820 research outputs found

    Ruthenacycles and Iridacycles as Catalysts for Asymmetric Transfer Hydrogenation and Racemisation

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    Ruthenacycles, which are easily prepared in a single step by reaction between enantiopure aromatic amines and [Ru(arene)Cl2]2 in the presence of NaOH and KPF6, are very good asymmetric transfer hydrogenation catalysts. A range of aromatic ketones were reduced using isopropanol in good yields with ee’s up to 98%. Iridacycles, which are prepared in similar fashion from [IrCp*Cl2]2 are excellent catalysts for the racemisation of secondary alcohols and chlorohydrins at room temperature. This allowed the development of a new dynamic kinetic resolution of chlorohydrins to the enantiopure epoxides in up to 90% yield and 98% enantiomeric excess (ee) using a mutant of the enzyme Haloalcohol dehalogenase C and an iridacycle as racemisation catalyst.

    Probabilistic machine learning and artificial intelligence.

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    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

    Spatial heterogeneity of habitat suitability for Rift Valley fever occurrence in Tanzania: an ecological niche modelling approach

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    Despite the long history of Rift Valley fever (RVF) in Tanzania, extent of its suitable habitat in the country remains unclear. In this study we investigated potential effects of temperature, precipitation, elevation, soil type, livestock density, rainfall pattern, proximity to wild animals, protected areas and forest on the habitat suitability for RVF occurrence in Tanzania. Presence-only records of 193 RVF outbreak locations from 1930 to 2007 together with potential predictor variables were used to model and map the suitable habitats for RVF occurrence using ecological niche modelling. Ground-truthing of the model outputs was conducted by comparing the levels of RVF virus specific antibodies in cattle, sheep and goats sampled from locations in Tanzania that presented different predicted habitat suitability values. Habitat suitability values for RVF occurrence were higher in the northern and central-eastern regions of Tanzania than the rest of the regions in the country. Soil type and precipitation of the wettest quarter contributed equally to habitat suitability (32.4% each), followed by livestock density (25.9%) and rainfall pattern (9.3%). Ground-truthing of model outputs revealed that the odds of an animal being seropositive for RVFV when sampled from areas predicted to be most suitable for RVF occurrence were twice the odds of an animal sampled from areas least suitable for RVF occurrence (95% CI: 1.43, 2.76, p < 0.001). The regions in the northern and central-eastern Tanzania were more suitable for RVF occurrence than the rest of the regions in the country. The modelled suitable habitat is characterised by impermeable soils, moderate precipitation in the wettest quarter, high livestock density and a bimodal rainfall pattern. The findings of this study should provide guidance for the design of appropriate RVF surveillance, prevention and control strategies which target areas with these characteristics

    Breast cancer incidence, stage, treatment and survival in ethnic groups in South East England

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    Studies from the US have shown variations in breast cancer incidence, stage distribution, treatment and survival between ethnic groups. Data on 35 631 women diagnosed with breast cancer in South East England between 1998 and 2003 with self-assigned ethnicity information available were analysed. Results are reported for White, Indian, Pakistani, Bangladeshi, Black Caribbean, Black African and Chinese women. Age-standardised breast cancer incidence rate ratios, patterns of stage of disease at diagnosis, treatment, overall and breast cancer-specific survival were examined. All ethnic groups studied had lower age-standardised breast cancer incidence rates than White women, with Bangladeshi women having the lowest rate ratio (0.23, 95% CI: 0.20–0.26). White women were the most likely to have a stage recorded at diagnosis (adjusted proportion 75%), and least likely to be diagnosed with metastatic disease (7%). Black African women were the least likely to have a record of cancer surgery (63%) or hormone therapy (32%), and most likely to receive chemotherapy (38%). After fully adjusting for age, socioeconomic deprivation, stage of disease and treatment received, there was no significant variation in breast cancer-specific survival. However, Black African women had significantly worse overall survival (hazard ratio 1.24, P=0.025). These findings suggest that a strategy of earlier detection should be pursued in Black and South Asian women

    Alterations of the extracellular matrix in ovarian cancer studied by Second Harmonic Generation imaging microscopy

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    <p>Abstract</p> <p>Background</p> <p>Remodeling of the extracellular matrix (ECM) has been implicated in ovarian cancer, and we hypothesize that these alterations may provide a better optical marker of early disease than currently available imaging/screening methods and that understanding their physical manifestations will provide insight into invasion.</p> <p>Methods</p> <p>For this investigation we use Second Harmonic Generation (SHG) imaging microcopy to study changes in the structure of the ovarian ECM in human normal and malignant ex vivo biopsies. This method directly visualizes the type I collagen in the ECM and provides quantitative metrics of the fibrillar assembly. To quantify these changes in collagen morphology we utilized an integrated approach combining 3D SHG imaging measurements and bulk optical parameter measurements in conjunction with Monte Carlo simulations of the experimental data to extract tissue structural properties.</p> <p>Results</p> <p>We find the SHG emission attributes (directionality and relative intensity) and bulk optical parameters, both of which are related to the tissue structure, are significantly different in the tumors in a manner that is consistent with the change in collagen assembly. The normal and malignant tissues have highly different collagen fiber assemblies, where collectively, our findings show that the malignant ovaries are characterized by lower cell density, denser collagen, as well as higher regularity at both the fibril and fiber levels. This further suggests that the assembly in cancer may be comprised of newly synthesized collagen as opposed to modification of existing collagen.</p> <p>Conclusions</p> <p>Due to the large structural changes in tissue assembly and the SHG sensitivity to these collagen alterations, quantitative discrimination is achieved using small patient data sets. Ultimately these measurements may be developed as intrinsic biomarkers for use in clinical applications.</p

    Interplay between CD8α+ Dendritic Cells and Monocytes in Response to Listeria monocytogenes Infection Attenuates T Cell Responses

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    During the course of a microbial infection, different antigen presenting cells (APCs) are exposed and contribute to the ensuing immune response. CD8α+ dendritic cells (DCs) are an important coordinator of early immune responses to the intracellular bacteria Listeria monocytogenes (Lm) and are crucial for CD8+ T cell immunity. In this study, we examine the contribution of different primary APCs to inducing immune responses against Lm. We find that CD8α+ DCs are the most susceptible to infection while plasmacytoid DCs are not infected. Moreover, CD8α+ DCs are the only DC subset capable of priming an immune response to Lm in vitro and are also the only APC studied that do so when transferred into β2 microglobulin deficient mice which lack endogenous cross-presentation. Upon infection, CD11b+ DCs primarily secrete low levels of TNFα while CD8α+ DCs secrete IL-12 p70. Infected monocytes secrete high levels of TNFα and IL-12p70, cytokines associated with activated inflammatory macrophages. Furthermore, co-culture of infected CD8α+ DCs and CD11b+ DCs with monocytes enhances production of IL-12 p70 and TNFα. However, the presence of monocytes in DC/T cell co-cultures attenuates T cell priming against Lm-derived antigens in vitro and in vivo. This suppressive activity of spleen-derived monocytes is mediated in part by both TNFα and inducible nitric oxide synthase (iNOS). Thus these monocytes enhance IL-12 production to Lm infection, but concurrently abrogate DC-mediated T cell priming
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