The Extremes of Thermonuclear Supernovae

The majority of thermonuclear explosions in the Universe seem to proceed in a rather standardised way, as explosions of carbon-oxygen (CO) white dwarfs in binary systems, leading to 'normal' Type Ia supernovae (SNe Ia). However, over the years a number of objects have been found which deviate from normal SNe Ia in their observational properties, and which require different and not seldom more extreme progenitor systems. While the 'traditional' classes of peculiar SNe Ia - luminous '91T-like' and faint '91bg-like' objects - have been known since the early 1990s, other classes of even more unusual transients have only been established 20 years later, fostered by the advent of new wide-field SN surveys such as the Palomar Transient Factory. These include the faint but slowly declining '02es-like' SNe, 'Ca-rich' transients residing in the luminosity gap between classical novae and supernovae, extremely short-lived, fast-declining transients, and the very luminous so-called 'super-Chandrasekhar' SNe Ia. Not all of them are necessarily thermonuclear explosions, but there are good arguments in favour of a thermonuclear origin for most of them. The aim of this chapter is to provide an overview of the zoo of potentially thermonuclear transients, reviewing their observational characteristics and discussing possible explosion scenarios.Comment: Author version of a chapter for the 'Handbook of Supernovae', edited by A. Alsabti and P. Murdin, Springer. 50 pages, 7 figure

A Model for the Detection of Moving Targets in Visual Clutter Inspired by Insect Physiology

We present a computational model for target discrimination based on intracellular recordings from neurons in the fly visual system. Determining how insects detect and track small moving features, often against cluttered moving backgrounds, is an intriguing challenge, both from a physiological and a computational perspective. Previous research has characterized higher-order neurons within the fly brain, known as ‘small target motion detectors’ (STMD), that respond robustly to moving features, even when the velocity of the target is matched to the background (i.e. with no relative motion cues). We recorded from intermediate-order neurons in the fly visual system that are well suited as a component along the target detection pathway. This full-wave rectifying, transient cell (RTC) reveals independent adaptation to luminance changes of opposite signs (suggesting separate ON and OFF channels) and fast adaptive temporal mechanisms, similar to other cell types previously described. From this physiological data we have created a numerical model for target discrimination. This model includes nonlinear filtering based on the fly optics, the photoreceptors, the 1st order interneurons (Large Monopolar Cells), and the newly derived parameters for the RTC. We show that our RTC-based target detection model is well matched to properties described for the STMDs, such as contrast sensitivity, height tuning and velocity tuning. The model output shows that the spatiotemporal profile of small targets is sufficiently rare within natural scene imagery to allow our highly nonlinear ‘matched filter’ to successfully detect most targets from the background. Importantly, this model can explain this type of feature discrimination without the need for relative motion cues

Consumer perceptions of co-branding alliances: Organizational dissimilarity signals and brand fit

This study explores how consumers evaluate co-branding alliances between dissimilar partner firms. Customers are well aware that different firms are behind a co-branded product and observe the partner firms’ characteristics. Drawing on signaling theory, we assert that consumers use organizational characteristics as signals in their assessment of brand fit and for their purchasing decisions. Some organizational signals are beyond the control of the co-branding partners or at least they cannot alter them on short notice. We use a quasi-experimental design and test how co-branding partner dissimilarity affects brand fit perception. The results show that co-branding partner dissimilarity in terms of firm size, industry scope, and country-of-origin image negatively affects brand fit perception. Firm age dissimilarity does not exert significant influence. Because brand fit generally fosters a benevolent consumer attitude towards a co-branding alliance, the findings suggest that high partner dissimilarity may reduce overall co-branding alliance performance

Type Ia Supernovae as Stellar Endpoints and Cosmological Tools

Empirically, Type Ia supernovae are the most useful, precise, and mature tools for determining astronomical distances. Acting as calibrated candles they revealed the presence of dark energy and are being used to measure its properties. However, the nature of the SN Ia explosion, and the progenitors involved, have remained elusive, even after seven decades of research. But now new large surveys are bringing about a paradigm shift --- we can finally compare samples of hundreds of supernovae to isolate critical variables. As a result of this, and advances in modeling, breakthroughs in understanding all aspects of SNe Ia are finally starting to happen.Comment: Invited review for Nature Communications. Final published version. Shortened, update

Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data

Contains fulltext : 89126.pdf (publisher's version ) (Open Access)BACKGROUND: Epistasis is recognized as a fundamental part of the genetic architecture of individuals. Several computational approaches have been developed to model gene-gene interactions in case-control studies, however, none of them is suitable for time-dependent analysis. Herein we introduce the Survival Dimensionality Reduction (SDR) algorithm, a non-parametric method specifically designed to detect epistasis in lifetime datasets. RESULTS: The algorithm requires neither specification about the underlying survival distribution nor about the underlying interaction model and proved satisfactorily powerful to detect a set of causative genes in synthetic epistatic lifetime datasets with a limited number of samples and high degree of right-censorship (up to 70%). The SDR method was then applied to a series of 386 Dutch patients with active rheumatoid arthritis that were treated with anti-TNF biological agents. Among a set of 39 candidate genes, none of which showed a detectable marginal effect on anti-TNF responses, the SDR algorithm did find that the rs1801274 SNP in the Fc gamma RIIa gene and the rs10954213 SNP in the IRF5 gene non-linearly interact to predict clinical remission after anti-TNF biologicals. CONCLUSIONS: Simulation studies and application in a real-world setting support the capability of the SDR algorithm to model epistatic interactions in candidate-genes studies in presence of right-censored data. Availability: http://sourceforge.net/projects/sdrproject/

Histoplasmosis infection in patients with rheumatoid arthritis, 1998-2009

<p>Abstract</p> <p>Background</p> <p>Patients with rheumatic diseases including rheumatoid arthritis (RA) are at increased risk for infections related to both the disease and its treatments. These include uncommonly reported infections due to histoplasmosis.</p> <p>Methods</p> <p>Medical record review of all patients with a diagnosis of RA who developed new histoplasmosis infection in an endemic region between Jan 1, 1998 and Jan 30, 2009 and who were seen at Mayo Clinic in Rochester, Minnesota was performed.</p> <p>Results</p> <p>Histoplasmosis was diagnosed in 26 patients. Most patients were on combination therapies; 15 were on anti-tumor necrosis factor (anti-TNF) agents, 15 on corticosteroids and 16 on methotrexate. Most received more than 6 months of itraconazole and/or amphotericin treatment. Two patients died of causes unrelated to histoplasmosis. Anti-TNF treatment was restarted in 4/15 patients, with recurrence of histoplasmosis in one.</p> <p>Conclusions</p> <p>In this largest single center series of patients with RA and histoplasmosis in the era of immunomodulatory therapy, we found that most patients had longstanding disease and were on multiple immunomodulatory agents. Most cases were pulmonary; typical signs and symptoms of disease were frequently lacking.</p

Sphingosine-1-phosphate attenuates proteoglycan aggrecan expression via production of prostaglandin E(2 )from human articular chondrocytes

BACKGROUND: Sphingosine-1-phosphate (S1P), a downstream metabolite of ceramide, induces various bioactivities via two distinct pathways: as an intracellular second messenger or through receptor activation. The receptor for S1P (S1PR) is the family of Endothelial differentiation, sphingolipid G-protein-coupled receptor (EDG). We have here attempted to reveal the expression of EDG/S1PR in human articular chondrocytes (HAC), exploring the implications of S1P in cartilage degradation. METHODS: Articular cartilage specimens were obtained from patients with rheumatoid arthritis (RA), osteoarthritis (OA) or traumatic fracture (representing normal chondrocytes) who underwent joint surgery. Isolated HAC were cultured in vitro by monolayer and stimulated with S1P in the presence or absence of inhibitors of signaling molecules. Stimulated cells and culture supernatants were collected and subjected to analyses using reverse transcription-polymerase chain reaction (RT-PCR), Western blotting, and enzyme-linked immunosorbent assay (ELISA). RESULTS: All of the tested HAC samples showed positive results in terms of EDG/S1PR expression in basal condition. When HAC was stimulated with S1P, a significant increase in prostaglandin (PG) E(2 )production was observed together with enhanced expression of cyclooxygenase (COX)-2. S1P stimulated extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinase (MAPK) in HAC, and the PGE(2 )induction was abrogated by PD98059 and SB203580. Pertussis toxin inhibited the PGE(2 )induction from HAC by S1P, suggesting an essential role for Gi protein. S1P also attenuated the expression of proteoglycan aggrecan, a component of cartilage matrix, in HAC at transcriptional level. CONCLUSION: It was suggested that the S1P-induced PGE(2 )was at least in part involved in the aggrecan-suppressing effect of S1P, seeing as COX inhibitors attenuated the effect. Accordingly, S1P might play an important role in cartilage degradation in arthritides