36 research outputs found

    How are emergent constraints quantifying uncertainty and what do they leave behind?

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    The use of emergent constraints to quantify uncertainty for key policy relevant quantities such as Equilibrium Climate Sensitivity (ECS) has become increasingly widespread in recent years. Many researchers, however, claim that emergent constraints are inappropriate or even under-report uncertainty. In this paper we contribute to this discussion by examining the emergent constraints methodology in terms of its underpinning statistical assumptions. We argue that the existing frameworks are based on indefensible assumptions, then show how weakening them leads to a more transparent Bayesian framework wherein hitherto ignored sources of uncertainty, such as how reality might differ from models, can be quantified. We present a guided framework for the quantification of additional uncertainties that is linked to the confidence we can have in the underpinning physical arguments for using linear constraints. We provide a software tool for implementing our general framework for emergent constraints and use it to illustrate the framework on a number of recent emergent constraints for ECS. We find that the robustness of any constraint to additional uncertainties depends strongly on the confidence we can have in the underpinning physics, allowing a future framing of the debate over the validity of a particular constraint around the underlying physical arguments, rather than statistical assumptions

    A Bayesian framework for verification and recalibration of ensemble forecasts: How uncertain is NAO predictability?

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    Predictability estimates of ensemble prediction systems are uncertain due to limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that provides a simple 6-parameter representation of ensemble forecasting systems and the corresponding observations. The framework is probabilistic, and thus allows for quantifying uncertainty in predictability measures such as correlation skill and signal-to-noise ratios. It also provides a natural way to produce recalibrated probabilistic predictions from uncalibrated ensembles forecasts. The framework is used to address important questions concerning the skill of winter hindcasts of the North Atlantic Oscillation for 1992-2011 issued by the Met Office GloSea5 climate prediction system. Although there is much uncertainty in the correlation between ensemble mean and observations, there is strong evidence of skill: the 95% credible interval of the correlation coefficient of [0.19,0.68] does not overlap zero. There is also strong evidence that the forecasts are not exchangeable with the observations: With over 99% certainty, the signal-to-noise ratio of the forecasts is smaller than the signal-to-noise ratio of the observations, which suggests that raw forecasts should not be taken as representative scenarios of the observations. Forecast recalibration is thus required, which can be coherently addressed within the proposed framework.Comment: 36 pages, 10 figure

    Free backbone carbonyls mediate rhodopsin activation

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    Conserved prolines in the transmembrane helices of G-protein-coupled receptors (GPCRs) are often considered to function as hinges that divide the helix into two segments capable of independent motion. Depending on their potential to hydrogen-bond, the free C=O groups associated with these prolines can facilitate conformational flexibility, conformational switching or stabilization of the receptor structure. To address the role of conserved prolines in family A GPCRs through solid-state NMR spectroscopy, we focus on bovine rhodopsin, a GPCR in the visual receptor subfamily. The free backbone C=O groups on helices H5 and H7 stabilize the inactive rhodopsin structure through hydrogen-bonds to residues on adjacent helices. In response to light-induced isomerization of the retinal chromophore, hydrogen-bonding interactions involving these C=O groups are released, thus facilitating repacking of H5 and H7 onto the transmembrane core of the receptor. These results provide insights into the multiple structural and functional roles of prolines in membrane proteins

    A single cell atlas of frozen shoulder capsule identifies features associated with inflammatory fibrosis resolution

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    Frozen shoulder is a spontaneously self-resolving chronic inflammatory fibrotic human disease, which distinguishes the condition from most fibrotic diseases that are progressive and irreversible. Using single-cell analysis, we identify pro-inflammatory MERTKlowCD48+ macrophages and MERTK + LYVE1 + MRC1+ macrophages enriched for negative regulators of inflammation which co-exist in frozen shoulder capsule tissues. Micro-cultures of patient-derived cells identify integrin-mediated cell-matrix interactions between MERTK+ macrophages and pro-resolving DKK3+ and POSTN+ fibroblasts, suggesting that matrix remodelling plays a role in frozen shoulder resolution. Cross-tissue analysis reveals a shared gene expression cassette between shoulder capsule MERTK+ macrophages and a respective population enriched in synovial tissues of rheumatoid arthritis patients in disease remission, supporting the concept that MERTK+ macrophages mediate resolution of inflammation and fibrosis. Single-cell transcriptomic profiling and spatial analysis of human foetal shoulder tissues identify MERTK + LYVE1 + MRC1+ macrophages and DKK3+ and POSTN+ fibroblast populations analogous to those in frozen shoulder, suggesting that the template to resolve fibrosis is established during shoulder development. Crosstalk between MerTK+ macrophages and pro-resolving DKK3+ and POSTN+ fibroblasts could facilitate resolution of frozen shoulder, providing a basis for potential therapeutic resolution of persistent fibrotic diseases

    Oncogenic BRAF, unrestrained by TGFβ-receptor signalling, drives right-sided colonic tumorigenesis

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    Right-sided (proximal) colorectal cancer (CRC) has a poor prognosis and a distinct mutational profile, characterized by oncogenic BRAF mutations and aberrations in mismatch repair and TGFβ signalling. Here, we describe a mouse model of right-sided colon cancer driven by oncogenic BRAF and loss of epithelial TGFβ-receptor signalling. The proximal colonic tumours that develop in this model exhibit a foetal-like progenitor phenotype (Ly6a/Sca1+) and, importantly, lack expression of Lgr5 and its associated intestinal stem cell signature. These features are recapitulated in human BRAF-mutant, right-sided CRCs and represent fundamental differences between left- and right-sided disease. Microbial-driven inflammation supports the initiation and progression of these tumours with foetal-like characteristics, consistent with their predilection for the microbe-rich right colon and their antibiotic sensitivity. While MAPK-pathway activating mutations drive this foetal-like signature via ERK-dependent activation of the transcriptional coactivator YAP, the same foetal-like transcriptional programs are also initiated by inflammation in a MAPK-independent manner. Importantly, in both contexts, epithelial TGFβ-receptor signalling is instrumental in suppressing the tumorigenic potential of these foetal-like progenitor cells
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