RUNX1: an emerging therapeutic target for cardiovascular disease

Runt-related transcription factor-1 (RUNX1), also known as acute myeloid leukaemia 1 protein (AML1), is a member of the core-binding factor family of transcription factors which modulate cell proliferation, differentiation, and survival in multiple systems. It is a master-regulator transcription factor, which has been implicated in diverse signalling pathways and cellular mechanisms during normal development and disease. RUNX1 is best characterized for its indispensable role for definitive haematopoiesis and its involvement in haematological malignancies. However, more recently RUNX1 has been identified as a key regulator of adverse cardiac remodelling following myocardial infarction. This review discusses the role RUNX1 plays in the heart and highlights its therapeutic potential as a target to limit the progression of adverse cardiac remodelling and heart failure

The High-Mass End of the Red Sequence at z~0.55 from SDSS-III/BOSS: completeness, bimodality and luminosity function

We have developed an analytical method based on forward-modeling techniques to characterize the high-mass end of the red sequence (RS) galaxy population at redshift $z\sim0.55$, from the DR10 BOSS CMASS spectroscopic sample, which comprises $\sim600,000$ galaxies. The method, which follows an unbinned maximum likelihood approach, allows the deconvolution of the intrinsic CMASS colour-colour-magnitude distributions from photometric errors and selection effects. This procedure requires modeling the covariance matrix for the i-band magnitude, g-r colour and r-i colour using Stripe 82 multi-epoch data. Our results indicate that the error-deconvolved intrinsic RS distribution is consistent, within the photometric uncertainties, with a single point ($<0.05~{\rm{mag}}$) in the colour-colour plane at fixed magnitude, for a narrow redshift slice. We have computed the high-mass end ($^{0.55}M_i \lesssim -22$) of the $^{0.55}i$-band RS Luminosity Function (RS LF) in several redshift slices within the redshift range $0.52<z<0.63$. In this narrow redshift range, the evolution of the RS LF is consistent, within the uncertainties in the modeling, with a passively-evolving model with $\Phi_* = (7.248 \pm 0.204) \times10^{-4}$ Mpc$^{-3}$ mag$^{-1}$, fading at a rate of $1.5\pm0.4$ mag per unit redshift. We report RS completeness as a function of magnitude and redshift in the CMASS sample, which will facilitate a variety of galaxy-evolution and clustering studies using BOSS. Our forward-modeling method lays the foundations for future studies using other dark-energy surveys like eBOSS or DESI, which are affected by the same type of photometric blurring/selection effects.Comment: 27 pages, 20 figures, accepted for publication in MNRA

Conceptualisations of children’s wellbeing at school: the contribution of recognition theory

A large study in Australian schools aimed to elucidate understandings of ‘wellbeing’ and of factors in school life that contribute to it. Students and teachers understood wellbeing primarily, and holistically, in terms of interpersonal relationships, in contrast to policy documents which mainly focused on ‘problem areas’ such as mental health. The study also drew on recognition theory as developed by the social philosopher Axel Honneth. Results indicate that recognition theory may be useful in understanding wellbeing in schools, and that empirical research in schools may give rise to further questions regarding theory

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: measuring structure growth using passive galaxies

We explore the benefits of using a passively evolving population of galaxies to measure the evolution of the rate of structure growth between z=0.25 and z=0.65 by combining data from the SDSS-I/II and SDSS-III surveys. The large-scale linear bias of a population of dynamically passive galaxies, which we select from both surveys, is easily modeled. Knowing the bias evolution breaks degeneracies inherent to other methodologies, and decreases the uncertainty in measurements of the rate of structure growth and the normalization of the galaxy power-spectrum by up to a factor of two. If we translate our measurements into a constraint on sigma_8(z=0) assuming a concordance cosmological model and General Relativity (GR), we find that using a bias model improves our uncertainty by a factor of nearly 1.5. Our results are consistent with a flat Lambda Cold Dark Matter model and with GR.Comment: Accepted for publication in MNRAS (clarifications added, results and conclusions unchanged

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey : cosmological implications of the full shape of the clustering wedges in the data release 10 and 11 galaxy samples

We explore the cosmological implications of the angle-averaged correlation function, ξ(s), and the clustering wedges, ξ⊥(s) and ξ∥(s), of the LOWZ and CMASS galaxy samples from Data Releases 10 and 11 of the Sloan Digital Sky Survey III (SDSS-III) Baryon Oscillation Spectroscopic Survey. Our results show no significant evidence for a deviation from the standard Λ cold dark matter model. The combination of the information from our clustering measurements with recent data from the cosmic microwave background is sufficient to constrain the curvature of the Universe to Ωk = 0.0010 ± 0.0029, the total neutrino mass to ∑mν < 0.23 eV (95 per cent confidence level), the effective number of relativistic species to Neff = 3.31 ± 0.27 and the dark energy equation of state to wDE = −1.051 ± 0.076. These limits are further improved by adding information from Type Ia supernovae and baryon acoustic oscillations from other samples. In particular, this data set combination is completely consistent with a time-independent dark energy equation of state, in which case we find wDE = −1.024 ± 0.052. We explore the constraints on the growth rate of cosmic structures assuming f(z) = Ωm(z)γ and obtain γ = 0.69 ± 0.15, consistent with the predictions of general relativity of γ = 0.55.Publisher PDFPeer reviewe

Tropical cyclones and climate change

Recent research has strengthened the understanding of the links between climate and tropical cyclones (TCs) on various timescales. Geological records of past climates have shown century-long variations in TC numbers. While no significant trends have been identified in the Atlantic since the late 19th century, significant observed trends in TC numbers and intensities have occurred in this basin over the past few decades, and trends in other basins are increasingly being identified. However, understanding of the causes of these trends is incomplete, and confidence in these trends continues to be hampered by a lack of consistent observations in some basins. A theoretical basis for maximum TC intensity appears now to be well established, but a climate theory of TC formation remains elusive. Climate models mostly continue to predict future decreases in global TC numbers, projected increases in the intensities of the strongest storms and increased rainfall rates. Sea level rise will likely contribute toward increased storm surge risk. Against the background of global climate change and sea level rise, it is important to carry out quantitative assessments on the potential risk of TC-induced storm surge and flooding to densely populated cities and river deltas. Several climate models are now able to generate a good distribution of both TC numbers and intensities in the current climate. Inconsistent TC projection results emerge from modeling studies due to different downscaling methodologies and warming scenarios, inconsistencies in projected changes of large-scale conditions, and differences in model physics and tracking algorithms