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

Approximation of conformal mappings using conformally equivalent triangular lattices

Consider discrete conformal maps defined on the basis of two conformally equivalent triangle meshes, that is edge lengths are related by scale factors associated to the vertices. Given a smooth conformal map $f$, we show that it can be approximated by such discrete conformal maps $f^\epsilon$. In particular, let $T$ be an infinite regular triangulation of the plane with congruent triangles and only acute angles (i.e.\ $<\pi/2$). We scale this tiling by $\epsilon>0$ and approximate a compact subset of the domain of $f$ with a portion of it. For $\epsilon$ small enough we prove that there exists a conformally equivalent triangle mesh whose scale factors are given by $\log|f'|$ on the boundary. Furthermore we show that the corresponding discrete conformal maps $f^\epsilon$ converge to $f$ uniformly in $C^1$ with error of order $\epsilon$.Comment: 14 pages, 3 figures; v2 typos corrected, revised introduction, some proofs extende

Enhanced Delivery of Rituximab Into Brain and Lymph Nodes Using Timed-Release Nanocapsules in Non-Human Primates.

Tumor metastasis into the central nervous system (CNS) and lymph nodes (LNs) is a major obstacle for effective therapies. Therapeutic monoclonal antibodies (mAb) have revolutionized tumor treatment; however, their efficacy for treating metastatic tumors-particularly, CNS and LN metastases-is poor due to inefficient penetration into the CNS and LNs following intravenous injection. We recently reported an effective delivery of mAb to the CNS by encapsulating the anti-CD20 mAb rituximab (RTX) within a thin shell of polymer that contains the analogs of choline and acetylcholine receptors. This encapsulated RTX, denoted as n-RTX, eliminated lymphoma cells systemically in a xenografted humanized mouse model using an immunodeficient mouse as a recipient of human hematopoietic stem/progenitor cells and fetal thymus more effectively than native RTX; importantly, n-RTX showed notable anti-tumor effect on CNS metastases which is unable to show by native RTX. As an important step toward future clinical translation of this technology, we further analyzed the properties of n-RTX in immunocompetent animals, rats, and non-human primates (NHPs). Our results show that a single intravenous injection of n-RTX resulted in 10-fold greater levels in the CNS and 2-3-fold greater levels in the LNs of RTX, respectively, than the injection of native RTX in both rats and NHPs. In addition, we demonstrate the enhanced delivery and efficient B-cell depletion in lymphoid organs of NHPs with n-RTX. Moreover, detailed hematological analysis and liver enzyme activity tests indicate n-RTX treatment is safe in NHPs. As this nanocapsule platform can be universally applied to other therapeutic mAbs, it holds great promise for extending mAb therapy to poorly accessible body compartments

Predictive direct power control for dual-active-bridge multilevel inverter based on conservative power theory

This paper explores the feasibility of multilevel dual-active bridge-inverter (DABMI) applications for grid-connected applications of a modern Model of Predictive Direct Power Control (MPDPC) based on the conservative power theory (CPT). In the case of unbalanced grid voltages, the objective of the study is to promote continued active and reactive energy in MPDPC without reducing effciency such as transient response and current harmonics. The nature of the instantaneous p-q theory permits only one out of three control targets to be fulfilled. The proposed control approached directly regulates the instantaneous active and reactive power to achieve three particular control objectives namely sinusoidal and symmetrical grid current, cancelling twice of fundamental grid frequency reactive power ripples, and removing twice grid frequency active power ripple. The techniques of complicated Grid part sequence extraction are unnecessary and improved at no extra expense, as is the case with current MPDPC fault-tolerant approaches. The instantaneous power at the next sampling instant is predicted with the newly developed discrete-time model. Each possible switching state will then be evaluated in the cost function defined until the optimal state which lead to the minimum power errors is determined. In MATLAB/Simulink simulation, the proposed CPT-based MPDPC measures reliability and performance at balanced and unbalanced grid voltages then compared with the conventional and existing MPDPC The proposed method manages to achieve all of three control targets which generates sinusoidal grid currents and attenuates active and reactive power ripple of twice the grid frequency exactly at the same time without losing its critical effciency including transient reaction and current harmonics

The novel mTOR inhibitor RAD001 (Everolimus) induces antiproliferative effects in human pancreatic neuroendocrine tumor cells

Background/Aim: Tumors exhibiting constitutively activated PI(3) K/Akt/mTOR signaling are hypersensitive to mTOR inhibitors such as RAD001 (everolimus) which is presently being investigated in clinical phase II trials in various tumor entities, including neuroendocrine tumors (NETs). However, no preclinical data about the effects of RAD001 on NET cells have been published. In this study, we aimed to evaluate the effects of RAD001 on BON cells, a human pancreatic NET cell line that exhibits constitutively activated PI(3) K/Akt/mTOR signaling. Methods: BON cells were treated with different concentrations of RAD001 to analyze its effect on cell growth using proliferation assays. Apoptosis was examined by Western blot analysis of caspase-3/PARP cleavage and by FACS analysis of DNA fragmentation. Results: RAD001 potently inhibited BON cell growth in a dose-dependent manner which was dependent on the serum concentration in the medium. RAD001-induced growth inhibition involved G0/G1-phase arrest as well as induction of apoptosis. Conclusion: In summary, our data demonstrate antiproliferative and apoptotic effects of RAD001 in NET cells in vitro supporting its clinical use in current phase II trials in NET patients. Copyright (c) 2007 S. Karger AG, Basel

Semiparametric Multivariate Accelerated Failure Time Model with Generalized Estimating Equations

The semiparametric accelerated failure time model is not as widely used as the Cox relative risk model mainly due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations provide promising tools to make the accelerate failure time models more attractive in practice. For semiparametric multivariate accelerated failure time models, we propose a generalized estimating equation approach to account for the multivariate dependence through working correlation structures. The marginal error distributions can be either identical as in sequential event settings or different as in parallel event settings. Some regression coefficients can be shared across margins as needed. The initial estimator is a rank-based estimator with Gehan's weight, but obtained from an induced smoothing approach with computation ease. The resulting estimator is consistent and asymptotically normal, with a variance estimated through a multiplier resampling method. In a simulation study, our estimator was up to three times as efficient as the initial estimator, especially with stronger multivariate dependence and heavier censoring percentage. Two real examples demonstrate the utility of the proposed method

Entanglement of single-photons and chiral phonons in atomically thin WSe2_2

Quantum entanglement is a fundamental phenomenon which, on the one hand, reveals deep connections between quantum mechanics, gravity and the space-time; on the other hand, has practical applications as a key resource in quantum information processing. While it is routinely achieved in photon-atom ensembles, entanglement involving the solid-state or macroscopic objects remains challenging albeit promising for both fundamental physics and technological applications. Here, we report entanglement between collective, chiral vibrations in two-dimensional (2D) WSe$_2$ host --- chiral phonons (CPs) --- and single-photons emitted from quantum dots (QDs) present in it. CPs which carry angular momentum were recently observed in WSe$_2$ and are a distinguishing feature of the underlying honeycomb lattice. The entanglement results from a "which-way" scattering process, involving an optical excitation in a QD and doubly-degenerate CPs, which takes place via two indistinguishable paths. Our unveiling of entanglement involving a macroscopic, collective excitation together with strong interaction between CPs and QDs in 2D materials opens up ways for phonon-driven entanglement of QDs and engineering chiral or non-reciprocal interactions at the single-photon level