39 research outputs found

    How to Measure Group Selection in Real-world Populations

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    Multilevel selection and the evolution of cooperation are fundamental to the formation of higher-level organisation and the evolution of biocomplexity, but such notions are controversial and poorly understood in natural populations. The theoretic principles of group selection are well developed in idealised models where a population is neatly divided into multiple semi-isolated sub-populations. But since such models can be explained by individual selection given the localised frequency-dependent effects involved, some argue that the group selection concepts offered are, even in the idealised case, redundant and that in natural conditions where groups are not well-defined that a group selection framework is entirely inapplicable. This does not necessarily mean, however, that a natural population is not subject to some interesting localised frequency-dependent effects – but how could we formally quantify this under realistic conditions? Here we focus on the presence of a Simpson’s Paradox where, although the local proportion of cooperators decreases at all locations, the global proportion of cooperators increases. We illustrate this principle in a simple individual-based model of bacterial biofilm growth and discuss various complicating factors in moving from theory to practice of measuring group selection

    How to measure group selection in real-world populations

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    Multilevel selection and the evolution of cooperation are fundamental to the formation of higher-level organisation and the evolution of biocomplexity, but such notions are controversial and poorly understood in natural populations. The theoretic principles of group selection are well developed in idealised models where a population is neatly divided into multiple semi-isolated sub-populations. But since such models can be explained by individual selection given the localised frequency-dependent effects involved, some argue that the group selection concepts offered are, even in the idealised case, redundant and that in natural conditions where groups are not well-defined that a group selection framework is entirely inapplicable. This does not necessarily mean, however, that a natural population is not subject to some interesting localised frequency-dependent effects -- but how could we formally quantify this under realistic conditions? Here we focus on the presence of a Simpson's Paradox where, although the local proportion of cooperators decreases at all locations, the global proportion of cooperators increases. We illustrate this principle in a simple individual-based model of bacterial biofilm growth and discuss various complicating factors in moving from theory to practice of measuring group selection.Comment: pp. 672-679 in Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems (Advances in Artificial Life, ECAL 2011). Edited by Tom Lenaerts, Mario Giacobini, Hugues Bersini, Paul Bourgine, Marco Dorigo and Ren\'e Doursat. MIT Press (2011). http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=12760. 8 pages, 5 figure

    Children and Young People's Health Partnership (CYPHP) Evelina London model of care: protocol for an opportunistic cluster randomised controlled trial (cRCT) to assess child health outcomes, healthcare quality and health service use.

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    INTRODUCTION: Children and young people (CYP) in many high-income settings have poor healthcare outcomes, especially those with long-term conditions (LTCs). Emergency and outpatient hospital service use is increasing unsustainably. To address these problems, the Children and Young People's Health Partnership (CYPHP) has developed and is evaluating an integrated model of care as part of a health systems strengthening programme across two boroughs of London, UK that are characterised by mixed ethnic populations and varying levels of deprivation. The CYPHP Evelina London model of care comprises proactive case-finding and triage, specialist clinics and transformative education and training for professionals working with CYP. Services are delivered by multidisciplinary health teams with an emphasis on increased coordination across primary, community and hospital settings and integration of physical and mental healthcare that accounts for the CYP's social context. METHODS AND ANALYSIS: The phased roll out of the CYPHP Evelina London model allows an opportunistic population-based evaluation using a cluster randomised controlled trial design. Seventy general practices across two London boroughs, grouped into 23 clusters, were randomised to provide either the CYPHP model of care (n=11) or enhanced usual care (n=12).The evaluation will measure the impact of the CYPHP Evelina London model of care on child and parent health and well-being, healthcare quality and health service use up to 2 years postimplementation. A population-level evaluation will use routinely collected pseudonymised healthcare data to conduct a service-use analysis for all CYP registered with a participating general practice (n=~90 000) with the rate of non-elective admissions as the primary outcome. We will seek consent from a subset of this population, with specific conditions (target n=2138) to assess the impact on patient-reported outcomes using the Paediatric Quality of Life Inventory (PedsQL) and Warwick-Edinburgh Mental Well-Being Scale (WEBWMS) as, respectively, the child- and parent-related primary outcomes. ETHICS AND DISSEMINATION: Ethics approval obtained from South West-Cornwall & Plymouth Research Ethics Committee. Results will be submitted for publication in peer-reviewed journals. Findings will be generalisable to community-based models of care, especially in urban settings. Our process evaluation will identify barriers and enablers of implementation and delivery of care salient to the context and condition. TRIAL REGISTRATION NUMBER: NCT03461848; Pre-results

    Replay as wavefronts and theta sequences as bump oscillations in a grid cell attractor network.

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    Grid cells fire in sequences that represent rapid trajectories in space. During locomotion, theta sequences encode sweeps in position starting slightly behind the animal and ending ahead of it. During quiescence and slow wave sleep, bouts of synchronized activity represent long trajectories called replays, which are well-established in place cells and have been recently reported in grid cells. Theta sequences and replay are hypothesized to facilitate many cognitive functions, but their underlying mechanisms are unknown. One mechanism proposed for grid cell formation is the continuous attractor network. We demonstrate that this established architecture naturally produces theta sequences and replay as distinct consequences of modulating external input. Driving inhibitory interneurons at the theta frequency causes attractor bumps to oscillate in speed and size, which gives rise to theta sequences and phase precession, respectively. Decreasing input drive to all neurons produces traveling wavefronts of activity that are decoded as replays

    Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis.

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    The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package ('Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes

    The impact of immediate breast reconstruction on the time to delivery of adjuvant therapy: the iBRA-2 study

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    Background: Immediate breast reconstruction (IBR) is routinely offered to improve quality-of-life for women requiring mastectomy, but there are concerns that more complex surgery may delay adjuvant oncological treatments and compromise long-term outcomes. High-quality evidence is lacking. The iBRA-2 study aimed to investigate the impact of IBR on time to adjuvant therapy. Methods: Consecutive women undergoing mastectomy ± IBR for breast cancer July–December, 2016 were included. Patient demographics, operative, oncological and complication data were collected. Time from last definitive cancer surgery to first adjuvant treatment for patients undergoing mastectomy ± IBR were compared and risk factors associated with delays explored. Results: A total of 2540 patients were recruited from 76 centres; 1008 (39.7%) underwent IBR (implant-only [n = 675, 26.6%]; pedicled flaps [n = 105,4.1%] and free-flaps [n = 228, 8.9%]). Complications requiring re-admission or re-operation were significantly more common in patients undergoing IBR than those receiving mastectomy. Adjuvant chemotherapy or radiotherapy was required by 1235 (48.6%) patients. No clinically significant differences were seen in time to adjuvant therapy between patient groups but major complications irrespective of surgery received were significantly associated with treatment delays. Conclusions: IBR does not result in clinically significant delays to adjuvant therapy, but post-operative complications are associated with treatment delays. Strategies to minimise complications, including careful patient selection, are required to improve outcomes for patients

    Proceedings of the Virtual 3rd UK Implementation Science Research Conference : Virtual conference. 16 and 17 July 2020.

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    Automated connection of diagnostics with instant outbreak triage and live global surveillance for TB

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    Trabajo presentado en el Applied Bioinformatics and Public Health Microbiology Cambridge, UK, 5-7 June 2019M. tuberculosis, causal agent of the disease tuberculosis (TB) causes over a million deaths annually, and is responsible for as much as 1/3 of drug resistant infections globally. Genomics offers a route to rapid and comprehensive diagnostics, and if we could enable default (or at least common) data-sharing, there would be huge global benefits for public health epidemiology and drug discovery. However, the transition from research to routine public health usage is challenging: high and low burden countries have different needs, there is no directly useful way to share, and the act of sharing currently offers no direct benefit to the person doing it. We set out to build a publicly available service to address this. Mykrobe Atlas provides rapid offline diagnostics for illumina or nanopore data, that run on a laptop. When a network connection is available, the raw sequence data is synched to the EBI, decontaminated of human and HIV data, and deposited in the ENA under embargo. Rapid turnaround (minutes) gives comparison with a live updated database of all TB ever deposited in NCBI/EBI, including identification of potential outbreak clusters. The user is able to filter and visualise the global set by genetic, geographical, or metadata criteria (e.g. phenotype). The global library of TB uses the BIGSI search index (Bradley et al, 2019), which scales to millions of samples, distributed across multiple disks (low RAM usage). On a slower timescale (within an hour) the data is run through the full variation analysis pipeline that is being evaluated at Public Health England. Of particular note is the system that allows countries to participate while maintaining control of their data, by supporting centralised data with access control *and* distributed databases controlled by the data owners. I will discuss this concretely by looking at a real data from an ongoing (1993-2018) outbreak from the Canary Islands in the context of our current database of over 38,250 M. tuberculosis isolates. I will show how we find both the known outbreak samples from Valencia and Canary Islands, and also related samples from across Europe and Africa. I will finish by detailing future plans, including public availability, incorporation of 100k genomes including thousands with phenotypes, upload of lossy compressed data when internet bandwidth is low, and integration with Nextstrain

    Spatial and temporal age-related spectral alterations in benign human breast tissue

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    Epidemiological evidence suggests that cancers attributable to exogenous carcinogenic agents may appear decades after initiating exposures. Environmental factors including lifestyle and/or diet have been implicated in the aetiology of breast cancer. Breast tissue undergoes continuous molecular and morphological changes from the time of thelarche to menopause and thereafter. These alterations are both cyclical and longitudinal, and can be influenced by several environmental factors including exposure to oestrogens. Research into the latent period leading to breast carcinogenesis has been mostly limited to when hyperplastic lesions are present. Investigations to identify a biomarker of commitment to disease in normal breast tissue are hindered by the molecular and histological diversity of disease-free breast tissue. Benign tissue from reduction mammoplasties provides an opportunity to study biochemical differences between women of similar ages as well as alterations with advancing age. Herein, synchrotron radiation-based Fourier-transform infrared (SR-FTIR) microspectroscopy was used to examine the terminal ductal lobular epithelium (TDLU) and, intra- and inter-lobular epithelium to identify spatial and temporal changes within these areas. Principal component analysis (PCA) followed by linear discriminant analysis of mid-infrared spectra revealed unambiguous inter-individual as well as age-related differences in each histological compartment interrogated. Moreover, exploratory PCA of luminal and myoepithelial cells within the TDLU indicated the presence of specific cells, potentially stem cells. Understanding alterations within benign tissue may assist in the identification of alterations in latent pre-clinical stages of breast cancer
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