The massive binary companion star to the progenitor of supernova 1993J

The massive star that underwent a collapse of its core to produce supernova (SN)1993J was subsequently identified as a non-variable red supergiant star in images of the galaxy M81 taken before explosion(1, 2). It showed an excess in ultraviolet and B-band colours, suggesting either the presence of a hot, massive companion star or that it was embedded in an unresolved young stellar association1. The spectra of SN1993J underwent a remarkable transformation from the signature of a hydrogen-rich type II supernova to one of a helium-rich (hydrogen-deficient) type Ib(3, 4). The spectral and photometric peculiarities were best explained by models in which the 13�20 solar mass supergiant had lost almost its entire hydrogen envelope to a close binary companion(5, 6, 7), producing a 'type IIb' supernova, but the hypothetical massive companion stars for this class of supernovae have so far eluded discovery. Here we report photometric and spectroscopic observations of SN1993J ten years after the explosion. At the position of the fading supernova we detect the unambiguous signature of a massive star: the binary companion to the progenitor.

Luminous blue variables as the progenitors of supernovae with quasi-periodic radio modulations

The interaction between supernova ejecta and circumstellar matter, arising from previous episodes of mass loss, provides us with a means of constraining the progenitors of supernovae. Radio observations of a number of supernovae show quasi-periodic deviations from a strict power-law decline at late times. Although several possibilities have been put forward to explain these modulations, no single explanation has proven to be entirely satisfactory. Here we suggest that Luminous blue variables undergoing S-Doradus type variations give rise to enhanced phases of mass loss that are imprinted on the immediate environment of the exploding star as a series of density enhancements. The variations in mass loss arise from changes in the ionization balance of Fe, the dominant ion that drives the wind. With this idea, we find that both the recurrence timescale of the variability and the amplitude of the modulations are in line with the observations. Our scenario thus provides a natural, single-star explanation for the observed behaviour that is, in fact, expected on theoretical grounds.

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Abstract: Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R-2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (>= 2 double bonds per chain) was also well predicted with R-2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R-2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R-2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

Individual mRNA expression profiles reveal the effects of specific microRNAs

BACKGROUND: MicroRNAs (miRNAs) are oligoribonucleotides with an important role in regulation of gene expression at the level of translation. Despite imperfect target complementarity, they can also significantly reduce mRNA levels. The validity of miRNA target gene predictions is difficult to assess at the protein level. We sought, therefore, to determine whether a general lowering of predicted target gene mRNA expression by endogenous miRNAs was detectable within microarray gene expression profiles. RESULTS: The target gene sets predicted for each miRNA were mapped onto known gene expression data from a range of tissues. Whether considering mean absolute target gene expression, rank sum tests or 'ranked ratios', many miRNAs with significantly reduced target gene expression corresponded to those known to be expressed in the cognate tissue. Expression levels of miRNAs with reduced target mRNA levels were higher than those of miRNAs with no detectable effect on mRNA expression. Analysis of microarray data gathered after artificial perturbation of expression of a specific miRNA confirmed the predicted increase or decrease in influence of the altered miRNA upon mRNA levels. Strongest associations were observed with targets predicted by TargetScan. CONCLUSION: We have demonstrated that the effect of a miRNA on its target mRNAs' levels can be measured within a single gene expression profile. This emphasizes the extent of this mode of regulation in vivo and confirms that many of the predicted miRNA-mRNA interactions are correct. The success of this approach has revealed the vast potential for extracting information about miRNA function from gene expression profiles.

Individual trade-offs between nutrition and risk of interspecific transmission of disease by grazing: cows, badger latrines and bovine tuberculosis

1. We examine whether various measures of herbivore current physiological state (age, breeding and immune status) and genetic potential can be used as indicators of exposure to and risk from disease. We use dairy cattle and the risks of tuberculosis (TB) transmission posed to them by pasture contaminated with badger excreta (via the fecal-oral route) as a model system to address our aim.

Algal epiphytes of Zostera marina: Variation in assemblage structure from individual leaves to regional scale

Data from a hierarchical study of four Zostera marina beds in Wales were used to identify the spatial scales of variation in epiphyte assemblages. There were significant within and among bed differences in assemblage structure. The differences in assemblage structure with spatial scale generally persisted when species identifications were aggregated into functional groups. There was also significant within and among bed variability in Zostera density and average length. Local variations in Zostera canopy variables at the quadrat scale (total leaf length, average leaf length and leaf density per quadrat) were not related to epiphyte species richness nor to the structure of the assemblage. In contrast, individual leaf length was significantly related to species richness in two of the beds and the structure of epiphyte assemblages was always related to individual leaf lengths. The absence of links between quadrat scale measurements of canopy variables and assemblage structure may reflect the high turnover of individual Zostera leaves. Experimental work is required to discriminate further between the potential causes of epiphyte assemblage variation within and between beds. No bed represented a refuge where a rare species was abundant. If a species was uncommon at the bed scale, it was also uncommon in beds where it occurred. The heterogeneous assemblages found in this study suggest that a precautionary approach to conservation is advisable.