Detection of Neuritic Plaques in Alzheimer's Disease Mouse Model

Alzheimer's disease (AD) is the most common neurodegenerative disorder leading to dementia. Neuritic plaque formation is one of the pathological hallmarks of Alzheimer's disease. The central component of neuritic plaques is a small filamentous protein called amyloid β protein (Aβ)1, which is derived from sequential proteolytic cleavage of the beta-amyloid precursor protein (APP) by β-secretase and γ-secretase. The amyloid hypothesis entails that Aγ-containing plaques as the underlying toxic mechanism in AD pathology2. The postmortem analysis of the presence of neuritic plaque confirms the diagnosis of AD. To further our understanding of Aγ neurobiology in AD pathogenesis, various mouse strains expressing AD-related mutations in the human APP genes were generated. Depending on the severity of the disease, these mice will develop neuritic plaques at different ages. These mice serve as invaluable tools for studying the pathogenesis and drug development that could affect the APP processing pathway and neuritic plaque formation. In this protocol, we employ an immunohistochemical method for specific detection of neuritic plaques in AD model mice. We will specifically discuss the preparation from extracting the half brain, paraformaldehyde fixation, cryosectioning, and two methods to detect neurotic plaques in AD transgenic mice: immunohistochemical detection using the ABC and DAB method and fluorescent detection using thiofalvin S staining method

Robust high-dimensional precision matrix estimation

The dependency structure of multivariate data can be analyzed using the covariance matrix $\Sigma$. In many fields the precision matrix $\Sigma^{-1}$ is even more informative. As the sample covariance estimator is singular in high-dimensions, it cannot be used to obtain a precision matrix estimator. A popular high-dimensional estimator is the graphical lasso, but it lacks robustness. We consider the high-dimensional independent contamination model. Here, even a small percentage of contaminated cells in the data matrix may lead to a high percentage of contaminated rows. Downweighting entire observations, which is done by traditional robust procedures, would then results in a loss of information. In this paper, we formally prove that replacing the sample covariance matrix in the graphical lasso with an elementwise robust covariance matrix leads to an elementwise robust, sparse precision matrix estimator computable in high-dimensions. Examples of such elementwise robust covariance estimators are given. The final precision matrix estimator is positive definite, has a high breakdown point under elementwise contamination and can be computed fast

Scaling violations: Connections between elastic and inelastic hadron scattering in a geometrical approach

Starting from a short range expansion of the inelastic overlap function, capable of describing quite well the elastic pp and $\bar{p}p$ scattering data, we obtain extensions to the inelastic channel, through unitarity and an impact parameter approach. Based on geometrical arguments we infer some characteristics of the elementary hadronic process and this allows an excellent description of the inclusive multiplicity distributions in $pp$ and $\bar{p}p$ collisions. With this approach we quantitatively correlate the violations of both geometrical and KNO scaling in an analytical way. The physical picture from both channels is that the geometrical evolution of the hadronic constituents is principally reponsible for the energy dependence of the physical quantities rather than the dynamical (elementary) interaction itself.Comment: 16 pages, aps-revtex, 11 figure

Tight Lower Bound for Linear Sketches of Moments

The problem of estimating frequency moments of a data stream has attracted a lot of attention since the onset of streaming algorithms [AMS99]. While the space complexity for approximately computing the $p^{\rm th}$ moment, for $p\in(0,2]$ has been settled [KNW10], for $p>2$ the exact complexity remains open. For $p>2$ the current best algorithm uses $O(n^{1-2/p}\log n)$ words of space [AKO11,BO10], whereas the lower bound is of $\Omega(n^{1-2/p})$ [BJKS04]. In this paper, we show a tight lower bound of $\Omega(n^{1-2/p}\log n)$ words for the class of algorithms based on linear sketches, which store only a sketch $Ax$ of input vector $x$ and some (possibly randomized) matrix $A$. We note that all known algorithms for this problem are linear sketches.Comment: In Proceedings of the 40th International Colloquium on Automata, Languages and Programming (ICALP), Riga, Latvia, July 201

Quantization and Compressive Sensing

Quantization is an essential step in digitizing signals, and, therefore, an indispensable component of any modern acquisition system. This book chapter explores the interaction of quantization and compressive sensing and examines practical quantization strategies for compressive acquisition systems. Specifically, we first provide a brief overview of quantization and examine fundamental performance bounds applicable to any quantization approach. Next, we consider several forms of scalar quantizers, namely uniform, non-uniform, and 1-bit. We provide performance bounds and fundamental analysis, as well as practical quantizer designs and reconstruction algorithms that account for quantization. Furthermore, we provide an overview of Sigma-Delta ($\Sigma\Delta$) quantization in the compressed sensing context, and also discuss implementation issues, recovery algorithms and performance bounds. As we demonstrate, proper accounting for quantization and careful quantizer design has significant impact in the performance of a compressive acquisition system.Comment: 35 pages, 20 figures, to appear in Springer book "Compressed Sensing and Its Applications", 201

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

First-principles quantum transport modeling of thermoelectricity in single-molecule nanojunctions with graphene nanoribbon electrodes

We overview nonequilibrium Green function combined with density functional theory (NEGF-DFT) modeling of independent electron and phonon transport in nanojunctions with applications focused on a new class of thermoelectric devices where a single molecule is attached to two metallic zigzag graphene nanoribbons (ZGNRs) via highly transparent contacts. Such contacts make possible injection of evanescent wavefunctions from ZGNRs, so that their overlap within the molecular region generates a peak in the electronic transmission. Additionally, the spatial symmetry properties of the transverse propagating states in the ZGNR electrodes suppress hole-like contributions to the thermopower. Thus optimized thermopower, together with diminished phonon conductance through a ZGNR/molecule/ZGNR inhomogeneous structure, yields the thermoelectric figure of merit ZT~0.5 at room temperature and 0.5<ZT<2.5 below liquid nitrogen temperature. The reliance on evanescent mode transport and symmetry of propagating states in the electrodes makes the electronic-transport-determined power factor in this class of devices largely insensitive to the type of sufficiently short conjugated organic molecule, which we demonstrate by showing that both 18-annulene and C10 molecule sandwiched by the two ZGNR electrodes yield similar thermopower. Thus, one can search for molecules that will further reduce the phonon thermal conductance (in the denominator of ZT) while keeping the electronic power factor (in the nominator of ZT) optimized. We also show how often employed Brenner empirical interatomic potential for hydrocarbon systems fails to describe phonon transport in our single-molecule nanojunctions when contrasted with first-principles results obtained via NEGF-DFT methodology.Comment: 20 pages, 6 figures; mini-review article prepared for the special issue of the Journal of Computational Electronics on "Simulation of Thermal, Thermoelectric, and Electrothermal Phenomena in Nanostructures", edited by I. Knezevic and Z. Aksamij

Fungal diversity notes 1512-1610: taxonomic and phylogenetic contributions on genera and species of fungal taxa

This article is the 14th in the Fungal Diversity Notes series, wherein we report 98 taxa distributed in two phyla, seven classes, 26 orders and 50 families which are described and illustrated. Taxa in this study were collected from Australia, Brazil, Burkina Faso, Chile, China, Cyprus, Egypt, France, French Guiana, India, Indonesia, Italy, Laos, Mexico, Russia, Sri Lanka, Thailand, and Vietnam. There are 59 new taxa, 39 new hosts and new geographical distributions with one new combination. The 59 new species comprise Angustimassarina kunmingense, Asterina lopi, Asterina brigadeirensis, Bartalinia bidenticola, Bartalinia caryotae, Buellia pruinocalcarea, Coltricia insularis, Colletotrichum flexuosum, Colletotrichum thasutense, Coniochaeta caraganae, Coniothyrium yuccicola, Dematipyriforma aquatic, Dematipyriforma globispora, Dematipyriforma nilotica, Distoseptispora bambusicola, Fulvifomes jawadhuvensis, Fulvifomes malaiyanurensis, Fulvifomes thiruvannamalaiensis, Fusarium purpurea, Gerronema atrovirens, Gerronema flavum, Gerronema keralense, Gerronema kuruvense, Grammothele taiwanensis, Hongkongmyces changchunensis, Hypoxylon inaequale, Kirschsteiniothelia acutisporum, Kirschsteiniothelia crustaceum, Kirschsteiniothelia extensum, Kirschsteiniothelia septemseptatum, Kirschsteiniothelia spatiosum, Lecanora immersocalcarea, Lepiota subthailandica, Lindgomyces guizhouensis, Marthe asmius pallidoaurantiacus, Marasmius tangerinus, Neovaginatispora mangiferae, Pararamichloridium aquisubtropicum, Pestalotiopsis piraubensis, Phacidium chinaum, Phaeoisaria goiasensis, Phaeoseptum thailandicum, Pleurothecium aquisubtropicum, Pseudocercospora vernoniae, Pyrenophora verruculosa, Rhachomyces cruralis, Rhachomyces hyperommae, Rhachomyces magrinii, Rhachomyces platyprosophi, Rhizomarasmius cunninghamietorum, Skeletocutis cangshanensis, Skeletocutis subchrysella, Sporisorium anadelphiae-leptocomae, Tetraploa dashaoensis, Tomentella exiguelata, Tomentella fuscoaraneosa, Tricholomopsis lechatii, Vaginatispora flavispora and Wetmoreana blastidiocalcarea. The new combination is Torula sundara. The 39 new records on hosts and geographical distribution comprise Apiospora guiyangensis, Aplosporella artocarpi, Ascochyta medicaginicola, Astrocystis bambusicola, Athelia rolfsii, Bambusicola bambusae, Bipolaris luttrellii, Botryosphaeria dothidea, Chlorophyllum squamulosum, Colletotrichum aeschynomenes, Colletotrichum pandanicola, Coprinopsis cinerea, Corylicola italica, Curvularia alcornii, Curvularia senegalensis, Diaporthe foeniculina, Diaporthe longicolla, Diaporthe phaseolorum, Diatrypella quercina, Fusarium brachygibbosum, Helicoma aquaticum, Lepiota metulispora, Lepiota pongduadensis, Lepiota subvenenata, Melanconiella meridionalis, Monotosporella erecta, Nodulosphaeria digitalis, Palmiascoma gregariascomum, Periconia byssoides, Periconia cortaderiae, Pleopunctum ellipsoideum, Psilocybe keralensis, Scedosporium apiospermum, Scedosporium dehoogii, Scedosporium marina, Spegazzinia deightonii, Torula fici, Wiesneriomyces laurinus and Xylaria venosula. All these taxa are supported by morphological and multigene phylogenetic analyses. This article allows the researchers to publish fungal collections which are important for future studies. An updated, accurate and timely report of fungus-host and fungus-geography is important. We also provide an updated list of fungal taxa published in the previous fungal diversity notes. In this list, erroneous taxa and synonyms are marked and corrected accordingly

Measurement of the cross section for isolated-photon plus jet production in pp collisions at √s=13 TeV using the ATLAS detector

The dynamics of isolated-photon production in association with a jet in proton–proton collisions at a centre-of-mass energy of 13 TeV are studied with the ATLAS detector at the LHC using a dataset with an integrated luminosity of 3.2 fb−1. Photons are required to have transverse energies above 125 GeV. Jets are identified using the anti- algorithm with radius parameter and required to have transverse momenta above 100 GeV. Measurements of isolated-photon plus jet cross sections are presented as functions of the leading-photon transverse energy, the leading-jet transverse momentum, the azimuthal angular separation between the photon and the jet, the photon–jet invariant mass and the scattering angle in the photon–jet centre-of-mass system. Tree-level plus parton-shower predictions from Sherpa and Pythia as well as next-to-leading-order QCD predictions from Jetphox and Sherpa are compared to the measurements

A search for resonances decaying into a Higgs boson and a new particle X in the XH → qqbb final state with the ATLAS detector

A search for heavy resonances decaying into a Higgs boson (H) and a new particle (X) is reported, utilizing 36.1 fb−1 of proton–proton collision data at collected during 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider. The particle X is assumed to decay to a pair of light quarks, and the fully hadronic final state is analysed. The search considers the regime of high XH resonance masses, where the X and H bosons are both highly Lorentz-boosted and are each reconstructed using a single jet with large radius parameter. A two-dimensional phase space of XH mass versus X mass is scanned for evidence of a signal, over a range of XH resonance mass values between 1 TeV and 4 TeV, and for X particles with masses from 50 GeV to 1000 GeV. All search results are consistent with the expectations for the background due to Standard Model processes, and 95% CL upper limits are set, as a function of XH and X masses, on the production cross-section of the resonance