Searching for dark matter annihilation in recently discovered Milky Way satellites with Fermi-LAT

We search for excess γ-ray emission coincident with the positions of confirmed and candidate Milky Way satellite galaxies using six years of data from the Fermi Large Area Telescope (LAT). Our sample of 45 stellar systems includes 28 kinematically confirmed dark-matter-dominated dwarf spheroidal galaxies (dSphs) and 17 recently discovered systems that have photometric characteristics consistent with the population of known dSphs. For each of these targets, the relative predicted γ-ray flux due to dark matter annihilation is taken from kinematic analysis if available, and estimated from a distance-based scaling relation otherwise, assuming that the stellar systems are DM-dominated dSphs. LAT data coincident with four of the newly discovered targets show a slight preference (each ~2σ local) for γ-ray emission in excess of the background. However, the ensemble of derived γ-ray flux upper limits for individual targets is consistent with the expectation from analyzing random blank-sky regions, and a combined analysis of the population of stellar systems yields no globally significant excess (global significance 1 TeV and mDM,t+t-> 70 GeV) and weakening by a factor of ~1.5 at lower masses relative to previously observed limits

VDES J2325−5229 a z = 2.7 gravitationally lensed quasar discovered using morphology-independent supervised machine learning

We present the discovery and preliminary characterization of a gravitationally lensed quasar with a source redshift zs = 2.74 and image separation of 2.9 arcsec lensed by a foreground zl = 0.40 elliptical galaxy. Since optical observations of gravitationally lensed quasars showthe lens system as a superposition of multiple point sources and a foreground lensing galaxy, we have developed a morphology-independent multi-wavelength approach to the photometric selection of lensed quasar candidates based on Gaussian Mixture Models (GMM) supervised machine learning. Using this technique and gi multicolour photometric observations from the Dark Energy Survey (DES), near-IR JK photometry from the VISTA Hemisphere Survey (VHS) and WISE mid-IR photometry, we have identified a candidate system with two catalogue components with iAB = 18.61 and iAB = 20.44 comprising an elliptical galaxy and two blue point sources. Spectroscopic follow-up with NTT and the use of an archival AAT spectrum show that the point sources can be identified as a lensed quasar with an emission line redshift of z = 2.739 ± 0.003 and a foreground early-type galaxy with z = 0.400 ± 0.002.We model the system as a single isothermal ellipsoid and find the Einstein radius θE ∼ 1.47 arcsec, enclosed mass Menc ∼ 4 × 1011 M and a time delay of ∼52 d. The relatively wide separation, month scale time delay duration and high redshift make this an ideal system for constraining the expansion rate beyond a redshift of 1

Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods—ANNZ2, BPZ calibrated against BCC-Ufig simulations, SKYNET, and TPZ—are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z’s. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72 0.01 over the range 0.3 < z < 1.3, we construct three tomographic bins with means of z ¼ f0.45; 0.67; 1.00g. These bins each have systematic uncertainties δz ≲ 0.05 in the mean of the fiducial SKYNET photo-z nðzÞ. We propagate the errors in the redshift distributions through to their impact on cosmological parameters estimated with cosmic shear, and find that they cause shifts in the value of σ8 of approximately 3%. This shift is within the one sigma statistical errors on σ8 for the DES SV shear catalogue. We further study the potential impact of systematic differences on the critical surface density, Σcrit, finding levels of bias safely less than the statistical power of DES SV data. We recommend a final Gaussian prior for the photo-z bias in the mean of nðzÞ of width 0.05 for each of the three tomographic bins, and show that this is a sufficient bias model for the corresponding cosmology analysis

Staging Parkinson’s Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life

Background: Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD). Objective: Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity. Methods: Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort from January 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL: 1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8). Results: Four hundred and thirty-nine PD patients (62.05 +/- 7.84 years old; 59% males) were included. MNCD stage was: stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advanced MNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p < 0.0001) and EUROHIS-QOL8 (p < 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages. Conclusion: Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD

The Dark Energy Survey : more than dark energy – an overview

This overview paper describes the legacy prospect and discovery potential of the Dark Energy Survey (DES) beyond cosmological studies, illustrating it with examples from the DES early data. DES is using a wide-field camera (DECam) on the 4 m Blanco Telescope in Chile to image 5000 sq deg of the sky in five filters (grizY). By its completion, the survey is expected to have generated a catalogue of 300 million galaxies with photometric redshifts and 100 million stars. In addition, a time-domain survey search over 27 sq deg is expected to yield a sample of thousands of Type Ia supernovae and other transients. The main goals of DES are to characterize dark energy and dark matter, and to test alternative models of gravity; these goals will be pursued by studying large-scale structure, cluster counts, weak gravitational lensing and Type Ia supernovae. However, DES also provides a rich data set which allows us to study many other aspects of astrophysics. In this paper, we focus on additional science with DES, emphasizing areas where the survey makes a difference with respect to other current surveys. The paper illustrates, using early data (from ‘Science Verification’, and from the first, second and third seasons of observations), what DES can tell us about the Solar system, the Milky Way, galaxy evolution, quasars and other topics. In addition, we show that if the cosmological model is assumed to be +cold dark matter, then important astrophysics can be deduced from the primary DES probes. Highlights from DES early data include the discovery of 34 trans-Neptunian objects, 17 dwarf satellites of the Milky Way, one published z > 6 quasar (and more confirmed) and two published superluminous supernovae (and more confirmed)

Staging Parkinson’s Disease According to the MNCD (Motor/Non-motor/Cognition/Dependency) Classification Correlates with Disease Severity and Quality of Life

© 2023 – The authors. Published by IOS Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC 4.0).Background: Recently, a novel simple classification called MNCD, based on 4 axes (Motor; Non-motor; Cognition; Dependency) and 5 stages, has been proposed to classify Parkinson's disease (PD).Objective: Our aim was to apply the MNCD classification in a cohort of PD patients for the first time and also to analyze the correlation with quality of life (QoL) and disease severity.Methods: Data from the baseline visit of PD patients recruited from 35 centers in Spain from the COPPADIS cohort fromJanuary 2016 to November 2017 were used to apply the MNCD classification. Three instruments were used to assess QoL:1) the 39-item Parkinson's disease Questionnaire [PDQ-39]); PQ-10; the EUROHIS-QOL 8-item index (EUROHIS-QOL8).Results: Four hundred and thirty-nine PD patients (62.05±7.84 years old; 59% males) were included. MNCD stage was:stage 1, 8.4% (N = 37); stage 2, 62% (N = 272); stage 3, 28.2% (N = 124); stage 4-5, 1.4% (N = 6). A more advancedMNCD stage was associated with a higher score on the PDQ39SI (p < 0.0001) and a lower score on the PQ-10 (p< 0.0001) and EUROHIS-QOL8 (p< 0.0001). In many other aspects of the disease, such as disease duration, levodopa equivalent daily dose, motor symptoms, non-motor symptoms, and autonomy for activities of daily living, an association between the stage and severity was observed, with data indicating a progressive worsening related to disease progression throughout the proposed stages.Conclusion: Staging PD according to the MNCD classification correlated with QoL and disease severity. The MNCD could be a proper tool to monitor the progression of PD.COPPADIS and the present study were developed with the help of Fundación Española de Ayuda a la Investigación en Enfermedades Neurodegenerativas y/o de Origen Genético (https://fundaciondegen.org/) and Alpha Bioresearch (www.alphabioresearch.com). Also, we received grants from the Spanish Ministry of Economy and Competitiveness [PI16/01575] co-founded by ISCIII (Concesión de subvenciones de Proyectos de Investigación en Salud de la convocatoria 2020 de la Acción Estratégica en Salud 2017-2020 por el Proyecto “PROGRESION NO MOTORA E IMPACTO EN LA CALIDAD DE VIDA EN LA ENFERMEDAD DE PARKINSON”) to develop a part of the COPPADIS project.Peer reviewe

DFT exchange: sharing perspectives on the workhorse of quantum chemistry and materials science

In this paper, the history, present status, and future of density-functional theory (DFT) is informally reviewed and discussed by 70 workers in the field, including molecular scientists, materials scientists, method developers and practitioners. The format of the paper is that of a roundtable discussion, in which the participants express and exchange views on DFT in the form of 302 individual contributions, formulated as responses to a preset list of 26 questions. Supported by a bibliography of 777 entries, the paper represents a broad snapshot of DFT, anno 2022

Ectromelia Virus Disease Characterization in the BALB/c Mouse: A Surrogate Model for Assessment of Smallpox Medical Countermeasures

In 2007, the United States– Food and Drug Administration (FDA) issued guidance concerning animal models for testing the efficacy of medical countermeasures against variola virus (VARV), the etiologic agent for smallpox. Ectromelia virus (ECTV) is naturally-occurring and responsible for severe mortality and morbidity as a result of mousepox disease in the murine model, displaying similarities to variola infection in humans. Due to the increased need of acceptable surrogate animal models for poxvirus disease, we have characterized ECTV infection in the BALB/c mouse. Mice were inoculated intranasally with a high lethal dose (125 PFU) of ECTV, resulting in complete mortality 10 days after infection. Decreases in weight and temperature from baseline were observed eight to nine days following infection. Viral titers via quantitative polymerase chain reaction (qPCR) and plaque assay were first observed in the blood at 4.5 days post-infection and in tissue (spleen and liver) at 3.5 days post-infection. Adverse clinical signs of disease were first observed four and five days post-infection, with severe signs occurring on day 7. Pathological changes consistent with ECTV infection were first observed five days after infection. Examination of data obtained from these parameters suggests the ECTV BALB/c model is suitable for potential use in medical countermeasures (MCMs) development and efficacy testing