the different behaviour of the codes at the faint end is the set of adopted priors for the various structural parameters

Euclid preparation: XIII. Forecasts for galaxy morphology with the Euclid Survey using deep generative models

We present a machine learning framework to simulate realistic galaxies for the Euclid Survey, producing more complex and realistic galaxies than the analytical simulations currently used in Euclid. The proposed method combines a control on galaxy shape parameters offered by analytic models with realistic surface brightness distributions learned from real Hubble Space Telescope observations by deep generative models. We simulate a galaxy field of 0.4 deg2 as it will be seen by the Euclid visible imager VIS, and we show that galaxy structural parameters are recovered to an accuracy similar to that for pure analytic Sérsic profiles. Based on these simulations, we estimate that the Euclid Wide Survey (EWS) will be able to resolve the internal morphological structure of galaxies down to a surface brightness of 22.5 mag arcsec-2, and the Euclid Deep Survey (EDS) down to 24.9 mag arcsec-2. This corresponds to approximately 250 million galaxies at the end of the mission and a 50% complete sample for stellar masses above 1010.6 M (resp. 109.6 M) at a redshift z ∼ 0.5 for the EWS (resp. EDS). The approach presented in this work can contribute to improving the preparation of future high-precision cosmological imaging surveys by allowing simulations to incorporate more realistic galaxies

Dementia Caregiver Burden: A Research Update and Critical Analysis

Purpose of Review: This article provides an updated review of the determinants of caregiver burden and depression, with a focus on care demands and especially the differential effects of various neuropsychiatric symptoms or symptom clusters. Moreover, studies on caregivers for frontotemporal and Lewy body dementias were referred to in order to identify differences and similarities with the mainstream literature based largely on Alzheimer caregivers. Recent Findings: As a group, neuropsychiatric symptoms are most predictive of caregiver burden and depression regardless of dementia diagnosis, but the effects appear to be driven primarily by disruptive behaviors (e.g., agitation, aggression, disinhibition), followed by delusions and mood disturbance. Disruptive behaviors are more disturbing partly because of the adverse impact on the emotional connection between the caregiver and the care-recipient and partly because they exacerbate difficulties in other domains (e.g., caring for activities of daily living). In behavioral variant frontotemporal dementia, not only are these disruptive behaviors more prominent but they are also more disturbing due to the care-recipient’s insensitivity to others’ feelings. In Lewy body dementia, visual hallucinations also appear to be distressing. Summary: The disturbing nature of disruptive behaviors cuts across dementia conditions, but the roles played by symptoms that are unique or particularly serious in a certain condition need to be explored further

Neurobiol Aging

GRN mutations are frequent causes of familial frontotemporal degeneration. Although there is no clear consensual threshold, plasma progranulin levels represent an efficient biomarker for predicting GRN mutations when decreased. We evaluated plasma levels to determine whether it could also predict age at onset, clinical phenotype, or disease progression in 160 GRN carriers. Importantly, progranulin levels were influenced by gender, with lower levels in male than in female patients in our study. Although we found no correlation with age at onset or with clinical phenotype, we confirmed that decreased level predicts GRN mutations, even in presymptomatic carriers more than four decades before disease onset. We also provided first evidence for the stability of levels throughout longitudinal trajectory in carriers, over a 4-year time span. Finally, we confirmed that progranulin levels constitute a reliable, cost-effective marker, suitable as a screening tool in patients with familial frontotemporal degeneration, and more broadly in patients without family history or with atypical presentations who are less likely to be referred for molecular diagnosis

Euclid preparation. XXV. The Euclid Morphology Challenge -- Towards model-fitting photometry for billions of galaxies

The ESA Euclid mission will provide high-quality imaging for about 1.5 billion galaxies. A software pipeline to automatically process and analyse such a huge amount of data in real time is being developed by the Science Ground Segment of the Euclid Consortium; this pipeline will include a model-fitting algorithm, which will provide photometric and morphological estimates of paramount importance for the core science goals of the mission and for legacy science. The Euclid Morphology Challenge is a comparative investigation of the performance of five model-fitting software packages on simulated Euclid data, aimed at providing the baseline to identify the best suited algorithm to be implemented in the pipeline. In this paper we describe the simulated data set, and we discuss the photometry results. A companion paper (Euclid Collaboration: Bretonni\`ere et al. 2022) is focused on the structural and morphological estimates. We created mock Euclid images simulating five fields of view of 0.48 deg2 each in the $I_E$ band of the VIS instrument, each with three realisations of galaxy profiles (single and double S\'ersic, and 'realistic' profiles obtained with a neural network); for one of the fields in the double S\'ersic realisation, we also simulated images for the three near-infrared $Y_E$, $J_E$ and $H_E$ bands of the NISP-P instrument, and five Rubin/LSST optical complementary bands ($u$, $g$, $r$, $i$, and $z$). To analyse the results we created diagnostic plots and defined ad-hoc metrics. Five model-fitting software packages (DeepLeGATo, Galapagos-2, Morfometryka, ProFit, and SourceXtractor++) were compared, all typically providing good results. (cut)Comment: 29 pages, 33 figures. Euclid pre-launch key paper. Companion paper: Bretonniere et al. 202