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1.
Regul Toxicol Pharmacol ; 83: 109-116, 2017 Feb.
Article in English | MEDLINE | ID: mdl-27871869

ABSTRACT

This paper describes the further development of a read-across approach applicable to the toxicological assessment of structurally-related xenobiotic metabolites. The approach, which can be applied in the absence of definitive identification of all the individual metabolites, draws on the use of chemical descriptors and multi-variate statistical analysis to define a composite "chemical space" and to classify and characterize closely-related subgroups within this. In this example, consideration of the descriptors driving grouping, combined with empirical evidence for lack of significant further biotransformation of metabolites, leads to the conclusion that, in the absence of any specific structural alerts, the relative toxicity of metabolites within a single grouping will be determined by their relative systemic exposure as described by their ADME characteristics. The in vivo testing of a smaller number of exemplars, selected to have representative ADME properties for each grouping, is sufficient, therefore, to evaluate the toxicity of the remainder. The approach is exemplified using the metabolites of the herbicide S-metolachlor, detected in the leachate of a soil lysimeter.


Subject(s)
Acetamides/toxicity , Environmental Monitoring/instrumentation , Soil Pollutants/pharmacokinetics , Soil Pollutants/toxicity , Toxicity Tests/methods , Toxicokinetics , Xenobiotics/toxicity , Acetamides/chemistry , Acetamides/classification , Acetamides/pharmacokinetics , Animals , Biotransformation , Environmental Exposure/adverse effects , Environmental Monitoring/methods , Humans , Models, Chemical , Models, Statistical , Molecular Structure , Multivariate Analysis , Principal Component Analysis , Risk Assessment , Soil Pollutants/chemistry , Soil Pollutants/classification , Structure-Activity Relationship , Xenobiotics/chemistry , Xenobiotics/classification , Xenobiotics/pharmacokinetics
2.
Environ Toxicol Chem ; 35(6): 1401-12, 2016 06.
Article in English | MEDLINE | ID: mdl-26627902

ABSTRACT

Lysimeter studies can be used to identify and quantify soil degradates of agrochemicals (metabolites) that have the potential to leach to groundwater. However, the apparent metabolic profile of such lysimeter leachate samples will often be significantly more complex than would be expected in true groundwater samples. This is particularly true for S-metolachlor, which has an extremely complex metabolic pathway. Consequently, it was not practically possible to apply a conventional analytical approach to identify all metabolites in an S-metolachlor lysimeter study, because there was insufficient mass to enable the use of techniques such as nuclear magnetic resonance. Recent advances in high-resolution accurate mass spectrometry, however, allow innovative screening approaches to characterize leachate samples to a greater extent than previously possible. Leachate from the S-metolachlor study was screened for accurate masses (±5 ppm of the nominal mass) corresponding to more than 400 hypothetical metabolite structures. A refined list of plausible metabolites was constructed from these data to provide a comprehensive description of the most likely metabolites present. The properties of these metabolites were then evaluated using a principal component analysis model, based on molecular descriptors, to visualize the entire chemical space and to cluster the metabolites into a number of subclasses. This characterization and principal component analysis evaluation enabled the selection of suitable representative metabolites that were subsequently used as exemplars to assess the toxicological relevance of the leachate as a whole. Environ Toxicol Chem 2016;35:1401-1412. © 2015 SETAC.


Subject(s)
Acetamides/analysis , Agrochemicals/analysis , Groundwater/chemistry , Mass Spectrometry/methods , Soil , Water Pollutants, Chemical/analysis , Acetamides/chemistry , Agrochemicals/chemistry , Databases, Factual , Models, Theoretical , Principal Component Analysis , Sensitivity and Specificity , Soil/chemistry , Soil/standards , Water Pollutants, Chemical/chemistry
3.
Phytochem Anal ; 22(3): 214-24, 2011.
Article in English | MEDLINE | ID: mdl-21204151

ABSTRACT

INTRODUCTION: High salinity, caused by either natural (e.g. climatic changes) or anthropic factors (e.g. agriculture), is a widespread environmental stressor that can affect development and growth of salt-sensitive plants, leading to water deficit, the inhibition of intake of essential ions and metabolic disorders. OBJECTIVE: The application of an NMR-based metabolic profiling approach to the investigation of saline-induced stress in Maize plants is presented. METHODOLOGY: Zea Maize seedlings were grown in either 0, 50 or 150 mM saline solution. Plants were harvested after 2, 4 and 6 days (n = 5 per class and time point) and (1) H NMR spectroscopy was performed separately on shoot and root extracts. Spectral data were analysed and interpreted using multivariate statistical analyses. RESULTS: A distinct effect of time/growth was observed for the control group with relatively higher concentrations of acetoacetate at day 2 and increased levels of alanine at days 4 and 6 in root extracts, whereas concentration of alanine was positively correlated with the shoot extracts harvested at day 2 and trans-aconitic acid increased at days 4 and 6. A clear dose-dependent effect, superimposed on the growth effect, was observed for saline treated shoot and root extracts. This was correlated with increased levels of alanine, glutamate, asparagine, glycine-betaine and sucrose and decreased levels of malic acid, trans-aconitic acid and glucose in shoots. Correlation with salt-load shown in roots included elevated levels of alanine, γ-amino-N-butyric acid, malic acid, succinate and sucrose and depleted levels of acetoacetate and glucose. CONCLUSIONS: The metabolic effect of high salinity was predominantly consistent with osmotic stress as reported for other plant species and was found to be stronger in the shoots than the roots. Using multivariate data analysis it is possible to investigate the effects of more than one environmental stressor simultaneously.


Subject(s)
Magnetic Resonance Spectroscopy/methods , Metabolomics/methods , Plant Extracts/chemistry , Sodium Chloride/pharmacology , Zea mays/chemistry , Zea mays/metabolism , Hydroponics , Least-Squares Analysis , Osmotic Pressure , Plant Roots/chemistry , Plant Shoots/chemistry , Salinity , Seedlings/chemistry , Seedlings/drug effects , Seedlings/metabolism , Stress, Physiological , Time Factors , Water/metabolism , Zea mays/drug effects
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