Laser-Stimulated Fluorescence in Paleontology

Fluorescence using ultraviolet (UV) light has seen increased use as a tool in paleontology over the last decade. Laser-stimulated fluorescence (LSF) is a next generation technique that is emerging as a way to fluoresce paleontological specimens that remain dark under typical UV. A laser’s ability to concentrate very high flux rates both at the macroscopic and microscopic levels results in specimens fluorescing in ways a standard UV bulb cannot induce. Presented here are five paleontological case histories that illustrate the technique across a broad range of specimens and scales. Novel uses such as back-lighting opaque specimens to reveal detail and detection of specimens completely obscured by matrix are highlighted in these examples. The recent cost reductions in medium-power short wavelength lasers and use of standard photographic filters has now made this technique widely accessible to researchers. This technology has the potential to automate multiple aspects of paleontology, including preparation and sorting of microfossils. This represents a highly cost-effective way to address paleontology's preparatory bottleneck.published_or_final_versio

Fossil evidence for key innovations in the evolution of insect diversity

Explaining the taxonomic richness of the insects, comprising over half of all described species, is a major challenge in evolutionary biology. Previously, several evolutionary novelties (key innovations) have been posited to contribute to that richness, including the insect bauplan, wings, wing folding and complete metamorphosis, but evidence over their relative importance and modes of action is sparse and equivocal. Here, a new dataset on the first and last occurrences of fossil hexapod (insects and close relatives) families is used to show that basal families of winged insects (Palaeoptera, e.g. dragonflies) show higher origination and extinction rates in the fossil record than basal wingless groups (Apterygota, e.g. silverfish). Origination and extinction rates were maintained at levels similar to Palaeoptera in the more derived Polyneoptera (e.g. cockroaches) and Paraneoptera (e.g. true bugs), but extinction rates subsequently reduced in the very rich group of insects with complete metamorphosis (Holometabola, e.g. beetles). Holometabola show evidence of a recent slow-down in their high net diversification rate, whereas other winged taxa continue to diversify at constant but low rates. These data suggest that wings and complete metamorphosis have had the most effect on family-level insect macroevolution, and point to specific mechanisms by which they have influenced insect diversity through time

Orbit Determination of Close Binary Systems using Lucky Imaging

We present relative positions of visual binaries observed during 2009 with the FastCam "lucky-imaging" camera at the 1.5-m Carlos Sanchez Telescope (TCS) at the Observatorio del Teide. We obtained 424 CCD observations (averaged in 198 mean relative positions) of 157 binaries with angular separations in the range 0.14-15.40", with a median separation of 0.51". For a given system, each CCD image represents the sum of the best 10-25% images from 1000-5000 short-exposure frames. Derived internal errors were 7 mas in r and 1.2^{\circ} (9 mas) in q. When comparing to systems with very well-known orbits, we find that the rms deviation in r residuals is 23 mas, while the rms deviation in q residuals is 0.73 deg/r. We confirmed 18 Hipparcos binaries and we report new companions to BVD 36 A and J 621 B. For binaries with preliminary orbital parameters, the relative radial velocity was estimated as well. We also present four new revised orbits computed for LDS 873, BU 627 A-BC, BU 628 and HO 197 AB. This work is the first results on visual binaries using the FastCam lucky-imaging camera.Comment: 23 pages, 10 figures, 14 tables, accepted August 18th, 2011, to be published in MNRA

Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values and small sample sizes.

The data set supporting the results of this article is available in the Dryad repository, http://dx.doi.org/10.5061/dryad.6f4qs. Moustakas, A. and Evans, M. R. (2015) Effects of growth rate, size, and light availability on tree survival across life stages: a demographic analysis accounting for missing values.Plant survival is a key factor in forest dynamics and survival probabilities often vary across life stages. Studies specifically aimed at assessing tree survival are unusual and so data initially designed for other purposes often need to be used; such data are more likely to contain errors than data collected for this specific purpose

Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared

Predicting the outcome of conservative treatment with physiotherapy in adults with shoulder pain associated with partial-thickness rotator cuff tears – a prognostic model development study

Model coefficient statistics (DOCX 21 kb