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- Erondu, Ngozi, et al.
(författare)
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Neuropeptide Y5 receptor antagonism does not induce clinically meaningful weight loss in overweight and obese adults
- 2006
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Ingår i: Cell Metabolism. - : Elsevier BV. - 1550-4131. ; 4:4, s. 275-282
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Tidskriftsartikel (refereegranskat)abstract
- Neuropeptide Y (NPY) is a potent orexigenic neuropeptide, and antagonism of NPY Y1 and NPY Y5 receptors (NPYxR) is considered a potentially important anti-obesity drug target. We tested the hypothesis that blockade of the NPY5R will lead to weight loss in humans using MIK-0557, a potent, highly selective, orally active NPY5R antagonist. The initial series of experiments reported herein, including a multiple-dose positron-emission tomography study and a 12 week proof-of concept/dose-ranging study, suggested an optimal MK-0557 dose of 1 mg/day. The hypothesis was then tested in a 52 week, multicenter, randomized, double-blind, placebo-controlled trial involving 1661 overweight and obese patients. Although statistically significant at 52 weeks, the magnitude of induced weight loss was not clinically meaningful. These observations provide the first clinical insight into the human NPY-energy homeostatic pathway and suggest that solely targeting the NPY5R in future drug development programs is unlikely to produce therapeutic efficacy.
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- Renoult, Martin, et al.
(författare)
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A Bayesian framework for emergent constraints : case studies of climate sensitivity with PMIP
- 2020
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Ingår i: Climate of the Past. - : Copernicus GmbH. - 1814-9324 .- 1814-9332. ; 16:5, s. 1715-1735
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we introduce a Bayesian framework, which is explicit about prior assumptions, for using model ensembles and observations together to constrain future climate change. The emergent constraint approach has seen broad application in recent years, including studies constraining the equilibrium climate sensitivity (ECS) using the Last Glacial Maximum (LGM) and the mid-Pliocene Warm Period (mPWP). Most of these studies were based on ordinary least squares (OLS) fits between a variable of the climate state, such as tropical temperature, and climate sensitivity. Using our Bayesian method, and considering the LGM and mPWP separately, we obtain values of ECS of 2.7K (0.6-5.2, 5th-95th percentiles) using the PMIP2, PMIP3, and PMIP4 datasets for the LGM and 2.3K (0.5-4.4) with the PlioMIP1 and PlioMIP2 datasets for the mPWP. Restricting the ensembles to include only the most recent version of each model, we obtain 2.7K (0.7-5.2) using the LGM and 2.3K (0.4-4.5) using the mPWP. An advantage of the Bayesian framework is that it is possible to combine the two periods assuming they are independent, whereby we obtain a tighter constraint of 2.5K (0.8-4.0) using the restricted ensemble. We have explored the sensitivity to our assumptions in the method, including considering structural uncertainty, and in the choice of models, and this leads to 95% probability of climate sensitivity mostly below 5K and only exceeding 6K in a single and most uncertain case assuming a large structural uncertainty. The approach is compared with other approaches based on OLS, a Kalman filter method, and an alternative Bayesian method. An interesting implication of this work is that OLS-based emergent constraints on ECS generate tighter uncertainty estimates, in particular at the lower end, an artefact due to a flatter regression line in the case of lack of correlation. Although some fundamental challenges related to the use of emergent constraints remain, this paper provides a step towards a better foundation for their potential use in future probabilistic estimations of climate sensitivity.
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- Swietlicki, Erik, et al.
(författare)
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Source identification during the Great Dun Fell Cloud Experiment 1993
- 1997
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Ingår i: Atmospheric Environment. - 1352-2310. ; 31:16, s. 2441-2451
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Tidskriftsartikel (refereegranskat)abstract
- A characterisation of the sources influencing the site for the final field campaign of the EUROTRAC subproject GCE (Ground-based Cloud Experiment) at Great Dun Fell, Cumbria, Great Britain in April-May 1993 is presented. The sources were characterised mainly by means of aerosol filter and cascade impactor data, single particle analysis, gas data, data on aromatic organic compounds, cloud water ionic composition, measurements of aerosol size distributions and hygroscopic properties and various meteorological information. Receptor models applied on the aerosol filter and impactor data sets separately revealed two major source types being a marine sea spray source and a long-range transported anthropogenic pollution source. The results of the receptor models were largely consistent with the other observations used in the source identification. Periods of considerable anthropogenic pollution as well as almost pure marine air masses were clearly identified during the course of the experiment.
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