Potential for adaptation in response to thermal stress in an intertidal macroalga

Understanding responses of marine algae to changing ocean temperatures requires knowledge of the impacts of elevated temperatures and the likelihood of adaptation to thermal stress. The potential for rapid evolution of thermal tolerance is dependent on the levels of heritable genetic variation in response to thermal stress within a population. Here, we use a quantitative genetic breeding design to establish whether there is a heritable variation in thermal sensitivity in two populations of a habitat-forming intertidal macroalga, Hormosira banksii (Turner) Descaisne. Gametes from multiple parents were mixed and growth and photosynthetic performance were measured in the resulting embryos, which were incubated under control and elevated temperature (20°C and 28°C). Embryo growth was reduced at 28°C, but significant interactions between male genotype and temperature in one population indicated the presence of genetic variation in thermal sensitivity. Selection for more tolerant genotypes thus has the ability to result in the evolution of increased thermal tolerance. Furthermore, genetic correlations between embryos grown in the two temperatures were positive, indicating that those genotypes that performed well in elevated temperature also performed well in control temperature. Chlorophyll a fluorescence measurements showed a marked decrease in maximum quantum yield of photosystem II (PSII) under elevated temperature. There was an increase in the proportion of energy directed to photoinhibition (nonregulated nonphotochemical quenching) and a concomitant decrease in energy used to drive photochemistry and xanthophyll cycling (regulated nonphotochemical quenching). However, PSII performance between genotypes was similar, suggesting that thermal sensitivity is related to processes other than photosynthesis. © 2013 Phycological Society of America

Evidence from Individual Inference for High-Dimensional Coexistence: Long-Term Experiments on Recruitment Response

Background: For competing species to coexist, individuals must compete more with others of the same species than with those of other species. Ecologists search for tradeoffs in how species might partition the environment. The negative correlations among competing species that would be indicative of tradeoffs are rarely observed. A recent analysis showed that evidence for partitioning the environment is available when responses are disaggregated to the individual scale, in terms of the covariance structure of responses to environmental variation. That study did not relate that variation to the variables to which individuals were responding. To understand how this pattern of variation is related to niche variables, we analyzed responses to canopy gaps, long viewed as a key variable responsible for species coexistence. Methodology/Principal Findings: A longitudinal intervention analysis of individual responses to experimental canopy gaps with 12 yr of pre-treatment and 8 yr post-treatment responses showed that species-level responses are positively correlated – species that grow fast on average in the understory also grow fast on average in response to gap formation. In other words, there is no tradeoff. However, the joint distribution of individual responses to understory and gap showed a negative correlation – species having individuals that respond most to gaps when previously growing slowly also have individuals that respond least to gaps when previously growing rapidly (e.g., Morus rubra), and vice versa (e.g., Quercus prinus). Conclusions/Significance: Because competition occurs at the individual scale, not the species scale, aggregated speciesleve

A radio census of the massive stellar cluster Westerlund 1

CONTEXT: Massive stars and their stellar winds are important for a number of feedback processes. The mass lost in the stellar wind can help determine the end-point of the star as a neutron star (NS) or a black hole (BH). However, the impact of mass loss on the post-main sequence evolutionary stage of massive stars is not well understood. Westerlund 1 is an ideal astrophysical laboratory in which to study massive stars and their winds in great detail over a large range of different evolutionary phases. AIMS: We aim to study the radio emission from Westerlund 1, in order to measure radio fluxes from the population of massive stars, and determine mass-loss rates and spectral indices where possible. METHODS: Observations were carried out in 2015 and 2016 with the Australia Telescope Compact Array (ATCA) at 5.5 and 9 GHz using multiple configurations, with maximum baselines ranging from 750 m to 6 km. RESULTS: Thirty stars are detected in the radio from the fully concatenated dataset, ten of which are Wolf-Rayet stars (WRs) (predominantly late type WN stars), five yellow hypergiants (YHGs), four red supergiants (RSGs), one luminous blue variable (LBV), the sgB[e] star W9, and several OB supergiants. New source detections in the radio are found for five WR stars, and five OB supergiants. These detections lead to evidence for three new OB supergiant binary candidates, which is inferred from derived spectral index limits. CONCLUSIONS: Spectral indices and index limits were determined for massive stars in Westerlund 1. For cluster members found to have partially optically thick emission, mass-loss rates were calculated. Under the approximation of a thermally emitting stellar wind and a steady mass-loss rate, clumping ratios were then estimated for eight WRs. Diffuse radio emission was detected throughout the cluster. Detections of knots of radio emission with no known stellar counterparts indicate the highly clumped structure of this intra-cluster medium, likely shaped by a dense cluster wind

Post impact evaluation of an E-learning cross-infection control CD-ROM provided to all general dental practitioners in England

Aim To carry out a post-impact evaluation of a cross-infection control CD-ROM, developed for NHS dental teams as a continuing professional development e-learning tool. The program was commissioned by the Department of Health and developed by a project team through the UK Committee of Postgraduate Dental Deans. The Dental Practice Boardhad originally sent one copy of the CD-ROM to each dental practice in England in 2004. Method A quantitative statistical analysis of the results of 326 online respondents to the learning package and a survey of 118 dental practitioners drawn from the Dental Practice Board database. Results Practitioners felt the CD-ROM in this instance was well designed and appropriate for their needs. It is inclusive and accessible to a wide range of dental professionals including nurses and hygienists. Conclusions This form of continuing professional development is popular with dental practitioners, although it should not be the only form of continuing professional development available. However, whilst the project was generally regarded as successful, there were problems with the distribution of the CD-ROM. This suggests that anonline resource should be made available in the future

Tree migration-rates : narrowing the gap between inferred post-glacial rates and projected rates

Faster-than-expected post-glacial migration rates of trees have puzzled ecologists for a long time. In Europe, post-glacial migration is assumed to have started from the three southern European peninsulas (southern refugia), where large areas remained free of permafrost and ice at the peak of the last glaciation. However, increasing palaeobotanical evidence for the presence of isolated tree populations in more northerly microrefugia has started to change this perception. Here we use the Northern Eurasian Plant Macrofossil Database and palaeoecological literature to show that post-glacial migration rates for trees may have been substantially lower (60–260 m yr–1) than those estimated by assuming migration from southern refugia only (115–550 m yr–1), and that early-successional trees migrated faster than mid- and late-successional trees. Post-glacial migration rates are in good agreement with those recently projected for the future with a population dynamical forest succession and dispersal model, mainly for early-successional trees and under optimal conditions. Although migration estimates presented here may be conservative because of our assumption of uniform dispersal, tree migration-rates clearly need reconsideration. We suggest that small outlier populations may be a key factor in understanding past migration rates and in predicting potential future range-shifts. The importance of outlier populations in the past may have an analogy in the future, as many tree species have been planted beyond their natural ranges, with a more beneficial microclimate than their regional surroundings. Therefore, climate-change-induced range-shifts in the future might well be influenced by such microrefugia

Quantum oscillations in quasi-one-dimensional metals with spin-density-wave ground states

We consider the magnetoresistance oscillation phenomena in the Bechgaard salts (TMTSF)(2)X, where X = ClO4, PF6, and AsF6 in pulsed magnetic fields to 51 T. Of particular importance is the observation of a new magnetoresistance oscillation for X = ClO4 in its quenched state. In the absence of any Fermi-surface reconstruction due to anion order at low temperatures, all three materials exhibit nonmonotonic temperature dependence of the oscillation amplitude in the spin-density-wave (SDW) state. We discuss a model where, below a characteristic temperature T* within the SDW state, a magnetic breakdown gap opens. [S0163-1829(99)00904-2]

ATR based infrared spectroscopy for the diagnosis of neonatal respiratory distress syndrome

Optical spectroscopy offers a potential non-invasive, label free and rapid method to assist clinicians to diagnose diseases for which biomarkers are known. Neonatal respiratory distress syndrome (nRDS) diagnosis in preterm infants is known to be correlated with the lecithin/sphingomyelin ratio (LS ratio) in gastric aspirates, with a ratio less than 2.2 indicating that surfactant replacement therapy is needed. Currently no widespread method exists that can give clinically relevant answers in less than 2 hours from the point of sample collection as it is difficult to identify those who could benefit from prompt surfactant treatment. Various LS ratios were generated using pure dipalmitoylphosphatidylcholine (DPPC) and sphingomyelin (SM) dissolved in dichloromethane and infrared spectra generated using Attenuated Total Reflection (ATR) assisted Fourier Transform InfraRed spectrometry (FTIR). Subsequent analysis obtained the LS ratio using the spectra alone. Further, we demonstrate the application of principal component regression (PCR) and partial least squares (PLS) fits to measured spectra to assist in the determination of the LS ratio using a model trained with multiple runs of the different batches of the same concentration

Effect of paper quality on the response rate to a postal survey: A randomised controlled trial. [ISRCTN32032031]

BACKGROUND: Response rates to surveys are declining and this threatens the validity and generalisability of their findings. We wanted to determine whether paper quality influences the response rate to postal surveys METHODS: A postal questionnaire was sent to all members of the British Society of Gynaecological Endoscopy (BSGE). Recipients were randomised to receiving the questionnaire printed on standard quality paper or high quality paper. RESULTS: The response rate for the recipients of high quality paper was 43/195 (22%) and 57/194 (29%) for standard quality paper (relative rate of response 0.75, 95% CI 0.33–1.05, p = 0.1 CONCLUSION: The use of high quality paper did not increase response rates to a questionnaire survey of gynaecologists affiliated to an endoscopic society

Competition-Colonization Trade-Offs, Competitive Uncertainty, and the Evolutionary Assembly of Species

We utilize a standard competition-colonization metapopulation model in order to study the evolutionary assembly of species. Based on earlier work showing how models assuming strict competitive hierarchies will likely lead to runaway evolution and self-extinction for all species, we adopt a continuous competition function that allows for levels of uncertainty in the outcome of competition. We then, by extending the standard patch-dynamic metapopulation model in order to include evolutionary dynamics, allow for the coevolution of species into stable communities composed of species with distinct limiting similarities. Runaway evolution towards stochastic extinction then becomes a limiting case controlled by the level of competitive uncertainty. We demonstrate how intermediate competitive uncertainty maximizes the equilibrium species richness as well as maximizes the adaptive radiation and self-assembly of species under adaptive dynamics with mutations of non-negligible size. By reconciling competition-colonization tradeoff theory with co-evolutionary dynamics, our results reveal the importance of intermediate levels of competitive uncertainty for the evolutionary assembly of species

Prediction of Neonatal Respiratory Distress Biomarker Concentration by Application of Machine Learning to Mid-Infrared Spectra

The authors of this study developed the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR–FTIR) combined with machine learning as a point-of-care (POC) diagnostic platform, considering neonatal respiratory distress syndrome (nRDS), for which no POC currently exists, as an example. nRDS can be diagnosed by a ratio of less than 2.2 of two nRDS biomarkers, lecithin and sphingomyelin (L/S ratio), and in this study, ATR–FTIR spectra were recorded from L/S ratios of between 1.0 and 3.4, which were generated using purified reagents. The calibration of principal component (PCR) and partial least squares (PLSR) regression models was performed using 155 raw baselined and second derivative spectra prior to predicting the concentration of a further 104 spectra. A three-factor PLSR model of second derivative spectra best predicted L/S ratios across the full range (R2: 0.967; MSE: 0.014). The L/S ratios from 1.0 to 3.4 were predicted with a prediction interval of +0.29, −0.37 when using a second derivative spectra PLSR model and had a mean prediction interval of +0.26, −0.34 around the L/S 2.2 region. These results support the validity of combining ATR–FTIR with machine learning to develop a point-of-care device for detecting and quantifying any biomarker with an interpretable mid-infrared spectrum