Identifying high-performance catalytic conditions for carbon dioxide reduction to dimethoxymethane by multivariate modelling.

In times of a warming climate due to excessive carbon dioxide production, catalytic conversion of carbon dioxide to formaldehyde is not only a process of great industrial interest, but it could also serve as a means for meeting our climate goals. Currently, formaldehyde is produced in an energetically unfavourable and atom-inefficient process. A much needed solution remains academically challenging. Here we present an algorithmic workflow to improve the ruthenium-catalysed transformation of carbon dioxide to the formaldehyde derivative dimethoxymethane. Catalytic processes are typically optimised by comprehensive screening of catalysts, substrates, reaction parameters and additives to enhance activity and selectivity. The common problem of the multidimensionality of the parameter space, leading to only incremental improvement in laborious physical investigations, was overcome by combining elements from machine learning, optimisation and experimental design, tripling the turnover number of 786 to 2761. The optimised conditions were then used in a new reaction setup tailored to the process parameters leading to a turnover number of 3874, exceeding by far those of known processes.

Metabolomics in toxicology and preclinical research.

Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

Assessment of combinations of antiandrogenic compounds vinclozolin and flutamide in a yeast based reporter assay.

Humans are exposed to a combination of various substances such as cosmetic ingredients, drugs, biocides, pesticides and natural-occurring substances in food. The combined toxicological effects of two or more substances can simply be additive on the basis of response-addition, or it can be greater (synergistic) or smaller (antagonistic) than this. The need to assess combined effects of compounds with endocrine activity is currently discussed for regulatory risk assessment. We have used a well described yeast based androgen receptor transactivation assay YAS to assess the combinatorial effects of vinclozolin and flutamide; both mediating antiandrogenicity via the androgen receptor. Both vinclozolin and flutamide were antiandrogens of similar potency in the YAS assay. In the concentration range tested the two antiandrogens vinclozolin and flutamide did not act synergistically. Concentration additivity was observed in the linear, non-receptor-saturated concentration range. At high concentrations of one of the two substances tested the contribution of the second at lower concentration levels was less than additive. The combined response of both compounds at high concentration levels was also less than additive (saturation effect). At concentration levels which did not elicit a response of the individual compounds, the combination of these compounds also did not elicit a response.