10 research outputs found
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback
Recent research has shown the advantages of using autoencoders based on deep
neural networks for collaborative filtering. In particular, the recently
proposed Mult-VAE model, which used the multinomial likelihood variational
autoencoders, has shown excellent results for top-N recommendations. In this
work, we propose the Recommender VAE (RecVAE) model that originates from our
research on regularization techniques for variational autoencoders. RecVAE
introduces several novel ideas to improve Mult-VAE, including a novel composite
prior distribution for the latent codes, a new approach to setting the
hyperparameter for the -VAE framework, and a new approach to training
based on alternating updates. In experimental evaluation, we show that RecVAE
significantly outperforms previously proposed autoencoder-based models,
including Mult-VAE and RaCT, across classical collaborative filtering datasets,
and present a detailed ablation study to assess our new developments. Code and
models are available at https://github.com/ilya-shenbin/RecVAE.Comment: In The Thirteenth ACM International Conference on Web Search and Data
Mining (WSDM '20), February 3-7, 2020, Houston, TX, USA. ACM, New York, NY,
USA, 9 page
Using PET with 18F-AV-45 (florbetapir) to quantify brain amyloid load in a clinical environment
International audiencePURPOSE: Positron emission tomography (PET) imaging of brain amyloid load has been suggested as a core biomarker for Alzheimer's disease (AD). The aim of this study was to test the feasibility of using PET imaging with (18)F-AV-45 (florbetapir) in a routine clinical environment to differentiate between patients with mild to moderate AD and mild cognitive impairment (MCI) from normal healthy controls (HC). METHODS: In this study, 46 subjects (20 men and 26 women, mean age of 69.0 ± 7.6 years), including 13 with AD, 12 with MCI and 21 HC subjects, were enrolled from three academic memory clinics. PET images were acquired over a 10-min period 50 min after injection of florbetapir (mean ± SD of radioactivity injected, 259 ± 57 MBq). PET images were assessed visually by two individuals blinded to any clinical information and quantitatively via the standard uptake value ratio (SUVr) in the specific regions of interest, which were defined in relation to the cerebellum as the reference region. RESULTS: The mean values of SUVr were higher in AD patients (median 1.20, Q1-Q3 1.16-1.30) than in HC subjects (median 1.05, Q1-Q3 1.04-1.08; p = 0.0001) in the overall cortex and all cortical regions (precuneus, anterior and posterior cingulate, and frontal median, temporal, parietal and occipital cortex). The MCI subjects also showed a higher uptake of florbetapir in the posterior cingulate cortex (median 1.06, Q1-Q3 0.97-1.28) compared with HC subjects (median 0.95, Q1-Q3 0.82-1.02; p = 0.03). Qualitative visual assessment of the PET scans showed a sensitivity of 84.6% (95% CI 0.55-0.98) and a specificity of 38.1% (95% CI 0.18-0.62) for discriminating AD patients from HC subjects; however, the quantitative assessment of the global cortex SUVr showed a sensitivity of 92.3% and specificity of 90.5% with a cut-off value of 1.122 (area under the curve 0.894). CONCLUSION: These preliminary results suggest that PET with florbetapir is a safe and suitable biomarker for AD that can be used routinely in a clinical environment. However, the low specificity of the visual PET scan assessment could be improved by the use of specific training and automatic or semiautomatic quantification tools
Spotting the enemy within: Targeted silencing of foreign DNA in mammalian genomes by the Krüppel-associated box zinc finger protein family
Discourse macrolinguistic impairment as a marker of linguistic and extralinguistic functions decline in early Alzheimer's disease
Extensive survey on the prevalence and genetic diversity of SIVs in primate bushmeat provides insights into risks for potential new cross-species transmissions
Demyelination in mild cognitive impairment suggests progression path to Alzheimer's disease.
The preclinical Alzheimer's disease (AD) - amnestic mild cognitive impairment (MCI) - is manifested by phenotypes classified into exclusively memory (single-domain) MCI (sMCI) and multiple-domain MCI (mMCI). We suggest that typical MCI-to-AD progression occurs through the sMCI-to-mMCI sequence as a result of the extension of initial pathological processes. To support this hypothesis, we assess myelin content with a Magnetization Transfer Ratio (MTR) in 21 sMCI and 21 mMCI patients and in 42 age-, sex-, and education-matched controls. A conjunction analysis revealed MTR reduction shared by sMCI and mMCI groups in the medial temporal lobe and posterior structures including white matter (WM: splenium, posterior corona radiata) and gray matter (GM: hippocampus; parahippocampal and lingual gyri). A disjunction analysis showed the spread of demyelination to prefrontal WM and insula GM in executive mMCI. Our findings suggest that demyelination starts in the structures affected by neurofibrillary pathology; its presence correlates with the clinical picture and indicates the method of MCI-to-AD progression. In vivo staging of preclinical AD can be developed in terms of WM/GM demyelination
The thermal structure of the Venus atmosphere: Intercomparison of Venus Express and ground based observations of vertical temperature and density profiles✰
The Venus International Reference Atmosphere (VIRA) model contains tabulated values of temperature and number densities obtained by the experiments on the Venera entry probes, Pioneer Venus Orbiter and multi-probe missions in the 1980s. The instruments on the recent Venus Express orbiter mission generated a significant amount of new observational data on the vertical and horizontal structure of the Venus atmosphere from 40 km to about 180 km altitude from April 2006 to November 2014. Many ground based experiments have provided data on the upper atmosphere (90-130 km) temperature structure since the publication of VIRA in 1985. The "Thermal Structure of the Venus Atmosphere" Team was supported by the International Space Studies Institute (ISSI), Bern, Switzerland, from 2013 to 2015 in order to combine and compare the ground-based observations and the VEx observations of the thermal structure as a first step towards generating an updated VIRA model. Results of this comparison are presented in five latitude bins and three local time bins by assuming hemispheric symmetry. The intercomparison of the ground-based and VEx results provides for the first time a consistent picture of the temperature and density structure in the 40 km-180 km altitude range. The Venus Express observations have considerably increased our knowledge of the Venus atmospheric thermal structure above ∼40 km and provided new information above 100 km. There are, however, still observational gaps in latitude and local time above certain regions. Considerable variability in the temperatures and densities is seen above 100 km but certain features appear to be systematically present, such as a succession of warm and cool layers. Preliminary modeling studies support the existence of such layers in agreement with a global scale circulation. The intercomparison focuses on average profiles but some VEx experiments provide sufficient global coverage to identify solar thermal tidal components. The differences between the VEx temperature profiles and the VIRA below 0.1 mbar/95 km are small. There is, however, a clear discrepancy at high latitudes in the 10-30 mbar (70-80 km) range. The VEx observations will also allow the improvement of the empirical models (VTS3 by Hedin et al., 1983 and VIRA by Keating et al., 1985) above 0.03 mbar/100 km, in particular the 100-150 km region where a sufficient observational coverage was previously missing. The next steps in order to define the updated VIRA temperature structure up to 150 km altitude are (1) define the grid on which this database may be provided, (2) fill what is possible with the results of the data intercomparison, and (3) fill the observational gaps. An interpolation between the datasets may be performed by using available General Circulation Models as guidelines. An improved spatial coverage of observations is still necessary at all altitudes, in latitude-longitude and at all local solar times for a complete description of the atmospheric thermal structure, in particular on the dayside above 100 km. New in-situ observations in the atmosphere below 40 km are missing, an altitude region that cannot be accessed by occultation experiments. All these questions need to be addressed by future missions