347 research outputs found

    Enantioselective isothiourea-catalysed trans-dihydropyridinone synthesis using saccharin-derived ketimines : scope and limitations

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    The authors thank Syngenta and the EPSRC (grant code EP/K503162/1) (DGS) for funding. The European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) ERC Grant Agreement No. 279850 is also acknowledged (CMY). ADS thanks the Royal Society for a Wolfson Research Merit Award. We also thank the EPSRC UK National Mass Spectrometry Facility at Swansea University.The catalytic enantioselective synthesis of a range of trans-dihydropyridinones from aryl-, heteroaryl- and alkenylacetic acids and saccharin-derived ketimines with good to excellent stereocontrol (15 examples, up to >95:5 dr, up to >99:1 er) is reported. After extensive optimisation, HyperBTM proved the optimal isothiourea catalyst for this transformation at −78 °C, giving trans-dihydropyridones with generally excellent levels of diastereo- and enantioselectivity.Publisher PDFPeer reviewe

    N- to C-sulfonyl photoisomerisation of dihydropyridinones : a synthetic and mechanistic study

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    The authors thank the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007–2013) ERC Grant Agreement no. 279850 (CF and JET) and EPSRC grant number EP/J018139/1 (DSBD) for funding. ADS thanks the Royal Society for a Wolfson Research Merit Award.The scope and limitations of a photoinitiated N- to C-sulfonyl migration process within a range of dihydropyridinones is assessed. This sulfonyl transfer proceeds without erosion of either diastereo- or enantiocontrol, and is general across a range of N-sulfonyl substituents (SO2R; R = Ph, 4-MeC6H4, 4-MeOC6H4, 4-NO2C6H4, Me, Et) as well as C(3)-(aryl, heteroaryl, alkyl and alkenyl) and C(4)-(aryl and ester) substitution. Crossover reactions indicate an intermolecular step is operative within the formal migration process, although no crossover from C-sulfonyl products was observed. EPR studies indicate the intermediacy of a sulfonyl radical and a mechanism is proposed based upon these observations.Publisher PDFPeer reviewe

    A Keck Survey for Gravitationally Lensed Lyα Emitters in the Redshift Range 8.5 < z < 10.4: New Constraints on the Contribution of Low-Luminosity Sources to Cosmic Reionization

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    We discuss new observational constraints on the abundance of faint high-redshift Lyα emitters secured from a deep Keck near-infrared spectroscopic survey that utilizes the strong magnification provided by lensing galaxy clusters. In each of nine clusters, we have undertaken a systematic "blind" search for line emission with NIRSPEC in the J band within carefully selected regions that offer very high magnifications (≳10×-50×) for background sources with redshifts z ≃ 10. The high magnification enables the detection of emission at unprecedented flux limits (10^(41)-10^(42) ergs s^(-1)). As the comoving volumes probed are small, our survey is designed to address the important question of whether low-luminosity galaxies could provide the dominant ionizing flux at z ~ 10. Our survey has yielded six promising (>5 σ) candidate Lyα emitters that lie between z = 8.7 and z = 10.2. We carefully discuss the validity of our detections and the likelihood that the detected line is Lyα in light of earlier, apparently false, claims. Lower redshift line interpretations can be excluded, with reasonable assumptions, through the nondetection of secondary emission in further spectroscopy undertaken with LRIS and NIRSPEC. Nonetheless, as a result of our tests, we argue that at least two of our candidates are likely to be at z ≃ 10. Given the small survey volume, this suggests there is a large abundance of low-luminosity star-forming sources at z ≃ 8-10. While the predicted reionization photon budget depends upon a large number of physical assumptions, our first glimpse at the z 10 universe suggests that low-luminosity star-forming galaxies contribute a significant proportion of the UV photons necessary for cosmic reionization

    Isothiourea-catalysed enantioselective pyrrolizine synthesis : synthetic and computational studies

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    We thank Syngenta and the EPSRC (grant code EP/K503162/1) (DGS), and the EPSRC Centre for Doctoral Training in Critical Resource Catalysis (CRITICAT, grant code EP/L016419/1) (ERG,SFM, RWFK) for funding. The European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) ERC Grant Agreement No. 279850 is also acknowledged (JET). ADS thanks the Royal Society for a Wolfson Research Merit Award.The catalytic enantioselective synthesis of a range of cis-pyrrolizine carboxylate derivatives with outstanding stereocontrol (14 examples,>95:5 dr, >98:2 er) through an isothiourea-catalyzed intramolecular Michael addition-lactonisation and ring opening approach from the corresponding enone acid is reported. An optimised and straightforward three-step synthetic route to the enone acid starting materials from readily available pyrrole-2-carboxaldehydes is delineated, with benzotetramisole (5 mol%) proving the optimal catalyst for the enantioselective process. Ring-opening of the pyrrolizine dihydropyranone products with either MeOH or a range of amines leads to the desired products in excellent yield and enantioselectivity. Computation has been used to probe the factors leading to high stereocontrol, with the formation of the observed cis-steroisomer predicted to be kinetically and thermodynamically favoured.Publisher PDFPeer reviewe

    Treating Causes Not Symptoms : Basic Income as a Public Health Measure

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    New research funded by the National Institute for Health and Social Care Research (NIHR) has found that a Basic Income scheme could potentially save the NHS tens of billions of pounds. ‘Treating causes not symptoms: Basic Income as a public health measure’ uses a range of economic and health modelling, public opinion surveys and community consultation to present cutting-edge evidence on the impact of Basic Income schemes

    RELICS: Reionization Lensing Cluster Survey

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    Large surveys of galaxy clusters with the Hubble and Spitzer Space Telescopes, including CLASH and the Frontier Fields, have demonstrated the power of strong gravitational lensing to efficiently deliver large samples of high-redshift galaxies. We extend this strategy through a wider, shallower survey named RELICS, the Reionization Lensing Cluster Survey. This survey, described here, was designed primarily to deliver the best and brightest high-redshift candidates from the first billion years after the Big Bang. RELICS observed 41 massive galaxy clusters with Hubble and Spitzer at 0.4-1.7um and 3.0-5.0um, respectively. We selected 21 clusters based on Planck PSZ2 mass estimates and the other 20 based on observed or inferred lensing strength. Our 188-orbit Hubble Treasury Program obtained the first high-resolution near-infrared images of these clusters to efficiently search for lensed high-redshift galaxies. We observed 46 WFC3/IR pointings (~200 arcmin^2) with two orbits divided among four filters (F105W, F125W, F140W, and F160W) and ACS imaging as needed to achieve single-orbit depth in each of three filters (F435W, F606W, and F814W). As previously reported by Salmon et al., we discovered 322 z ~ 6 - 10 candidates, including the brightest known at z ~ 6, and the most distant spatially-resolved lensed arc known at z ~ 10. Spitzer IRAC imaging (945 hours awarded, plus 100 archival) has crucially enabled us to distinguish z ~ 10 candidates from z ~ 2 interlopers. For each cluster, two HST observing epochs were staggered by about a month, enabling us to discover 11 supernovae, including 3 lensed supernovae, which we followed up with 20 orbits from our program. We delivered reduced HST images and catalogs of all clusters to the public via MAST and reduced Spitzer images via IRSA. We have also begun delivering lens models of all clusters, to be completed before the JWST GO call for proposals.Comment: 29 pages, 6 figures, submitted to ApJ. For reduced images, catalogs, lens models, and more, see relics.stsci.ed

    Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

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    Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

    The United States COVID-19 Forecast Hub dataset

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    Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages
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