Multi-Channel Stochastic Variational Inference for the Joint Analysis of Heterogeneous Biomedical Data in Alzheimer's Disease

The joint analysis of biomedical data in Alzheimer's Disease (AD) is important for better clinical diagnosis and to understand the relationship between biomarkers. However, jointly accounting for heterogeneous measures poses important challenges related to the modeling of the variability and the interpretability of the results. These issues are here addressed by proposing a novel multi-channel stochastic generative model. We assume that a latent variable generates the data observed through different channels (e.g., clinical scores, imaging, ...) and describe an efficient way to estimate jointly the distribution of both latent variable and data generative process. Experiments on synthetic data show that the multi-channel formulation allows superior data reconstruction as opposed to the single channel one. Moreover, the derived lower bound of the model evidence represents a promising model selection criterion. Experiments on AD data show that the model parameters can be used for unsupervised patient stratification and for the joint interpretation of the heterogeneous observations. Because of its general and flexible formulation, we believe that the proposed method can find important applications as a general data fusion technique.Comment: accepted for presentation at MLCN 2018 workshop, in Conjunction with MICCAI 2018, September 20, Granada, Spai

Comparison of nonsense-mediated mRNA decay efficiency in various murine tissues

<p>Abstract</p> <p>Background</p> <p>The Nonsense-Mediated mRNA Decay (NMD) pathway detects and degrades mRNAs containing premature termination codons, thereby preventing the accumulation of potentially detrimental truncated proteins. Intertissue variation in the efficiency of this mechanism has been suggested, which could have important implications for the understanding of genotype-phenotype correlations in various genetic disorders. However, compelling evidence in favour of this hypothesis is lacking. Here, we have explored this question by measuring the ratio of mutant versus wild-type <it>Men1 </it>transcripts in thirteen tissues from mice carrying a heterozygous truncating mutation in the ubiquitously expressed <it>Men1 </it>gene.</p> <p>Results</p> <p>Significant differences were found between two groups of tissues. The first group, which includes testis, ovary, brain and heart, displays a strong decrease of the nonsense transcript (average ratio of 18% of mutant versus wild-type <it>Men1 </it>transcripts, identical to the value measured in murine embryonic fibroblasts). The second group, comprising lung, intestine and thymus, shows much less pronounced NMD (average ratio of 35%). Importantly, the extent of degradation by NMD does not correlate with the expression level of eleven genes encoding proteins involved in NMD or with the expression level of the <it>Men1 </it>gene.</p> <p>Conclusion</p> <p>Mouse models are an attractive option to evaluate the efficiency of NMD in multiple mammalian tissues and organs, given that it is much easier to obtain these from a mouse than from a single individual carrying a germline truncating mutation. In this study, we have uncovered in the thirteen different murine tissues that we examined up to a two-fold difference in NMD efficiency.</p

Inunditos como análogos de reservatórios: um exemplo nos depósitos gonduânicos triássicos do Gráben Arroio Moirão, RS

O estudo de reservatórios de óleo e gás de sistemas continentais tem enfatizado, na última década, arenitos associados a inunditos, provenientes de fluxos hiperpicnais. Contudo, há poucos estudos para entender sua arquitetura e heterogeneidade, resultando em dificuldades de reconhecimento e de exploração. O presente trabalho visa à análise de pacotes triássicos da Bacia do Paraná pertencentes à Formação Santa Maria, que ocorrem como fragmentos isolados sobre o Escudo Sul-Rio-Grandense na região do Gráben Arroio Moirão (RS). Para tanto, fez-se uso de mapeamento sistemático, análise de heterogeneidade de fácies e estratigrafia de sequências, que incluem levantamento de perfis colunares, identificação de associações e sucessões de fácies e superfícies-chave. Além disso, classificaram-se os arenitos e qualificou-se a porosidade com base na análise petrográfica. Foi possível delimitar os principais depósitos de arenitos, no quais predomina geometria tabular, grãos mal selecionados e matriz argilosa. Distinguiram-se cinco ciclos deposicionais granodecrescentes ascendentes, limitados na base e no topo por superfícies erosivas, que marcam heterogeneidades recorrentes. As fácies-reservatório foram classificadas como subarcósios, de matriz argilosa oxidada, com agregados de caulinita, e porosidade intergranular do tipo shrinkage. A integração dos dados resultou na elaboração de um modelo de variação lateral e vertical de fácies de depósitos de inunditos. Nele, identificaram-se fácies constituídas por arenitos grossos a conglomeráticos, com estratificações cruzada tangencial e plano-paralela, como potenciais modelos análogos de reservatórios. Esses resultados possibilitam prospectar outros depósitos arenosos dessa unidade estratigráfica da Bacia do Paraná, para fins de dimensionar regionalmente o análogo de reservatório.The study of oil and gas reservoirs in continental systems has emphasized, in the last decade, sandstones associated with inundites, coming from hyperpicnal flows. However, there are few studies to understand its architecture and heterogeneity, resulting in difficulties for exploration and exploitation. The current work aims at the analysis of Triassic strata from the Paraná Basin belonging to the Santa Maria Formation, which occur as isolated fragments on the Sul-rio-grandense Shield in Arroio Moirão Graben (RS). For this, systematic mapping, facies heterogeneity analysis and sequence stratigraphy were used, including columnar profiles, identification of associations and sequences of facies and key surfaces. In addition, the sandstones were classified and the porosity was qualified based on the petrographic analysis. It was possible to define the main deposits of sandstones, in which predominate tabular geometry, poorly selected grains and clayey matrix. Five ascending granodecrescent depositional cycles were distinguished, limited at the base and at the top by erosive surfaces, which marked recurrent heterogeneities. The reservoir facies were classified as subarcósios, of oxidized clay matrix, with aggregates of kaolinite, and intergranular porosity of the shrinkage type. The integration of the data resulted in the elaboration of a model of lateral and vertical variation inundites deposits facies. In it, facies composed of conglomeratic thick sandstones were identified, with tangential cross stratification and planar stratification, as potential analog models of reservoirs. These results allow the prospection of other sandy deposits from this stratigraphic unit of the Paraná Basin, in order to size the reservoir analogue regionally

Review of high-contrast imaging systems for current and future ground- and space-based telescopes I. Coronagraph design methods and optical performance metrics

The Optimal Optical Coronagraph (OOC) Workshop at the Lorentz Center in September 2017 in Leiden, the Netherlands gathered a diverse group of 25 researchers working on exoplanet instrumentation to stimulate the emergence and sharing of new ideas. In this first installment of a series of three papers summarizing the outcomes of the OOC workshop, we present an overview of design methods and optical performance metrics developed for coronagraph instruments. The design and optimization of coronagraphs for future telescopes has progressed rapidly over the past several years in the context of space mission studies for Exo-C, WFIRST, HabEx, and LUVOIR as well as ground-based telescopes. Design tools have been developed at several institutions to optimize a variety of coronagraph mask types. We aim to give a broad overview of the approaches used, examples of their utility, and provide the optimization tools to the community. Though it is clear that the basic function of coronagraphs is to suppress starlight while maintaining light from off-axis sources, our community lacks a general set of standard performance metrics that apply to both detecting and characterizing exoplanets. The attendees of the OOC workshop agreed that it would benefit our community to clearly define quantities for comparing the performance of coronagraph designs and systems. Therefore, we also present a set of metrics that may be applied to theoretical designs, testbeds, and deployed instruments. We show how these quantities may be used to easily relate the basic properties of the optical instrument to the detection significance of the given point source in the presence of realistic noise.Comment: To appear in Proceedings of the SPIE, vol. 1069

Markov models for fMRI correlation structure: is brain functional connectivity small world, or decomposable into networks?

Correlations in the signal observed via functional Magnetic Resonance Imaging (fMRI), are expected to reveal the interactions in the underlying neural populations through hemodynamic response. In particular, they highlight distributed set of mutually correlated regions that correspond to brain networks related to different cognitive functions. Yet graph-theoretical studies of neural connections give a different picture: that of a highly integrated system with small-world properties: local clustering but with short pathways across the complete structure. We examine the conditional independence properties of the fMRI signal, i.e. its Markov structure, to find realistic assumptions on the connectivity structure that are required to explain the observed functional connectivity. In particular we seek a decomposition of the Markov structure into segregated functional networks using decomposable graphs: a set of strongly-connected and partially overlapping cliques. We introduce a new method to efficiently extract such cliques on a large, strongly-connected graph. We compare methods learning different graph structures from functional connectivity by testing the goodness of fit of the model they learn on new data. We find that summarizing the structure as strongly-connected networks can give a good description only for very large and overlapping networks. These results highlight that Markov models are good tools to identify the structure of brain connectivity from fMRI signals, but for this purpose they must reflect the small-world properties of the underlying neural systems

Exoplanet Imaging Data Challenge, phase II: Characterization of exoplanet signals in high-contrast images

Today, there exists a wide variety of algorithms dedicated to high-contrast imaging, especially for the detection and characterisation of exoplanet signals. These algorithms are tailored to address the very high contrast between the exoplanet signal(s), which can be more than two orders of magnitude fainter than the bright starlight residuals in coronagraphic images. The starlight residuals are inhomogeneously distributed and follow various timescales that depend on the observing conditions and on the target star brightness. Disentangling the exoplanet signals within the starlight residuals is therefore challenging, and new post-processing algorithms are striving to achieve more accurate astrophysical results. The Exoplanet Imaging Data Challenge is a community-wide effort to develop, compare and evaluate algorithms using a set of benchmark high-contrast imaging datasets. After a first phase ran in 2020 and focused on the detection capabilities of existing algorithms, the focus of this ongoing second phase is to compare the characterisation capabilities of state-of-the-art techniques. The characterisation of planetary companions is two-fold: the astrometry (estimated position with respect to the host star) and spectrophotometry (estimated contrast with respect to the host star, as a function of wavelength). The goal of this second phase is to offer a platform for the community to benchmark techniques in a fair, homogeneous and robust way, and to foster collaborations.Comment: Submitted to SPIE Astronomical Telescopes + Instrumentation 2022, Adaptive Optics Systems VIII, Paper 12185-

Under pressure: Response urgency modulates striatal and insula activity during decision-making under risk

When deciding whether to bet in situations that involve potential monetary loss or gain (mixed gambles), a subjective sense of pressure can influence the evaluation of the expected utility associated with each choice option. Here, we explored how gambling decisions, their psychophysiological and neural counterparts are modulated by an induced sense of urgency to respond. Urgency influenced decision times and evoked heart rate responses, interacting with the expected value of each gamble. Using functional MRI, we observed that this interaction was associated with changes in the activity of the striatum, a critical region for both reward and choice selection, and within the insula, a region implicated as the substrate of affective feelings arising from interoceptive signals which influence motivational behavior. Our findings bridge current psychophysiological and neurobiological models of value representation and action-programming, identifying the striatum and insular cortex as the key substrates of decision-making under risk and urgency

Effective connectivity reveals strategy differences in an expert calculator

Mathematical reasoning is a core component of cognition and the study of experts defines the upper limits of human cognitive abilities, which is why we are fascinated by peak performers, such as chess masters and mental calculators. Here, we investigated the neural bases of calendrical skills, i.e. the ability to rapidly identify the weekday of a particular date, in a gifted mental calculator who does not fall in the autistic spectrum, using functional MRI. Graph-based mapping of effective connectivity, but not univariate analysis, revealed distinct anatomical location of “cortical hubs” supporting the processing of well-practiced close dates and less-practiced remote dates: the former engaged predominantly occipital and medial temporal areas, whereas the latter were associated mainly with prefrontal, orbitofrontal and anterior cingulate connectivity. These results point to the effect of extensive practice on the development of expertise and long term working memory, and demonstrate the role of frontal networks in supporting performance on less practiced calculations, which incur additional processing demands. Through the example of calendrical skills, our results demonstrate that the ability to perform complex calculations is initially supported by extensive attentional and strategic resources, which, as expertise develops, are gradually replaced by access to long term working memory for familiar material