Imaging drugs, metabolites and biomarkers in rodent lung: a DESI MS strategy for the evaluation of drug-induced lipidosis

© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Within drug development and pre-clinical trials, a common, significant and poorly understood event is the development of drug-induced lipidosis in tissues and cells. In this manuscript, we describe a mass spectrometry imaging strategy, involving repeated analysis of tissue sections by DESI MS, in positive and negative polarities, using MS and MS/MS modes. We present results of the detected distributions of the administered drug, drug metabolites, lipid molecules and a putative marker of lipidosis, di-docosahexaenoyl (22:6)-bis(monoacylglycerol) phosphate (di-22:6-BMP). A range of strategies have previously been reported for detection, isolation and identification of this compound, which is an isomer of di-docosahexaenoic (22:6 n-3) phosphatidylglycerol (di-22:6 PG), a commonly found lipid that acts as a surfactant in lung tissues. We show that MS imaging using MS/MS can be used to differentiate these compounds of identical mass, based upon the different distributions of abundant fragment ions. Registration of images of these fragments, and detected drugs and metabolites, is presented as a new method for studying drug-induced lipidosis in tissues. Graphical abstract.Peer reviewe

Far From \u27Easy\u27 Spectroscopy with the 8π and GRIFFIN Spectrometers at TRIUMF-ISAC

The 8π spectrometer, installed at the TRIUMF-ISAC facility, was the world\u27s most sensitive γ-ray spectrometer dedicated to β-decay studies. A description is given of the 8π spectrometer and its auxiliary detectors including the plastic scintillator array SCEPTAR used for β-particle tagging and the Si(Li) array PACES for conversion electron measurements, its moving tape collector, and its data acquisition system. The recent investigation of the decay of 124Cs to study the nuclear structure of 124Xe, and how the β-decay measurements complemented previous Coulomb excitation studies, is highlighted, including the extraction of the deformation parameters for the excited 0+ bands in 124Xe. As a by-product, the decay scheme of the (7+) 124Cs isomeric state, for which the data from the PACES detectors were vital, was studied. Finally, a description of the new GRIFFIN spectrometer, which uses the same auxiliary detectors as the 8π spectrometer, is given

Revealing components of the galaxy population through nonparametric techniques

The distributions of galaxy properties vary with environment, and are often multimodal, suggesting that the galaxy population may be a combination of multiple components. The behaviour of these components versus environment holds details about the processes of galaxy development. To release this information we apply a novel, nonparametric statistical technique, identifying four components present in the distribution of galaxy H$\alpha$ emission-line equivalent-widths. We interpret these components as passive, star-forming, and two varieties of active galactic nuclei. Independent of this interpretation, the properties of each component are remarkably constant as a function of environment. Only their relative proportions display substantial variation. The galaxy population thus appears to comprise distinct components which are individually independent of environment, with galaxies rapidly transitioning between components as they move into denser environments.Comment: 12 pages, 10 figures, accepted for publication in MNRA

Galaxy Zoo: Reproducing Galaxy Morphologies Via Machine Learning

We present morphological classifications obtained using machine learning for objects in SDSS DR6 that have been classified by Galaxy Zoo into three classes, namely early types, spirals and point sources/artifacts. An artificial neural network is trained on a subset of objects classified by the human eye and we test whether the machine learning algorithm can reproduce the human classifications for the rest of the sample. We find that the success of the neural network in matching the human classifications depends crucially on the set of input parameters chosen for the machine-learning algorithm. The colours and parameters associated with profile-fitting are reasonable in separating the objects into three classes. However, these results are considerably improved when adding adaptive shape parameters as well as concentration and texture. The adaptive moments, concentration and texture parameters alone cannot distinguish between early type galaxies and the point sources/artifacts. Using a set of twelve parameters, the neural network is able to reproduce the human classifications to better than 90% for all three morphological classes. We find that using a training set that is incomplete in magnitude does not degrade our results given our particular choice of the input parameters to the network. We conclude that it is promising to use machine- learning algorithms to perform morphological classification for the next generation of wide-field imaging surveys and that the Galaxy Zoo catalogue provides an invaluable training set for such purposes.Comment: 13 Pages, 5 figures, 10 tables. Accepted for publication in MNRAS. Revised to match accepted version

The dwarf galaxy population as revealed by ALFALFA

The combination of sensitivity and large sky coverage of the ALFALFA HI survey has enabled the detection of difficult to observe low mass galaxies in large numbers, including dwarf galaxies overlooked in optical surveys. Three different, but connected, studies of dwarf galaxies from the ALFALFA survey are of particular interest: SHIELD (Survey of HI in Extremely Low-mass Dwarfs), candidate gas-rich ultra- faint dwarf galaxies, and the (Almost) Dark population. SHIELD is a systematic multiwavelength study of all dwarf galaxies from ALFALFA with MHI < 107.2 M☉ and clear optical counterparts. Candidate gas-rich ultra-faint dwarf galaxies extend the dwarf galaxy population to even lower masses. These galaxies are identified as isolated HI clouds with no discernible optical counterpart but subsequent observations reveal that some are extremely faint, gas- dominated galaxies. Leo P, discovered first as an HI detection, and then found to be an actively star-forming galaxy, bridges the gap between these candidate galaxies and the SHIELD sample. The (Almost) Dark sample consists of galaxies whose optical counterparts are overlooked in current optical surveys but which are clear detections in ALFALFA. This sample includes field gas-rich ultra-diffuse galaxies. Coma P, with a peak surface brightness of only ~26.4 mag arcsec-2 in g', demonstrates the sort of extreme low surface brightness galaxy that can be discovered in an HI survey

The Enigmatic (Almost) Dark Galaxy Coma P: Distance Measurement and Stellar Populations from HST Imaging

We present Hubble Space Telescope (HST) observations of the low surface brightness (SB) galaxy Coma P. This system was first discovered in the Arecibo Legacy Fast ALFA HI survey and was cataloged as an (almost) dark galaxy because it did not exhibit any obvious optical counterpart in the available survey data (e.g., Sloan Digital Sky Survey). Subsequent WIYN pODI imaging revealed an ultra-low SB stellar component located at the center of the HI detection. We use the HST images to produce a deep color-magnitude diagram (CMD) of the resolved stellar population present in Coma P. We clearly detect a red stellar sequence that we interpret to be a red giant branch, and use it to infer a tip of the red giant branch (TRGB) distance of 5.50$^{+0.28}_{-0.53}$ Mpc. The new distance is substantially lower than earlier estimates and shows that Coma P is an extreme dwarf galaxy. Our derived stellar mass is only 4.3 $\times$ 10$^5$ $M_\odot$, meaning that Coma P has an extreme HI-to-stellar mass ratio of 81. We present a detailed analysis of the galaxy environment within which Coma P resides. We hypothesize that Coma P formed within a local void and has spent most of its lifetime in a low-density environment. Over time, the gravitational attraction of the galaxies located in the void wall has moved it to the edge, where it had a recent "fly-by" interaction with M64. We investigate the possibility that Coma P is at a farther distance and conclude that the available data are best fit by a distance of 5.5 Mpc.Comment: 22 pages, 11 figures. Accepted for publication in the Astronomical Journa

High-Statistics β\u3csup\u3e+\u3c/sup\u3e/EC-Decay Study of \u3csup\u3e122\u3c/sup\u3eXe

Low-lying excited states of 122Xe have been studied via the β+/EC decay of 122Cs with the 8π γ-ray spectrometer at the TRIUMF Isotope Separator and Accelerator facility. The data collected have enabled the observation of new in-band transitions in the excited 0+ state bands. In addition, the 2+ members of the second 0+ and third 0+ state bands have been firmly confirmed by angular correlation analysis