University of East Anglia

About: University of East Anglia is a education organization based out in Norwich, Norfolk, United Kingdom. It is known for research contribution in the topics: Population & Climate change. The organization has 13250 authors who have published 37504 publications receiving 1669060 citations. The organization is also known as: UEA.

Testing E-OBS European high-resolution gridded data set of daily precipitation and surface temperature

Abstract: Gridded data sets derived through interpolation of station data have a number of potential inaccuracies and errors. These errors can be introduced either by the propagation of errors in the station data into derived gridded data or by limitations in the ability of the interpolation method to estimate grid values from the underlying station network. Recently, Haylock et al. (2008) reported on the development of a new high-resolution gridded data set of daily climate over Europe (termed E-OBS). E-OBS is based on the largest available pan-European data set, and the interpolation methods used were chosen after careful evaluation of a number of alternatives, yet the data set will inevitably have errors and uncertainties. In this paper we assess the E-OBS data set with respect to: (1) homogeneity of the gridded data; (2) evaluation of inaccuracies arising from available network density, through comparison with existing data sets that have been developed with much denser station networks; and (3) the accuracy of the estimates of interpolation uncertainty that are provided as part of E-OBS. We find many inhomogeneities in the gridded data that are primarily caused by inhomogeneities in the underlying station data. In the comparison of existing data with E-OBS, we find that while correlations overall are high, relative differences in precipitation are large, and usually biased toward lower values in E-OBS. From the analysis of the interpolation uncertainties provided as part of E-OBS, we conclude that the interpolation standard deviation provided with the data significantly underestimates the true interpolation error when cross validated using station data, and therefore will similarly underestimate the interpolation error in the gridded E-OBS data. While E-OBS represents a valuable new resource for climate research in Europe, users of the data need to be aware of the limitations in the data set and use the data appropriately.

Brown and white adipose tissues: intrinsic differences in gene expression and response to cold exposure in mice

Abstract: Brown adipocytes dissipate energy, whereas white adipocytes are an energy storage site. We explored the plasticity of different white adipose tissue depots in acquiring a brown phenotype by cold exposure. By comparing cold-induced genes in white fat to those enriched in brown compared with white fat, at thermoneutrality we defined a “brite” transcription signature. We identified the genes, pathways, and promoter regulatory motifs associated with “browning,” as these represent novel targets for understanding this process. For example, neuregulin 4 was more highly expressed in brown adipose tissue and upregulated in white fat upon cold exposure, and cell studies showed that it is a neurite outgrowth-promoting adipokine, indicative of a role in increasing adipose tissue innervation in response to cold. A cell culture system that allows us to reproduce the differential properties of the discrete adipose depots was developed to study depot-specific differences at an in vitro level. The key transcriptional events underpinning white adipose tissue to brown transition are important, as they represent an attractive proposition to overcome the detrimental effects associated with metabolic disorders, including obesity and type 2 diabetes.

Thermodynamics of multicomponent, miscible, ionic solutions. 2. Mixtures including unsymmetrical electrolytes

Abstract: Model equation for the excess Gibbs energy and solvent and solute activity efficients (given previously for symmetrical salt systems) are here developed for mixtures containing an indefinite number of ions of arbitrary charge, over the entire concentration range. The equations are expressed on a mole fraction basis and comprise a Debye-Huckel term extended to include the effects of unsymmetrical mixing, and a Margules expansion carried out to the fow suffix level

Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study

Abstract: Summary Background Clinical prognostic groupings for localised prostate cancers are imprecise, with 30–50% of patients recurring after image-guided radiotherapy or radical prostatectomy. We aimed to test combined genomic and microenvironmental indices in prostate cancer to improve risk stratification and complement clinical prognostic factors. Methods We used DNA-based indices alone or in combination with intra-prostatic hypoxia measurements to develop four prognostic indices in 126 low-risk to intermediate-risk patients (Toronto cohort) who will receive image-guided radiotherapy. We validated these indices in two independent cohorts of 154 (Memorial Sloan Kettering Cancer Center cohort [MSKCC] cohort) and 117 (Cambridge cohort) radical prostatectomy specimens from low-risk to high-risk patients. We applied unsupervised and supervised machine learning techniques to the copy-number profiles of 126 pre-image-guided radiotherapy diagnostic biopsies to develop prognostic signatures. Our primary endpoint was the development of a set of prognostic measures capable of stratifying patients for risk of biochemical relapse 5 years after primary treatment. Findings Biochemical relapse was associated with indices of tumour hypoxia, genomic instability, and genomic subtypes based on multivariate analyses. We identified four genomic subtypes for prostate cancer, which had different 5-year biochemical relapse-free survival. Genomic instability is prognostic for relapse in both image-guided radiotherapy (multivariate analysis hazard ratio [HR] 4·5 [95% CI 2·1–9·8]; p=0·00013; area under the receiver operator curve [AUC] 0·70 [95% CI 0·65–0·76]) and radical prostatectomy (4·0 [1·6–9·7]; p=0·0024; AUC 0·57 [0·52–0·61]) patients with prostate cancer, and its effect is magnified by intratumoral hypoxia (3·8 [1·2–12]; p=0·019; AUC 0·67 [0·61–0·73]). A novel 100-loci DNA signature accurately classified treatment outcome in the MSKCC low-risk to intermediate-risk cohort (multivariate analysis HR 6·1 [95% CI 2·0–19]; p=0·0015; AUC 0·74 [95% CI 0·65–0·83]). In the independent MSKCC and Cambridge cohorts, this signature identified low-risk to high-risk patients who were most likely to fail treatment within 18 months (combined cohorts multivariate analysis HR 2·9 [95% CI 1·4–6·0]; p=0·0039; AUC 0·68 [95% CI 0·63–0·73]), and was better at predicting biochemical relapse than 23 previously published RNA signatures. Interpretation This is the first study of cancer outcome to integrate DNA-based and microenvironment-based failure indices to predict patient outcome. Patients exhibiting these aggressive features after biopsy should be entered into treatment intensification trials. Funding Movember Foundation, Prostate Cancer Canada, Ontario Institute for Cancer Research, Canadian Institute for Health Research, NIHR Cambridge Biomedical Research Centre, The University of Cambridge, Cancer Research UK, Cambridge Cancer Charity, Prostate Cancer UK, Hutchison Whampoa Limited, Terry Fox Research Institute, Princess Margaret Cancer Centre Foundation, PMH-Radiation Medicine Program Academic Enrichment Fund, Motorcycle Ride for Dad (Durham), Canadian Cancer Society.