950 research outputs found

    Motor output and control input in flapping flight: a compact model of the deforming wing kinematics of manoeuvring hoverflies

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    Insects are conventionally modelled as controlling flight by varying a few summary kinematic parameters that are defined on a per-wingbeat basis, such as the stroke amplitude, mean stroke angle and mean wing pitch angle. Nevertheless, as insects have tens of flight muscles and vary their kinematics continuously, the true dimension of their control input space is likely to be much higher. Here, we present a compact description of the deforming wing kinematics of 36 manoeuvring Eristalis hoverflies, applying functional principal components analysis to Fourier series fits of the wingtip position and wing twist measured over 26 541 wingbeats. This analysis offers a high degree of data reduction, in addition to insight into the natural kinematic couplings. We used statistical resampling techniques to verify that the principal components (PCs) were repeatable features of the data, and analysed their coefficient vectors to provide insight into the form of these natural couplings. Conceptually, the dominant PCs provide a natural set of control input variables that span the control input subspace utilized by this species, but they can also be thought of as output states of the flight motor. This functional description of the wing kinematics is appropriate to modelling insect flight as a form of limit cycle control

    A semi-empirical model of the aerodynamics of manoeuvring insect flight

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    Blade element modelling provides a quick analytical method for estimating the aerodynamic forces produced during insect flight, but such models have yet to be tested rigorously using kinematic data recorded from free-flying insects. This is largely because of the paucity of detailed free-flight kinematic data, but also because analytical limitations in existing blade element models mean that they cannot incorporate the complex three-dimensional movements of the wings and body that occur during insect flight. Here, we present a blade element model with empirically fitted aerodynamic force coefficients that incorporates the full three-dimensional wing kinematics of manoeuvring Eristalis hoverflies, including torsional deformation of their wings. The two free parameters were fitted to a large free-flight dataset comprising N = 26 541 wingbeats, and the fitted model captured approximately 80% of the variation in the stroke-averaged forces in the sagittal plane. We tested the robustness of the model by subsampling the data, and found little variation in the parameter estimates across subsamples comprising 10% of the flight sequences. The simplicity and generality of the model that we present is such that it can be readily applied to kinematic datasets from other insects, and also used for the study of insect flight dynamics

    Mutations in pericentrin cause Seckel syndrome with defective ATR-dependent DNA damage signaling

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    Large brain size is one of the defining characteristics of modern humans. Seckel syndrome (MIM 210600), a disorder of markedly reduced brain and body size, is associated with defective ATR-dependent DNA damage signaling. Only a single hypomorphic mutation of ATR has been identified in this genetically heterogeneous condition. We now report that mutations in the gene encoding pericentrin (PCNT)--resulting in the loss of pericentrin from the centrosome, where it has key functions anchoring both structural and regulatory proteins--also cause Seckel syndrome. Furthermore, we find that cells of individuals with Seckel syndrome due to mutations in PCNT (PCNT-Seckel) have defects in ATR-dependent checkpoint signaling, providing the first evidence linking a structural centrosomal protein with DNA damage signaling. These findings also suggest that other known microcephaly genes implicated in either DNA repair responses or centrosomal function may act in common developmental pathways determining human brain and body size

    Avatars of Eurocentrism in the critique of the liberal peace

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    Recent scholarly critiques of the so-called liberal peace raise important political and ethical challenges to practices of postwar intervention in the global South. However, their conceptual and analytic approaches have tended to reproduce rather than challenge the intellectual Eurocentrism underpinning the liberal peace. Eurocentric features of the critiques include the methodological bypassing of target subjects in research, the analytic bypassing of subjects through frameworks of governmentality, the assumed ontological split between the ‘liberal’ and the ‘local’, and a nostalgia for the liberal subject and the liberal social contract as alternative bases for politics. These collectively produce a ‘paradox of liberalism’ that sees the liberal peace as oppressive but also the only true source of emancipation. However, the article suggests that a repoliticization of colonial difference offers an alternative ‘decolonizing’ approach to critical analysis through repositioning the analytic gaze. Three alternative research strategies for critical analysis are briefly developed

    Identification of the first ATRIP-deficient patient and novel mutations in ATR define a clinical spectrum for ATR-ATRIP Seckel Syndrome

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    A homozygous mutational change in the Ataxia-Telangiectasia and RAD3 related (ATR) gene was previously reported in two related families displaying Seckel Syndrome (SS). Here, we provide the first identification of a Seckel Syndrome patient with mutations in ATRIP, the gene encoding ATR-Interacting Protein (ATRIP), the partner protein of ATR required for ATR stability and recruitment to the site of DNA damage. The patient has compound heterozygous mutations in ATRIP resulting in reduced ATRIP and ATR expression. A nonsense mutational change in one ATRIP allele results in a C-terminal truncated protein, which impairs ATR-ATRIP interaction; the other allele is abnormally spliced. We additionally describe two further unrelated patients native to the UK with the same novel, heterozygous mutations in ATR, which cause dramatically reduced ATR expression. All patient-derived cells showed defective DNA damage responses that can be attributed to impaired ATR-ATRIP function. Seckel Syndrome is characterised by microcephaly and growth delay, features also displayed by several related disorders including Majewski (microcephalic) osteodysplastic primordial dwarfism (MOPD) type II and Meier-Gorlin Syndrome (MGS). The identification of an ATRIP-deficient patient provides a novel genetic defect for Seckel Syndrome. Coupled with the identification of further ATR-deficient patients, our findings allow a spectrum of clinical features that can be ascribed to the ATR-ATRIP deficient sub-class of Seckel Syndrome. ATR-ATRIP patients are characterised by extremely severe microcephaly and growth delay, microtia (small ears), micrognathia (small and receding chin), and dental crowding. While aberrant bone development was mild in the original ATR-SS patient, some of the patients described here display skeletal abnormalities including, in one patient, small patellae, a feature characteristically observed in Meier-Gorlin Syndrome. Collectively, our analysis exposes an overlapping clinical manifestation between the disorders but allows an expanded spectrum of clinical features for ATR-ATRIP Seckel Syndrome to be define

    Conducting retrospective impact analysis to inform a medical research charity’s funding strategies: The case of Asthma UK

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    © 2013 Hanney et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.BACKGROUND: Debate is intensifying about how to assess the full range of impacts from medical research. Complexity increases when assessing the diverse funding streams of funders such as Asthma UK, a charitable patient organisation supporting medical research to benefit people with asthma. This paper aims to describe the various impacts identified from a range of Asthma UK research, and explore how Asthma UK utilised the characteristics of successful funding approaches to inform future research strategies. METHODS: We adapted the Payback Framework, using it both in a survey and to help structure interviews, documentary analysis, and case studies. We sent surveys to 153 lead researchers of projects, plus 10 past research fellows, and also conducted 14 detailed case studies. These covered nine projects and two fellowships, in addition to the innovative case studies on the professorial chairs (funded since 1988) and the MRC-Asthma UK Centre in Allergic Mechanisms of Asthma (the ‘Centre’) which together facilitated a comprehensive analysis of the whole funding portfolio. We organised each case study to capture whatever academic and wider societal impacts (or payback) might have arisen given the diverse timescales, size of funding involved, and extent to which Asthma UK funding contributed to the impacts. RESULTS: Projects recorded an average of four peer-reviewed journal articles. Together the chairs reported over 500 papers. All streams of funding attracted follow-on funding. Each of the various categories of societal impacts arose from only a minority of individual projects and fellowships. Some of the research portfolio is influencing asthma-related clinical guidelines, and some contributing to product development. The latter includes potentially major breakthroughs in asthma therapies (in immunotherapy, and new inhaled drugs) trialled by university spin-out companies. Such research-informed guidelines and medicines can, in turn, contribute to health improvements. The role of the chairs and the pioneering collaborative Centre is shown as being particularly important. CONCLUSIONS: We systematically demonstrate that all types of Asthma UK’s research funding assessed are making impacts at different levels, but the main societal impacts from projects and fellowships come from a minority of those funded. Asthma UK used the study’s findings, especially in relation to the Centre, to inform research funding strategies to promote the achievement of impact.This study was funded by Asthma UK

    Improving statistical inference on pathogen densities estimated by quantitative molecular methods: malaria gametocytaemia as a case study

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    BACKGROUND: Quantitative molecular methods (QMMs) such as quantitative real-time polymerase chain reaction (q-PCR), reverse-transcriptase PCR (qRT-PCR) and quantitative nucleic acid sequence-based amplification (QT-NASBA) are increasingly used to estimate pathogen density in a variety of clinical and epidemiological contexts. These methods are often classified as semi-quantitative, yet estimates of reliability or sensitivity are seldom reported. Here, a statistical framework is developed for assessing the reliability (uncertainty) of pathogen densities estimated using QMMs and the associated diagnostic sensitivity. The method is illustrated with quantification of Plasmodium falciparum gametocytaemia by QT-NASBA. RESULTS: The reliability of pathogen (e.g. gametocyte) densities, and the accompanying diagnostic sensitivity, estimated by two contrasting statistical calibration techniques, are compared; a traditional method and a mixed model Bayesian approach. The latter accounts for statistical dependence of QMM assays run under identical laboratory protocols and permits structural modelling of experimental measurements, allowing precision to vary with pathogen density. Traditional calibration cannot account for inter-assay variability arising from imperfect QMMs and generates estimates of pathogen density that have poor reliability, are variable among assays and inaccurately reflect diagnostic sensitivity. The Bayesian mixed model approach assimilates information from replica QMM assays, improving reliability and inter-assay homogeneity, providing an accurate appraisal of quantitative and diagnostic performance. CONCLUSIONS: Bayesian mixed model statistical calibration supersedes traditional techniques in the context of QMM-derived estimates of pathogen density, offering the potential to improve substantially the depth and quality of clinical and epidemiological inference for a wide variety of pathogens
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