Density-dependent cladogenesis in birds.

Published versio

Sparse Bayesian mass-mapping with uncertainties: Full sky observations on the celestial sphere

To date weak gravitational lensing surveys have typically been restricted to small fields of view, such that the flat-sky approximation has been sufficiently satisfied. However, with Stage IV surveys (e.g. LSST and Euclid) imminent, extending mass-mapping techniques to the sphere is a fundamental necessity. As such, we extend the sparse hierarchical Bayesian massmapping formalism presented in previous work to the spherical sky. For the first time, this allows us to construct maximum a posteriori spherical weak lensing dark-matter mass-maps, with principled Bayesian uncertainties, without imposing or assuming Gaussianty. We solve the spherical mass-mapping inverse problem in the analysis setting adopting a sparsity promoting Laplacetype wavelet prior, though this theoretical framework supports all log-concave posteriors. Our spherical mass-mapping formalism facilitates principled statistical interpretation of reconstructions. We apply our framework to convergence reconstruction on high resolution N-body simulations with pseudo-Euclid masking, polluted with a variety of realistic noise levels, and show a significant increase in reconstruction fidelity compared to standard approaches. Furthermore, we perform the largest joint reconstruction to date of the majority of publicly available shear observational data sets (combining DESY1, KiDS450, and CFHTLens) and find that our formalism recovers a convergence map with significantly enhanced small-scale detail. Within our Bayesian framework we validate, in a statistically rigorous manner, the community’s intuition regarding the need to smooth spherical Kaiser-Squires estimates to provide physically meaningful convergence maps. Such approaches cannot reveal the small-scale physical structures that we recover within our framework

Sparse Bayesian mass mapping with uncertainties: peak statistics and feature locations

Weak lensing convergence maps – upon which higher order statistics can be calculated – can be recovered from observations of the shear field by solving the lensing inverse problem. For typical surveys this inverse problem is ill-posed (often seriously) leading to substantial uncertainty on the recovered convergence maps. In this paper we propose novel methods for quantifying the Bayesian uncertainty in the location of recovered features and the uncertainty in the cumulative peak statistic – the peak count as a function of signal-to-noise ratio (SNR). We adopt the sparse hierarchical Bayesian mass-mapping framework developed in previous work, which provides robust reconstructions and principled statistical interpretation of reconstructed convergence maps without the need to assume or impose Gaussianity. We demonstrate our uncertainty quantification techniques on both Bolshoi N-body (cluster scale) and Buzzard V-1.6 (large-scale structure) N-body simulations. For the first time, this methodology allows one to recover approximate Bayesian upper and lower limits on the cumulative peak statistic at well-defined confidence levels

Mapping dark matter on the celestial sphere with weak gravitational lensing

Convergence maps of the integrated matter distribution are a key science result from weak gravitational lensing surveys. To date, recovering convergence maps has been performed using a planar approximation of the celestial sphere. However, with the increasing area of sky covered by dark energy experiments, such as Euclid, the Vera Rubin Observatory’s Legacy Survey of Space and Time (LSST), and the Nancy Grace Roman Space Telescope, this assumption will no longer be valid. We recover convergence fields on the celestial sphere using an extension of the Kaiser–Squires estimator to the spherical setting. Through simulations, we study the error introduced by planar approximations. Moreover, we examine how best to recover convergence maps in the planar setting, considering a variety of different projections and defining the local rotations that are required when projecting spin fields such as cosmic shear. For the sky coverages typical of future surveys, errors introduced by projection effects can be of the order of tens of percent, exceeding 50 per cent in some cases. The stereographic projection, which is conformal and so preserves local angles, is the most effective planar projection. In any case, these errors can be avoided entirely by recovering convergence fields directly on the celestial sphere. We apply the spherical Kaiser–Squires mass-mapping method presented to the public Dark Energy Survey science verification data to recover convergence maps directly on the celestial sphere

Reproductive responses to varying food supply in a population of Darwin's finches: Clutch size, growth rates and hatching synchrony

I show how food shortage affects reproduction in a population of Darwin's Medium Ground Finches, Geospiza fortis . Despite the common occurrence of starvation and absence of nest predation, hatching is typically nighly synchronous and adaptive brood reductionappears to be absent. Variation in both growth rates and clutch size in association with the varying conditions is documented. This variation is interpreted as being a direct response to environmental conditions rather than adaptive phenotypic plasticity. I conclude that selection pressures to raise one or two chicks during times of food shortage, or to delay growth rates, are weak or absent.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47759/1/442_2004_Article_BF00378307.pd

"First pain" in humans: convergent and specific forebrain responses

<p>Abstract</p> <p>Background</p> <p>Brief heat stimuli that excite nociceptors innervated by finely myelinated (Aδ) fibers evoke an initial, sharp, well-localized pain ("first pain") that is distinguishable from the delayed, less intense, more prolonged dull pain attributed to nociceptors innervated by unmyelinated (C) fibers ("second pain"). In the present study, we address the question of whether a brief, noxious heat stimulus that excites cutaneous Aδ fibers activates a distinct set of forebrain structures preferentially in addition to those with similar responses to converging input from C fibers. Heat stimuli at two temperatures were applied to the dorsum of the left hand of healthy volunteers in a functional brain imaging (fMRI) paradigm and responses analyzed in a set of volumes of interest (VOI).</p> <p>Results</p> <p>Brief 41°C stimuli were painless and evoked only C fiber responses, but 51°C stimuli were at pain threshold and preferentially evoked Aδ fiber responses. Most VOI responded to both intensities of stimulation. However, within volumes of interest, a contrast analysis and comparison of BOLD response latencies showed that the bilateral anterior insulae, the contralateral hippocampus, and the ipsilateral posterior insula were preferentially activated by painful heat stimulation that excited Aδ fibers.</p> <p>Conclusions</p> <p>These findings show that two sets of forebrain structures mediate the initial sharp pain evoked by brief cutaneous heat stimulation: those responding preferentially to the brief stimulation of Aδ heat nociceptors and those with similar responses to converging inputs from the painless stimulation of C fibers. Our results suggest a unique and specific physiological basis, at the forebrain level, for the "first pain" sensation that has long been attributed to Aδ fiber stimulation and support the concept that both specific and convergent mechanisms act concurrently to mediate pain.</p

Multi-modal signal evolution in birds: re-examining a standard proxy for sexual selection

Sexual selection is proposed to be an important driver of speciation and phenotypic diversification in animal systems. However, previous phylogenetic tests have produced conflicting results, perhaps because they have focused on a single signalling modality (visual ornaments), whereas sexual selection may act on alternative signalling modalities (e.g. acoustic ornaments). Here, we compile phenotypic data from 259 avian sister species pairs to assess the relationship between visible plumage dichromatism-a standard index of sexual selection in birds-and macroevolutionary divergence in the other major avian signalling modality: song. We find evidence for a strong negative relationship between the degree of plumage dichromatism and divergence in song traits, which remains significant even when accounting for other key factors, including habitat type, ecological divergence and interspecific interactions. This negative relationship is opposite to the pattern expected by a straightforward interpretation of the sexual selection-diversification hypothesis, whereby higher levels of dichromatism indicating strong sexual selection should be related to greater levels of mating signal divergence regardless of signalling modality. Our findings imply a 'trade-off' between the elaboration of visual ornaments and the diversification of acoustic mating signals, and suggest that the effects of sexual selection on diversification can only be determined by considering multiple alternative signalling modalities

Diagnosis of Aortic Graft Infection: A Case Definition by the Management of Aortic Graft Infection Collaboration (MAGIC)

OBJECTIVE/BACKGROUND: The management of aortic graft infection (AGI) is highly complex and in the absence of a universally accepted case definition and evidence-based guidelines, clinical approaches and outcomes vary widely. The objective was to define precise criteria for diagnosing AGI. METHODS: A process of expert review and consensus, involving formal collaboration between vascular surgeons, infection specialists, and radiologists from several English National Health Service hospital Trusts with large vascular services (Management of Aortic Graft Infection Collaboration [MAGIC]), produced the definition. RESULTS: Diagnostic criteria from three categories were classified as major or minor. It is proposed that AGI should be suspected if a single major criterion or two or more minor criteria from different categories are present. AGI is diagnosed if there is one major plus any criterion (major or minor) from another category. (i) Clinical/surgical major criteria comprise intraoperative identification of pus around a graft and situations where direct communication between the prosthesis and a nonsterile site exists, including fistulae, exposed grafts in open wounds, and deployment of an endovascular stent-graft into an infected field (e.g., mycotic aneurysm); minor criteria are localized AGI features or fever ≥38°C, where AGI is the most likely cause. (ii) Radiological major criteria comprise increasing perigraft gas volume on serial computed tomography (CT) imaging or perigraft gas or fluid (≥7 weeks and ≥3 months, respectively) postimplantation; minor criteria include other CT features or evidence from alternative imaging techniques. (iii) Laboratory major criteria comprise isolation of microorganisms from percutaneous aspirates of perigraft fluid, explanted grafts, and other intraoperative specimens; minor criteria are positive blood cultures or elevated inflammatory indices with no alternative source. CONCLUSION: This AGI definition potentially offers a practical and consistent diagnostic standard, essential for comparing clinical management strategies, trial design, and developing evidence-based guidelines. It requires validation that is planned in a multicenter, clinical service database supported by the Vascular Society of Great Britain & Ireland

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads