A framework for assessing urban greenery's effects and valuing its ecosystem services.

Ongoing urban exploitation is increasing pressure to transform urban green spaces, while there is increasing awareness that greenery provides a range of important benefits to city residents. In efforts to help resolve associated problems we have developed a framework for integrated assessments of ecosystem service (ES) benefits and values provided by urban greenery, based on the ecosystem service cascade model. The aim is to provide a method for assessing the contribution to, and valuing, multiple ES provided by urban greenery that can be readily applied in routine planning processes. The framework is unique as it recognizes that an urban greenery comprises several components and functions that can contribute to multiple ecosystem services in one or more ways via different functional traits (e.g. foliage characteristics) for which readily measured indicators have been identified. The framework consists of five steps including compilation of an inventory of indicator; application of effectivity factors to rate indicators' effectiveness; estimation of effects; estimation of benefits for each ES; estimation of the total ES value of the ecosystem. The framework was applied to assess ecosystem services provided by trees, shrubs, herbs, birds, and bees, in green areas spanning an urban gradient in Gothenburg, Sweden. Estimates of perceived values of ecosystem services were obtained from interviews with the public and workshop activities with civil servants. The framework is systematic and transparent at all stages and appears to have potential utility in the existing spatial planning processes.

Automated annotation and quantification of metabolites in 1H NMR data of biological origin.

In (1)H NMR metabolomic datasets, there are often over a thousand peaks per spectrum, many of which change position drastically between samples. Automatic alignment, annotation, and quantification of all the metabolites of interest in such datasets have not been feasible. In this work we propose a fully automated annotation and quantification procedure which requires annotation of metabolites only in a single spectrum. The reference database built from that single spectrum can be used for any number of (1)H NMR datasets with a similar matrix. The procedure is based on the generalized fuzzy Hough transform (GFHT) for alignment and on Principal-components analysis (PCA) for peak selection and quantification. We show that we can establish quantities of 21 metabolites in several (1)H NMR datasets and that the procedure is extendable to include any number of metabolites that can be identified in a single spectrum. The procedure speeds up the quantification of previously known metabolites and also returns a table containing the intensities and locations of all the peaks that were found and aligned but not assigned to a known metabolite. This enables both biopattern analysis of known metabolites and data mining for new potential biomarkers among the unknowns.

In situ mass spectrometry imaging and ex vivo characterization of renal crystalline deposits induced in multiple preclinical drug toxicology studies.

Drug toxicity observed in animal studies during drug development accounts for the discontinuation of many drug candidates, with the kidney being a major site of tissue damage. Extensive investigations are often required to reveal the mechanisms underlying such toxicological events and in the case of crystalline deposits the chemical composition can be problematic to determine. In the present study, we have used mass spectrometry imaging combined with a set of advanced analytical techniques to characterize such crystalline deposits in situ. Two potential microsomal prostaglandin E synthase 1 inhibitors, with similar chemical structure, were administered to rats over a seven day period. This resulted in kidney damage with marked tubular degeneration/regeneration and crystal deposits within the tissue that was detected by histopathology. Results from direct tissue section analysis by matrix-assisted laser desorption ionization mass spectrometry imaging were combined with data obtained following manual crystal dissection analyzed by liquid chromatography mass spectrometry and nuclear magnetic resonance spectroscopy. The chemical composition of the crystal deposits was successfully identified as a common metabolite, bisulphonamide, of the two drug candidates. In addition, an un-targeted analysis revealed molecular changes in the kidney that were specifically associated with the area of the tissue defined as pathologically damaged. In the presented study, we show the usefulness of combining mass spectrometry imaging with an array of powerful analytical tools to solve complex toxicological problems occurring during drug development.