Possible pre-dissociation of diorganotin dihalide complexes: relationship between antitumour activity and structure

An examination of crystallographic data has indicated that the structure/activity relationship for diorganotin dihalide complexes is different from that of other metal dihalides, in that the SnN bond lengths appear to determine the antitumour activity.

Formal total synthesis of (±)-conduramine E utilising the Bryce-Smith-Gilbert photoamination reaction

Utilising a Bryce-Smith-Gilbert photoamination of benzene as a key step, a synthesis of ()-conduramine E was carried out. A highly regioselective dihydroxylation of a cyclic diene was effected utilising Sharpless AD-mix-b.

Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

Trends in office rents in the City of London: 1867-1959

This paper details the construction and analysis of a dataset of office lettings, which is used to produce a rent index for the City of London spanning the late nineteenth and early twentieth centuries. It advances prior research through application of a modern version of the repeat measures technique and in coverage of years where office rents have not been previously measured. Results show that there has been no real growth in rents over the period as a whole. However, there have been distinct phases of rental growth and decline that correspond with the wider economic fortunes of the City.

Identifying human influences on atmospheric temperature

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the finger-print) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.