Atlantic multidecadal variability and the U.K. acsis program

Abstract Atlantic multidecadal variability (AMV) is the term used to describe the pattern of variability in North Atlantic sea surface temperatures (SSTs) that is characterized by decades of basinwide warm or cool anomalies, relative to the global mean. AMV has been associated with numerous climate impacts in many regions of the world including decadal variations in temperature and rainfall patterns, hurricane activity, and sea level changes. Given its importance, understanding the physical processes that drive AMV and the extent to which its evolution is predictable is a key challenge in climate science. A leading hypothesis is that natural variations in ocean circulation control changes in ocean heat content and consequently AMV phases. However, this view has been challenged recently by claims that changing natural and anthropogenic radiative forcings are critical drivers of AMV. Others have argued that changes in ocean circulation are not required. Here, we review the leading hypotheses and mechanisms for AMV and discuss the key debates. In particular, we highlight the need for a holistic understanding of AMV. This perspective is a key motivation for a major new U.K. research program: the North Atlantic Climate System Integrated Study (ACSIS), which brings together seven of the United Kingdom’s leading environmental research institutes to enable a broad spectrum approach to the challenges of AMV. ACSIS will deliver the first fully integrated assessment of recent decadal changes in the North Atlantic, will investigate the attribution of these changes to their proximal and ultimate causes, and will assess the potential to predict future changes.</jats:p

The relative impact of baryons and cluster shape on weak lensing mass estimates of galaxy clusters

Weak gravitational lensing depends on the integrated mass along the line of sight. Baryons contribute to the mass distribution of galaxy clusters and the resulting mass estimates from lensing analysis. We use the cosmo-OWLS suite of hydrodynamic simulations to investigate the impact of baryonic processes on the bias and scatter of weak lensing mass estimates of clusters. These estimates are obtained by fitting NFW profiles to mock data using MCMC techniques. In particular, we examine the difference in estimates between dark matter-only runs and those including various prescriptions for baryonic physics. We find no significant difference in the mass bias when baryonic physics is included, though the overall mass estimates are suppressed when feedback from AGN is included. For lowest-mass systems for which a reliable mass can be obtained ($M_{200} \approx 2 \times 10^{14}$ $M_{\odot}$), we find a bias of $\approx -10$ per cent. The magnitude of the bias tends to decrease for higher mass clusters, consistent with no bias for the most massive clusters which have masses comparable to those found in the CLASH and HFF samples. For the lowest mass clusters, the mass bias is particularly sensitive to the fit radii and the limits placed on the concentration prior, rendering reliable mass estimates difficult. The scatter in mass estimates between the dark matter-only and the various baryonic runs is less than between different projections of individual clusters, highlighting the importance of triaxiality

Gene variants influencing measures of inflammation or predisposing to autoimmune and inflammatory diseases are not associated with the risk of type 2 diabetes.

AIMS/HYPOTHESIS: There are strong associations between measures of inflammation and type 2 diabetes, but the causal directions of these associations are not known. We tested the hypothesis that common gene variants known to alter circulating levels of inflammatory proteins, or known to alter autoimmune-related disease risk, influence type 2 diabetes risk. METHODS: We selected 46 variants: (1) eight variants known to alter circulating levels of inflammatory proteins, including those in the IL18, IL1RN, IL6R, MIF, PAI1 (also known as SERPINE1) and CRP genes; and (2) 38 variants known to predispose to autoimmune diseases, including type 1 diabetes. We tested the associations of these variants with type 2 diabetes using a meta-analysis of 4,107 cases and 5,187 controls from the Wellcome Trust Case Control Consortium, the Diabetes Genetics Initiative, and the Finland-United States Investigation of NIDDM studies. We followed up associated variants (p < 0.01) in a further set of 3,125 cases and 3,596 controls from the UK. RESULTS: We found no evidence that inflammatory or autoimmune disease variants are associated with type 2 diabetes (at p <or= 0.01). The OR observed between the variant altering IL-18 levels, rs2250417, and type 2 diabetes (OR 1.00 [95% CI 0.99-1.03]), is much lower than that expected given (1) the effect of the variant on IL-18 levels (0.28 SDs per allele); and (2) estimates, based on other studies, of the correlation between IL-18 levels and type 2 diabetes risk (approximate OR 1.15 [95% CI 1.09-1.21] per 0.28 SD increase in IL-18 levels). CONCLUSIONS/INTERPRETATION: Our study provided no evidence that variants known to alter measures of inflammation, autoimmune or inflammatory disease risk, including type 1 diabetes, alter type 2 diabetes risk

Computing Equilibria of Prediction Markets via Persuasion

We study the computation of equilibria in prediction markets in perhaps the most fundamental special case with two players and three trading opportunities. To do so, we show equivalence of prediction market equilibria with those of a simpler signaling game with commitment introduced by Kong and Schoenebeck (2018). We then extend their results by giving computationally efficient algorithms for additional parameter regimes. Our approach leverages a new connection between prediction markets and Bayesian persuasion, which also reveals interesting conceptual insights

Integrating climate change mitigation and adaptation in agriculture and forestry: opportunities and trade-offs

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.International audienceAlthough many activities can jointly contribute to the climate change strategies of adaptation and mitigation, climate policies have generally treated these strategies separately. In recent years, there has been a growing interest shown by practitioners in agriculture, forestry, and landscape management in the links between the two strategies. This review explores the opportunities and trade-offs when managing landscapes for both climate change mitigation and adaptation; different conceptua-lizations of the links between adaptation and mitigation are highlighted. Under a first conceptualization of 'joint outcomes,' several reviewed studies analyze how activities without climatic objectives deliver joint adaptation and mitigation outcomes. In a second conceptualization of 'unintended side effects,' the focus is on how activities aimed at only one climate objective—either adaptation or mitigation—can deliver outcomes for the other objective. A third conceptualization of 'joint objectives' highlights that associating both adaptation and mitigation objectives in a climate-related activity can influence its outcomes because of multiple possible interactions. The review reveals a diversity of reasons for mainstreaming adaptation and mitigation separately or jointly in landscape management. The three broad conceptualizations of the links between adaptation and mitigation suggest different implications for climate policy mainstreaming and integration

The impact of baryonic physics and massive neutrinos on weak lensing peak statistics

We study the impact of baryonic processes and massive neutrinos on weak lensing peak statistics that can be used to constrain cosmological parameters. We use the BAHAMAS suite of cosmological simulations, which self-consistently include baryonic processes and the effect of massive neutrino free-streaming on the evolution of structure formation. We construct synthetic weak lensing catalogues by ray-tracing through light-cones, and use the aperture mass statistic for the analysis. The peaks detected on the maps reflect the cumulative signal from massive bound objects and general large-scale structure. We present the first study of weak lensing peaks in simulations that include both baryonic physics and massive neutrinos (summed neutrino mass $M_{\nu} =$ 0.06, 0.12, 0.24, and 0.48 eV assuming normal hierarchy), so that the uncertainty due to physics beyond the gravity of dark matter can be factored into constraints on cosmological models. Assuming a fiducial model of baryonic physics, we also investigate the correlation between peaks and massive haloes, over a range of summed neutrino mass values. As higher neutrino mass tends to suppress the formation of massive structures in the Universe, the halo mass function and lensing peak counts are therefore modified as a function of $M_{\nu}$. Over most of the S/N range, the impact of fiducial baryonic physics is greater (less) than neutrinos for 0.06 and 0.12 (0.24 and 0.48) eV models. Both baryonic physics and massive neutrinos should be accounted for when deriving cosmological parameters from weak lensing observations

Early Relapse After Autologous Hematopoietic Cell Transplantation Remains a Poor Prognostic Factor in Multiple Myeloma but Outcomes Have Improved Over Time

Duration of initial disease response remains a strong prognostic factor in multiple myeloma (MM) particularly for upfront autologous hematopoietic cell transplant (AHCT) recipients. We hypothesized that new drug classes and combinations employed prior to AHCT as well as after post-AHCT relapse may have changed the natural history of MM in this population. We analyzed the Center for International Blood and Marrow Transplant Research database to track overall survival (OS) of MM patients receiving single AHCT within 12 months after diagnosis (N=3256) and relapsing early post-AHCT (\u3c 24 months), and to identify factors predicting for early vs late relapses (24−48 months post-AHCT). Over three periods (2001–2004, 2005–2008, 2009–2013), patient characteristics were balanced except for lower proportion of Stage III, higher likelihood of one induction therapy with novel triplets and higher rates of planned post-AHCT maintenance over time. The proportion of patients relapsing early was stable over time at 35–38%. Factors reducing risk of early relapse included lower stage, chemosensitivity, transplant after 2008 and post-AHCT maintenance. Shorter post-relapse OS was associated with early relapse, IgA MM, Karnofsky \u3c 90, stage III, \u3e 1 line of induction and lack of maintenance. Post-AHCT early relapse remains a poor prognostic factor, even though outcomes have improved over time

No man’s land: information needs and resources of men with metastatic castrate resistant prostate cancer

The majority of men treated for prostate cancer will eventually develop castrate resistant disease (CRPC) with metastases (mCRPC). There are several options for further treatment: chemotherapy, third-line hormone therapy, radium, immunotherapy and palliation. Current ASCO guidelines for survivors of prostate cancer recommend that an individual’s information needs at all stages of disease are assessed, and that patients are provided with or referred to the appropriate sources for information and support. Earlier reviews have highlighted the dearth of such services and we wished to see if the situation had improved more recently. Unfortunately we conclude that there is still a lack of good quality congruent information easily accessible specifically for men with mCRPC and insufficient data regarding the risks, harms and benefits of different management plans. More research providing a clear evidence base about treatment consequences using patient reported outcome measures is required

Nuclear receptors in vascular biology

Nuclear receptors sense a wide range of steroids and hormones (estrogens, progesterone, androgens, glucocorticoid, and mineralocorticoid), vitamins (A and D), lipid metabolites, carbohydrates, and xenobiotics. In response to these diverse but critically important mediators, nuclear receptors regulate the homeostatic control of lipids, carbohydrate, cholesterol, and xenobiotic drug metabolism, inflammation, cell differentiation and development, including vascular development. The nuclear receptor family is one of the most important groups of signaling molecules in the body and as such represent some of the most important established and emerging clinical and therapeutic targets. This review will highlight some of the recent trends in nuclear receptor biology related to vascular biology