University of Queensland

About: University of Queensland is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 51138 authors who have published 155721 publications receiving 5717659 citations. The organization is also known as: UQ & The University of Queensland.

Galaxy and Mass Assembly (GAMA): survey diagnostics and core data release

Abstract: The Galaxy and Mass Assembly (GAMA) survey has been operating since 2008 February on the 3.9-m Anglo-Australian Telescope using the AAOmega fibre-fed spectrograph facility to acquire spectra with a resolution of R ≈ 1300 for 120 862 Sloan Digital Sky Survey selected galaxies. The target catalogue constitutes three contiguous equatorial regions centred at 9h (G09), 12h (G12) and 14.5h (G15) each of 12 × 4 deg2 to limiting fluxes of rpet < 19.4, rpet < 19.8 and rpet <19.4 mag, respectively (and additional limits at other wavelengths). Spectra and reliable redshifts have been acquired for over 98 per cent of the galaxies within these limits. Here we present the survey footprint, progression, data reduction, redshifting, re-redshifting, an assessment of data quality after 3 yr, additional image analysis products (including ugrizYJHK photometry, S´ersic profiles and photometric redshifts), observing mask and construction of our core survey catalogue (GamaCore). From this we create three science-ready catalogues: GamaCoreDR1 for public release, which includes data acquired during year 1 of operations within specified magnitude limits (2008 February to April); GamaCoreMainSurvey containing all data above our survey limits for use by the GAMA Team and collaborators; and GamaCore-AtlasSV containing year 1, 2 and 3 data matched to Herschel-ATLAS science demonstration data. These catalogues along with the associated spectra, stamps and profiles can be accessed via the GAMA website: http://www.gama-survey.org/

Non‐coding RNAs: regulators of disease

Abstract: For 50 years the term 'gene' has been synonymous with regions of the genome encoding mRNAs that are translated into protein. However, recent genome-wide studies have shown that the human genome is pervasively transcribed and produces many thousands of regulatory non-protein-coding RNAs (ncRNAs), including microRNAs, small interfering RNAs, PIWI-interacting RNAs and various classes of long ncRNAs. It is now clear that these RNAs fulfil critical roles as transcriptional and post-transcriptional regulators and as guides of chromatin-modifying complexes. Here we review the biology of ncRNAs, focusing on the fundamental mechanisms by which ncRNAs facilitate normal development and physiology and, when dysfunctional, underpin disease. We also discuss evidence that intergenic regions associated with complex diseases express ncRNAs, as well as the potential use of ncRNAs as diagnostic markers and therapeutic targets. Taken together, these observations emphasize the need to move beyond the confines of protein-coding genes and highlight the fact that continued investigation of ncRNA biogenesis and function will be necessary for a comprehensive understanding of human disease.

The training—injury prevention paradox: should athletes be training smarter and harder?

Abstract: Background There is dogma that higher training load causes higher injury rates. However, there is also evidence that training has a protective effect against injury. For example, team sport athletes who performed more than 18 weeks of training before sustaining their initial injuries were at reduced risk of sustaining a subsequent injury, while high chronic workloads have been shown to decrease the risk of injury. Second, across a wide range of sports, well-developed physical qualities are associated with a reduced risk of injury. Clearly, for athletes to develop the physical capacities required to provide a protective effect against injury, they must be prepared to train hard. Finally, there is also evidence that under-training may increase injury risk. Collectively, these results emphasise that reductions in workloads may not always be the best approach to protect against injury. Main thesis This paper describes the ‘Training-Injury Prevention Paradox’ model; a phenomenon whereby athletes accustomed to high training loads have fewer injuries than athletes training at lower workloads. The Model is based on evidence that non-contact injuries are not caused by training per se , but more likely by an inappropriate training programme. Excessive and rapid increases in training loads are likely responsible for a large proportion of non-contact, soft-tissue injuries. If training load is an important determinant of injury, it must be accurately measured up to twice daily and over periods of weeks and months (a season). This paper outlines ways of monitoring training load (‘internal’ and ‘external’ loads) and suggests capturing both recent (‘acute’) training loads and more medium-term (‘chronic’) training loads to best capture the player's training burden. I describe the critical variable—acute:chronic workload ratio—as a best practice predictor of training-related injuries. This provides the foundation for interventions to reduce players risk, and thus, time-loss injuries. Summary The appropriately graded prescription of high training loads should improve players’ fitness, which in turn may protect against injury, ultimately leading to (1) greater physical outputs and resilience in competition, and (2) a greater proportion of the squad available for selection each week.

The Amphimedon queenslandica genome and the evolution of animal complexity

Abstract: Sponges are an ancient group of animals that diverged from other metazoans over 600 million years ago. Here we present the draft genome sequence of Amphimedon queenslandica, a demosponge from the Great Barrier Reef, and show that it is remarkably similar to other animal genomes in content, structure and organization. Comparative analysis enabled by the sequencing of the sponge genome reveals genomic events linked to the origin and early evolution of animals, including the appearance, expansion and diversification of pan-metazoan transcription factor, signalling pathway and structural genes. This diverse ‘toolkit’ of genes correlates with critical aspects of all metazoan body plans, and comprises cell cycle control and growth, development, somatic- and germ-cell specification, cell adhesion, innate immunity and allorecognition. Notably, many of the genes associated with the emergence of animals are also implicated in cancer, which arises from defects in basic processes associated with metazoan multicellularity.