Neurogenesis Deep Learning

Neural machine learning methods, such as deep neural networks (DNN), have achieved remarkable success in a number of complex data processing tasks. These methods have arguably had their strongest impact on tasks such as image and audio processing - data processing domains in which humans have long held clear advantages over conventional algorithms. In contrast to biological neural systems, which are capable of learning continuously, deep artificial networks have a limited ability for incorporating new information in an already trained network. As a result, methods for continuous learning are potentially highly impactful in enabling the application of deep networks to dynamic data sets. Here, inspired by the process of adult neurogenesis in the hippocampus, we explore the potential for adding new neurons to deep layers of artificial neural networks in order to facilitate their acquisition of novel information while preserving previously trained data representations. Our results on the MNIST handwritten digit dataset and the NIST SD 19 dataset, which includes lower and upper case letters and digits, demonstrate that neurogenesis is well suited for addressing the stability-plasticity dilemma that has long challenged adaptive machine learning algorithms.Comment: 8 pages, 8 figures, Accepted to 2017 International Joint Conference on Neural Networks (IJCNN 2017

MicroRNA profile of extracellular vesicles released by Müller glial cells

IntroductionAs with any other radial glia in the central nervous system, Müller glia derive from the same neuroepithelial precursors, perform similar functions, and exhibit neurogenic properties as radial glia in the brain. Müller glial cells retain progenitor-like characteristics in the adult human eye and can partially restore visual function upon intravitreal transplantation into animal models of glaucoma. Recently, it has been demonstrated that intracellular communication is possible via the secretion of nano-sized membrane-bound extracellular vesicles (EV), which contain bioactive molecules like microRNA (miRNA) and proteins that induce phenotypic changes when internalised by recipient cells.MethodsWe conducted high-throughput sequencing to profile the microRNA signature of EV populations secreted by Müller glia in culture and used bioinformatics tools to evaluate their potential role in the neuroprotective signalling attributed to these cells.ResultsSequencing of miRNA within Müller EV suggested enrichment with species associated with stem cells such as miR-21 and miR-16, as well as with miRNA previously found to play a role in diverse Müller cell functions in the retina: miR-9, miR-125b, and the let-7 family. A total of 51 miRNAs were found to be differentially enriched in EV compared to the whole cells from which EV originated. Bioinformatics analyses also indicated that preferential enrichment of species was demonstrated to regulate genes involved in cell proliferation and survival, including PTEN, the master inhibitor of the PI3K/AKT pathway.DiscussionThe results suggest that the release by Müller cells of miRNA-enriched EV abundant in species that regulate anti-apoptotic signalling networks is likely to represent a significant proportion of the neuroprotective effect observed after the transplantation of these cells into animal models of retinal ganglion cell (RGC) depletion. Future studies will seek to evaluate the modulation of putative genes as well as the activation of these pathways in in vitro and in vivo models following the internalisation of Müller-EV by target retinal neurons

A High Statistics Search for Ultra-High Energy Gamma-Ray Emission from Cygnus X-3 and Hercules X-1

We have carried out a high statistics (2 Billion events) search for ultra-high energy gamma-ray emission from the X-ray binary sources Cygnus X-3 and Hercules X-1. Using data taken with the CASA-MIA detector over a five year period (1990-1995), we find no evidence for steady emission from either source at energies above 115 TeV. The derived upper limits on such emission are more than two orders of magnitude lower than earlier claimed detections. We also find no evidence for neutral particle or gamma-ray emission from either source on time scales of one day and 0.5 hr. For Cygnus X-3, there is no evidence for emission correlated with the 4.8 hr X-ray periodicity or with the occurrence of large radio flares. Unless one postulates that these sources were very active earlier and are now dormant, the limits presented here put into question the earlier results, and highlight the difficulties that possible future experiments will have in detecting gamma-ray signals at ultra-high energies.Comment: 26 LaTeX pages, 16 PostScript figures, uses psfig.sty to be published in Physical Review

The First Hour of Extra-galactic Data of the Sloan Digital Sky Survey Spectroscopic Commissioning: The Coma Cluster

On 26 May 1999, one of the Sloan Digital Sky Survey (SDSS) fiber-fed spectrographs saw astronomical first light. This was followed by the first spectroscopic commissioning run during the dark period of June 1999. We present here the first hour of extra-galactic spectroscopy taken during these early commissioning stages: an observation of the Coma cluster of galaxies. Our data samples the Southern part of this cluster, out to a radius of 1.5degrees and thus fully covers the NGC 4839 group. We outline in this paper the main characteristics of the SDSS spectroscopic systems and provide redshifts and spectral classifications for 196 Coma galaxies, of which 45 redshifts are new. For the 151 galaxies in common with the literature, we find excellent agreement between our redshift determinations and the published values. As part of our analysis, we have investigated four different spectral classification algorithms: spectral line strengths, a principal component decomposition, a wavelet analysis and the fitting of spectral synthesis models to the data. We find that a significant fraction (25%) of our observed Coma galaxies show signs of recent star-formation activity and that the velocity dispersion of these active galaxies (emission-line and post-starburst galaxies) is 30% larger than the absorption-line galaxies. We also find no active galaxies within the central (projected) 200 h-1 Kpc of the cluster. The spatial distribution of our Coma active galaxies is consistent with that found at higher redshift for the CNOC1 cluster survey. Beyond the core region, the fraction of bright active galaxies appears to rise slowly out to the virial radius and are randomly distributed within the cluster with no apparent correlation with the potential merger of the NGC 4839 group. [ABRIDGED]Comment: Accepted in AJ, 65 pages, 20 figures, 5 table

The Fifth Data Release of the Sloan Digital Sky Survey

This paper describes the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). DR5 includes all survey quality data taken through June 2005 and represents the completion of the SDSS-I project (whose successor, SDSS-II will continue through mid-2008). It includes five-band photometric data for 217 million objects selected over 8000 square degrees, and 1,048,960 spectra of galaxies, quasars, and stars selected from 5713 square degrees of that imaging data. These numbers represent a roughly 20% increment over those of the Fourth Data Release; all the data from previous data releases are included in the present release. In addition to "standard" SDSS observations, DR5 includes repeat scans of the southern equatorial stripe, imaging scans across M31 and the core of the Perseus cluster of galaxies, and the first spectroscopic data from SEGUE, a survey to explore the kinematics and chemical evolution of the Galaxy. The catalog database incorporates several new features, including photometric redshifts of galaxies, tables of matched objects in overlap regions of the imaging survey, and tools that allow precise computations of survey geometry for statistical investigations.Comment: ApJ Supp, in press, October 2007. This paper describes DR5. The SDSS Sixth Data Release (DR6) is now public, available from http://www.sdss.or

Discovering collectively informative descriptors from high-throughput experiments

<p>Abstract</p> <p>Background</p> <p>Improvements in high-throughput technology and its increasing use have led to the generation of many highly complex datasets that often address similar biological questions. Combining information from these studies can increase the reliability and generalizability of results and also yield new insights that guide future research.</p> <p>Results</p> <p>This paper describes a novel algorithm called BLANKET for symmetric analysis of two experiments that assess informativeness of descriptors. The experiments are required to be related only in that their descriptor sets intersect substantially and their definitions of case and control are consistent. From resulting lists of n descriptors ranked by informativeness, BLANKET determines <b>shortlists </b>of descriptors from each experiment, generally of different lengths p and q. For any pair of shortlists, four numbers are evident: the number of descriptors appearing in both shortlists, in exactly one shortlist, or in neither shortlist. From the associated contingency table, BLANKET computes Right Fisher Exact Test (RFET) values used as scores over a plane of possible pairs of shortlist lengths <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr></abbrgrp>. BLANKET then chooses a pair or pairs with RFET score less than a threshold; the threshold depends upon n and shortlist length limits and represents a quality of intersection achieved by less than 5% of random lists.</p> <p>Conclusions</p> <p>Researchers seek within a universe of descriptors some minimal subset that collectively and efficiently predicts experimental outcomes. Ideally, any smaller subset should be insufficient for reliable prediction and any larger subset should have little additional accuracy. As a method, BLANKET is easy to conceptualize and presents only moderate computational complexity. Many existing databases could be mined using BLANKET to suggest optimal sets of predictive descriptors.</p

The \u3cem\u3eChlamydomonas\u3c/em\u3e Genome Reveals the Evolution of Key Animal and Plant Functions

Chlamydomonas reinhardtii is a unicellular green alga whose lineage diverged from land plants over 1 billion years ago. It is a model system for studying chloroplast-based photosynthesis, as well as the structure, assembly, and function of eukaryotic flagella (cilia), which were inherited from the common ancestor of plants and animals, but lost in land plants. We sequenced the ∼120-megabase nuclear genome of Chlamydomonas and performed comparative phylogenomic analyses, identifying genes encoding uncharacterized proteins that are likely associated with the function and biogenesis of chloroplasts or eukaryotic flagella. Analyses of the Chlamydomonas genome advance our understanding of the ancestral eukaryotic cell, reveal previously unknown genes associated with photosynthetic and flagellar functions, and establish links between ciliopathy and the composition and function of flagella

The role of expertise in dynamic risk assessment: A reflection of the problem-solving strategies used by experienced fireground commanders

Although the concept of dynamic risk assessment has in recent times become more topical in the training manuals of most high risk domains, only a few empirical studies have reported how experts actually carry out this crucial task. The knowledge gap between research and practice in this area therefore calls for more empirical investigation within the naturalistic environment. In this paper, we present and discuss the problem solving strategies employed by sixteen experienced operational firefighters using a qualitative knowledge elicitation tool — the critical decision method. Findings revealed that dynamic risk assessment is not merely a process of weighing the risks of a proposed course of action against its benefits, but rather an experiential and pattern recognition process. The paper concludes by discussing the implications of designing training curriculum for the less experienced officers using the elicited expert knowledge

Dynamics of HIV-1 Assembly and Release

Assembly and release of human immunodeficiency virus (HIV) occur at the plasma membrane of infected cells and are driven by the Gag polyprotein. Previous studies analyzed viral morphogenesis using biochemical methods and static images, while dynamic and kinetic information has been lacking until very recently. Using a combination of wide-field and total internal reflection fluorescence microscopy, we have investigated the assembly and release of fluorescently labeled HIV-1 at the plasma membrane of living cells with high time resolution. Gag assembled into discrete clusters corresponding to single virions. Formation of multiple particles from the same site was rarely observed. Using a photoconvertible fluorescent protein fused to Gag, we determined that assembly was nucleated preferentially by Gag molecules that had recently attached to the plasma membrane or arrived directly from the cytosol. Both membrane-bound and cytosol derived Gag polyproteins contributed to the growing bud. After their initial appearance, assembly sites accumulated at the plasma membrane of individual cells over 1–2 hours. Assembly kinetics were rapid: the number of Gag molecules at a budding site increased, following a saturating exponential with a rate constant of ∼5×10−3 s−1, corresponding to 8–9 min for 90% completion of assembly for a single virion. Release of extracellular particles was observed at ∼1,500±700 s after the onset of assembly. The ability of the virus to recruit components of the cellular ESCRT machinery or to undergo proteolytic maturation, or the absence of Vpu did not significantly alter the assembly kinetics

Quantitative Analysis of Mechanisms That Govern Red Blood Cell Age Structure and Dynamics during Anaemia

Mathematical modelling has proven an important tool in elucidating and quantifying mechanisms that govern the age structure and population dynamics of red blood cells (RBCs). Here we synthesise ideas from previous experimental data and the mathematical modelling literature with new data in order to test hypotheses and generate new predictions about these mechanisms. The result is a set of competing hypotheses about three intrinsic mechanisms: the feedback from circulating RBC concentration to production rate of immature RBCs (reticulocytes) in bone marrow, the release of reticulocytes from bone marrow into the circulation, and their subsequent ageing and clearance. In addition we examine two mechanisms specific to our experimental system: the effect of phenylhydrazine (PHZ) and blood sampling on RBC dynamics. We performed a set of experiments to quantify the dynamics of reticulocyte proportion, RBC concentration, and erythropoietin concentration in PHZ-induced anaemic mice. By quantifying experimental error we are able to fit and assess each hypothesis against our data and recover parameter estimates using Markov chain Monte Carlo based Bayesian inference. We find that, under normal conditions, about 3% of reticulocytes are released early from bone marrow and upon maturation all cells are released immediately. In the circulation, RBCs undergo random clearance but have a maximum lifespan of about 50 days. Under anaemic conditions reticulocyte production rate is linearly correlated with the difference between normal and anaemic RBC concentrations, and their release rate is exponentially correlated with the same. PHZ appears to age rather than kill RBCs, and younger RBCs are affected more than older RBCs. Blood sampling caused short aperiodic spikes in the proportion of reticulocytes which appear to have a different developmental pathway than normal reticulocytes. We also provide evidence of large diurnal oscillations in serum erythropoietin levels during anaemia