The use of otolith morphology to indicate the stock structure of common coral trout (Plectropomus leopardus) on the Great Barrier Reef, Australia

We investigated the use of otolith morphology to indicate the stock structure of an exploited serranid coral reef fish, Plectropomus leopardus, on the Great Barrier Reef (GBR), Australia. Otoliths were measured by traditional one-and two-dimensional measures (otolith length, width, area, perimeter, circularity, and rectangularity), as well as by Fourier analysis to capture the finer details of otolith shape. Variables were compared among four regions of the GBR separated by hundreds of kilometers, as well as among three reefs within each region, hundreds of meters to tens of kilometers apart. The temporal stability in otolith structure was examined by comparing two cohorts of fully recruited four-year-old P. leopardus collected two years before and two years after a signif icant disturbance in the southern parts of the GBR caused by a large tropical cyclone in March 1997. Results indicated the presence of at least two stocks of P. leopardus, although the structure of each stock varied depending on the cohort considered. The results highlight the importance of incorporating data from several years in studies using otolith morphology to discriminate temporary and possibly misleading signals from those that indicate persistent spatial structure in stocks. We conclude that otolith morphology can be used as an initial step to direct further research on groups of P. leopardus that have lived at least a part of their life in different environments

Demographic characteristics of exploited tropical lutjanids: a comparative analysis

Demographic parameters from seven exploited coral reef lutjanid species were compared as a case study of the implications of intrafamily variation in life histories for multispecies harvest management. Modal lengths varied by 4 cm among four species (Lutjanus fulviflamma, L. vitta, L. carponotatus, L. adetii), which were at least 6 cm smaller than the modal lengths of the largest species (L. gibbus, Symphorus nematophorus, Aprion virescens). Modal ages, indicating ages of full selection to fishing gear, were 10 years or less for all species, but maximum ages ranged from 12 (L. gibbus) to 36 years (S. nematophorus). Each species had a unique growth pattern, with differences in length-at-age and mean asymptotic fork length (L∞), but smaller species generally grew fast during the first 1–2 years of life and larger species grew more slowly over a longer period. Total mortality rates varied among species; L. gibbus had the highest mortality and L. fulviflamma, the lowest mortality. The variability in life history strategies of these tropical lutjanids makes generalizations about lutjanid life histories difficult, but the fact that all seven had characteristics that would make them particularly vulnerable to fishing indicates that harvest of tropical lutjanids should be managed with caution

Metabolic correlates of prevalent mild cognitive impairment and Alzheimer's disease in adults with Down syndrome.

IntroductionDisruption of metabolic function is a recognized feature of late onset Alzheimer's disease (LOAD). We sought to determine whether similar metabolic pathways are implicated in adults with Down syndrome (DS) who have increased risk for Alzheimer's disease (AD).MethodsWe examined peripheral blood from 292 participants with DS who completed baseline assessments in the Alzheimer's Biomarkers Consortium-Down Syndrome (ABC-DS) using untargeted mass spectrometry (MS). Our sample included 38 individuals who met consensus criteria for AD (DS-AD), 43 who met criteria for mild cognitive impairment (DS-MCI), and 211 who were cognitively unaffected and stable (CS).ResultsWe measured relative abundance of 8,805 features using MS and 180 putative metabolites were differentially expressed (DE) among the groups at false discovery rate-corrected q< 0.05. From the DE features, a nine-feature classifier model classified the CS and DS-AD groups with receiver operating characteristic area under the curve (ROC AUC) of 0.86 and a two-feature model classified the DS-MCI and DS-AD groups with ROC AUC of 0.88. Metabolite set enrichment analysis across the three groups suggested alterations in fatty acid and carbohydrate metabolism.DiscussionOur results reveal metabolic alterations in DS-AD that are similar to those seen in LOAD. The pattern of results in this cross-sectional DS cohort suggests a dynamic time course of metabolic dysregulation which evolves with clinical progression from non-demented, to MCI, to AD. Metabolomic markers may be useful for staging progression of DS-AD

Integrating communication skills into undergraduate science degrees: A practical and evidence-based approach

The introduction of generic skills, such as communication, into undergraduate science degrees is becoming common in higher education and has met with mixed implementation success. This study designed, piloted, and evaluated a set of adaptable activities that scaffold the explicit teaching and learning of science communication with non-scientific audiences. These activities were implemented in undergraduate science classes from three disciplines at an Australian research-intensive university. A mixed- methods approach was used to evaluate learning gains by collecting data from: student surveys; semi-structured interviews with academic teaching staff; and student performance by marking of assessment tasks. Self-reported learning gains showed 95% of all students perceived improvements in their ability to do all communication skills and 94% perceived improvements in their confidence in communicating science as a result of the activities. Academic teaching staff reported improvements in students’ communication skills and understanding of core science content, and indicated that the tasks were explicit, engaging, and sustainable for use in future years. Students successfully transferred their learning to their assignments, demonstrating on average, a ‘good,’ ‘excellent,’ or ‘outstanding’ standard for each of the science communication criteria. These activities provide a promising starting point for integrating employable communication skills into undergraduate science degrees

Epidemiology and outcomes from out-of-hospital cardiac arrests in England

Introduction This study reports the epidemiology and outcomes from out-of-hospital cardiac arrest (OHCA) in England during 2014. Methods Prospective observational study from the national OHCA registry. The incidence, demographic and outcomes of patients who were treated for an OHCA between 1st January 2014 and 31st December 2014 in 10 English ambulance service (EMS) regions, serving a population of almost 54 million, are reported in accordance with Utstein recommendations. Results 28,729 OHCA cases of EMS treated cardiac arrests were reported (53 per 100,000 of resident population). The mean age was 68.6 (SD = 19.6) years and 41.3% were female. Most (83%) occurred in a place of residence, 52.7% were witnessed by either the EMS or a bystander. In non-EMS witnessed cases, 55.2% received bystander CPR whilst public access defibrillation was used rarely (2.3%). Cardiac aetiology was the leading cause of cardiac arrest (60.9%). The initial rhythm was asystole in 42.4% of all cases and was shockable (VF or pVT) in 20.6%. Return of spontaneous circulation at hospital transfer was evident in 25.8% (n = 6302) and survival to hospital discharge was 7.9%. Conclusion Cardiac arrest is an important cause of death in England. With less than one in ten patients surviving, there is scope to improve outcomes. Survival rates were highest amongst those who received bystander CPR and public access defibrillation

Spatial and fishing effects on sampling gear biases in a tropical reef line fishery

Biased estimates of population parameters for harvested stocks can have severe implications for fishery management strategy choices. Hook-and-line fishing gear is size-selective and therefore collects biased samples from wild populations. Such biases may also vary in space and time. To assess this assertion, we compared line- and spear-caught samples of the main target species of an Australian hook-and-line fishery to quantify relative bias in size and age structure estimates. We also assessed the consistency of biases among four fishery regions and between two management zones – areas open and closed to fishing. Fish less than 310 mm and younger than 4 years comprised a larger proportion of the speared than the line samples regardless of region or management zone. Conversely, hook-and-line sampled more fish in larger size classes (>370 mm) and older age classes (≥6 years) relative to spear fishing. These biases were qualitatively, but not quantitatively, consistent in all regions and management zones. This variation in sampling resulted in different inferences about regional and zone-related patterns in population size and age structure. We recommend careful consideration of sampling bias when drawing conclusions about regional and management zone effects on fish populations

Lateral specialization in unilateral spatial neglect : a cognitive robotics model

In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilateral spatial neglect (USN). To this end, we introduce an artificial neural network architecture designed and trained to control the spatial attentional focus of the iCub robotic platform. Like the human brain, the architecture is divided into two hemispheres and it incorporates bio-inspired plasticity mechanisms, which allow the development of the phenomenon of the specialization of the right hemisphere for spatial attention. In this study, we validate the model by replicating a previous experiment with human patients affected by the USN and numerical results show that the robot mimics the behaviours previously exhibited by humans. We also simulated recovery after the damage to compare the performance of each of the two hemispheres as additional validation of the model. Finally, we highlight some possible advantages of modelling cognitive dysfunctions of the human brain by means of robotic platforms, which can supplement traditional approaches for studying spatial impairments in humans

Cyanobacteria and microalgae in supporting human habitation on Mars

Establishing the first human presence on Mars will be the most technically challenging undertaking yet in the exploration beyond our planet. The remoteness of Mars from Earth, the inhospitable surface conditions including low atmospheric pressure and cold temperatures, and the need for basic resources including water, pose a formidable challenge to this endeavour. The intersection of multiple disciplines will be required to provide solutions for temporary and eventually permanent Martian habitation. This review considers the role cyanobacteria and eukaryotic microalgae (collectively referred to here as ‘microalgae’) may have in supporting missions to the red planet. The current research using these microorganisms in biological life support systems is discussed, with a systematic analysis of their usage in each system conducted. The potential of microalgae to provide astronauts with oxygen, food, bio-polymers and pharmaceuticals is considered. An overview of microalgal experiments in space missions across the last 60 years is presented, and the research exploring the technical challenges of cultivation on Mars is discussed. From these findings, an argument for culturing microalgae in subterranean bioreactors is proposed. Finally, future synthetic biology approaches for enhancing the cyanobacterial/microalgal role in supporting human deep-space exploration are presented. We show that microalgae hold significant promise for providing solutions to many problems faced by the first Martian settlers, however these can only be realised with significant infrastructure and a reliable power source

ADA: an open-source software platform for plotting and analysis of data from laboratory photobioreactors

Algal biotechnology has received significant attention over the past two decades in fields ranging from biofuels to cosmeceuticals. However, the development of domesticated or genetically engineered microalgal strains for commercial applications depends on accurate and reliable growth data. To this end, several companies have developed lab-scale photobioreactors (PBRs) that enable precision control of conditions and automated growth recording. Whilst the transition from manual control of conditions and measurements to automated systems has allowed researchers to greatly improve the accuracy and scope of cultivation experiments, it has also presented novel challenges. The most pertinent of these being the analysis of the copious quantities of data produced. A standard PBR experiment can contain tens or even hundreds of thousands of data points, and often features outliers, noise, and a requirement for datasets to be calibrated with a standard curve or merged with replicates. Furthermore, complex analysis of multiple curves may be required in order to extract information such as the gradient or fit to a growth model. This can be laborious, time consuming and is not standardized between research groups. Proprietary software provided with most PBRs tends to lack these more advanced features and is typically unable to process data from other PBR manufacturers. To address these issues, we have developed the Algal Data Analyser (ADA), an open-source software platform providing the tools to rapidly plot and analyse microalgal data. ADA can simultaneously interpret datasets from three major PBR suppliers (Algenuity, Industrial Plankton, Photon Systems Instruments), and can also incorporate data from manual readings. Users can rapidly produce standardized, publication ready plots, and analyse multiple growth curves in parallel. Future iterations of ADA will include compatibility with datasets from other PBR suppliers as they become available, with the aim of making it a universal platform for all PBR data