Galactic and Extragalactic Samples of Supernova Remnants: How They Are Identified and What They Tell Us

Supernova remnants (SNRs) arise from the interaction between the ejecta of a supernova (SN) explosion and the surrounding circumstellar and interstellar medium. Some SNRs, mostly nearby SNRs, can be studied in great detail. However, to understand SNRs as a whole, large samples of SNRs must be assembled and studied. Here, we describe the radio, optical, and X-ray techniques which have been used to identify and characterize almost 300 Galactic SNRs and more than 1200 extragalactic SNRs. We then discuss which types of SNRs are being found and which are not. We examine the degree to which the luminosity functions, surface-brightness distributions and multi-wavelength comparisons of the samples can be interpreted to determine the class properties of SNRs and describe efforts to establish the type of SN explosion associated with a SNR. We conclude that in order to better understand the class properties of SNRs, it is more important to study (and obtain additional data on) the SNRs in galaxies with extant samples at multiple wavelength bands than it is to obtain samples of SNRs in other galaxiesComment: Final 2016 draft of a chapter in "Handbook of Supernovae" edited by Athem W. Alsabti and Paul Murdin. Final version available at https://doi.org/10.1007/978-3-319-20794-0_90-

How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?

Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition

Photodynamic Therapy Can Induce a Protective Innate Immune Response against Murine Bacterial Arthritis via Neutrophil Accumulation

Background: Local microbial infections induced by multiple-drug-resistant bacteria in the orthopedic field can be intractable, therefore development of new therapeutic modalities is needed. Photodynamic therapy (PDT) is a promising alternative modality to antibiotics for intractable microbial infections, and we recently reported that PDT has the potential to accumulate neutrophils into the infected site which leads to resolution of the infection. PDT for cancer has long been known to be able to stimulate the innate and adaptive arms of the immune system. Methodology/Principal Findings: In the present study, a murine methicillin-resistant Staphylococcus aureus (MRSA) arthritis model using bioluminescent MRSA and polystyrene microparticles was established, and both the therapeutic (Th-PDT) and preventive (Pre-PDT) effects of PDT using methylene blue as photosensitizer were examined. Although Th-PDT could not demonstrate direct bacterial killing, neutrophils were accumulated into the infectious joint space after PDT and MRSA arthritis was reduced. With the preconditioning Pre-PDT regimen, neutrophils were quickly accumulated into the joint immediately after bacterial inoculation and bacterial growth was suppressed and the establishment of infection was inhibited. Conclusions/Significance: This is the first demonstration of a protective innate immune response against a bacterial pathogen produced by PDT.National Institutes of Health (U.S.) (Grant number R01AI050875

Area deprivation and its association with health in a cross-sectional study: are the results biased by recent migration?

<p>Abstract</p> <p>Background</p> <p>The association between area deprivation and health has mostly been examined in cross-sectional studies or prospective studies with short follow-up. These studies have rarely taken migration into account. This is a possible source of misclassification of exposure, i.e. an unknown number of study participants are attributed an exposure of area deprivation that they may have experienced too short for it to have any influence. The aim of this article was to examine to what extent associations between area deprivation and health outcomes were biased by recent migration.</p> <p>Methods</p> <p>Based on data from the Oslo Health Study, a cross-sectional study conducted in 2000 in Oslo, Norway, we used six health outcomes (self rated health, mental health, coronary heart disease, chronic obstructive pulmonary disease, smoking and exercise) and considered migration nine years prior to the study conduct. Migration into Oslo, between the areas of Oslo, and the changes in area deprivation during the period were taken into account. Associations were investigated by multilevel logistic regression analyses.</p> <p>Results</p> <p>After adjustment for individual socio-demographic variables we found significant associations between area deprivation and all health outcomes. Accounting for migration into Oslo and between areas of Oslo did not change these associations much. However, the people who migrated into Oslo were younger and had lower prevalences of unfavourable health outcomes than those who were already living in Oslo. But since they were evenly distributed across the area deprivation quintiles, they had little influence on the associations between area deprivation and health. Evidence of selective migration within Oslo was weak, as both moving up and down in the deprivation hierarchy was associated with significantly worse health than not moving.</p> <p>Conclusion</p> <p>We have documented significant associations between area deprivation and health outcomes in Oslo after adjustment for socio-demographic variables in a cross-sectional study. These associations were weakly biased by recent migration. From our results it still appears that migration prior to study conduct may be relevant to investigate even within a relatively short period of time, whereas changes in area deprivation during such a period is of limited interest.</p

Production of dust by massive stars at high redshift

The large amounts of dust detected in sub-millimeter galaxies and quasars at high redshift pose a challenge to galaxy formation models and theories of cosmic dust formation. At z > 6 only stars of relatively high mass (> 3 Msun) are sufficiently short-lived to be potential stellar sources of dust. This review is devoted to identifying and quantifying the most important stellar channels of rapid dust formation. We ascertain the dust production efficiency of stars in the mass range 3-40 Msun using both observed and theoretical dust yields of evolved massive stars and supernovae (SNe) and provide analytical expressions for the dust production efficiencies in various scenarios. We also address the strong sensitivity of the total dust productivity to the initial mass function. From simple considerations, we find that, in the early Universe, high-mass (> 3 Msun) asymptotic giant branch stars can only be dominant dust producers if SNe generate <~ 3 x 10^-3 Msun of dust whereas SNe prevail if they are more efficient. We address the challenges in inferring dust masses and star-formation rates from observations of high-redshift galaxies. We conclude that significant SN dust production at high redshift is likely required to reproduce current dust mass estimates, possibly coupled with rapid dust grain growth in the interstellar medium.Comment: 72 pages, 9 figures, 5 tables; to be published in The Astronomy and Astrophysics Revie

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC