A Dutch Approach to the European Directive on Integrated Pollution Prevention and Control: Using Life-Cycle Assessment for the Integrated Assessment of Technologies

In light of the European Directive on Integrated Pollution Prevention and Control (IPPC Directive), traditional environmental regulation can be improved using the framework of industrial ecology. The objective of the IPPC Directive is to achieve a high level of protection of the environment as a whole (Article 1) by applying the best available techniques (BAT). In essence, the IPPC Directive obliges member states of the European Union to include considerations such as resources, energy, waste, and multimedia emissions when permitting industrial installations. This is a marked contrast to traditional environmental regulation that focuses on individual media of an individual site. In order to take all considerations into account, an integrated assessment of technologies is needed, for which a standard method is currently lacking.
In this article, a systematic approach is introduced for the integrated assessment of IPPC technologies using life-cycle assessment (LCA), a form of environmental assessment that can be broadened to an overall assessment of environmental, economic, and social aspects. This systematic approach has proven to be successful for the environmental assessment of the described cases. It is suggested here that weighting can be omitted for the evaluation of IPPC technologies. Leaving the weighting step to competent authorities of member states and allowing them to consider local issues provides maximum opportunity for the subsidiarity and flexibility principles of the IPPC Directive.     

Combining Machine Learning Systems and Multiple Docking Simulation Packages to Improve Docking Prediction Reliability for Network Pharmacology

Increased availability of bioinformatics resources is creating opportunities for the application of network pharmacology to predict drug effects and toxicity resulting from multi-target interactions. Here we present a high-precision computational prediction approach that combines two elaborately built machine learning systems and multiple molecular docking tools to assess binding potentials of a test compound against proteins involved in a complex molecular network. One of the two machine learning systems is a re-scoring function to evaluate binding modes generated by docking tools. The second is a binding mode selection function to identify the most predictive binding mode. Results from a series of benchmark validations and a case study show that this approach surpasses the prediction reliability of other techniques and that it also identifies either primary or off-targets of kinase inhibitors. Integrating this approach with molecular network maps makes it possible to address drug safety issues by comprehensively investigating network-dependent effects of a drug or drug candidate.     

Integration of Zebrafish Model and Network Pharmacology to Explore Possible Action Mechanisms of Morinda officinalis for Treating Osteoporosis

Osteoporosis (OP) is a metabolic bone disease affecting nearly 200 million individuals globally. Morinda officinalis F.C.How (MOH) has long been used as a traditional herbal medicine for the treatment of bone fractures and joint diseases in China. However, it still remains unclear how the compounds in MOH work synergistically for treating OP. In this study, we used prednisolone (PNSL)‐induced zebrafish OP model to screen the antiosteoporosis components in MOH. A network pharmacology approach was further proposed to explore the underlying mechanism of MOH on OP. The PNSL‐induced zebrafish model validated that two anthraquinones, one iridoid glycoside, and two saccharides exerted antiosteoporotic effect. We constructed the components‐targets network and obtained the enriched Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. A total of 26 candidate compounds of MOH and 257 related targets could probably treat OP through regulating osteoclast differentiation and MAPK signaling pathway. Our work developed a strategy to screen the antiosteoporosis components and explore the underlying mechanism of MOH for treating OP at a network pharmacology level.     

Statistical and Artificial Neural Network Approaches to Modeling and Optimization of Fermentation Conditions for Production of a Surface/Bioactive Glyco-lipo-peptide

International Journal of Peptide Research and Therapeutics - A freshwater alkaliphilic strain of Pseudomonas aeruginosa, grown on waste frying oil-basal medium, produced a surface-active metabolite...