Synthesis of 12-aminododecenoic acid by coupling transaminase to oxylipin pathway enzymes.

Biobased polymers derived from plant oils are sustainable alternatives to petro based polymers. In recent years, multienzyme cascades have been developed for the synthesis of biobased ω-aminocarboxylic acids, which serve as building blocks for polyamides. In this work, we have developed a novel enzyme cascade for the synthesis of 12-aminododeceneoic acid, a precursor for nylon-12, starting from linoleic acid.

Synthesis of Polymer Precursor 12-Oxododecenoic Acid Utilizing Recombinant Papaya Hydroperoxide Lyase in an Enzyme Cascade.

Hydroperoxide lyases (HPLs) catalyze the splitting of 13S-hydroperoxyoctadecadienoic acid (13S-HPODE) into the green note flavor hexanal and 12-oxo-9(Z)-dodecenoic acid, which is not yet used industrially. Here, HPL from Carica papaya (HPL) was cloned and functionally expressed in Escherichia coli to investigate synthesis of 12-oxo-9(Z)-dodecenoic acid in detail. To improve the low catalytic activity of full-length HPL, the hydrophobic, non-conserved N-terminal sequence was deleted.

Formation of cyclic structures in the cationic ring-opening polymerization of 1,3-dioxolane.

The cationic ring-opening polymerization of acetals is prone to cyclization of the polymer chains. This is also the case for the polymerization of 1,3-dioxolane. Literature states that this cyclization can be reduced by applying the Active Monomer mechanism, at least if no competition with the Active Chain End mechanism occurs.

Identification of LcpRB, a novel regulator of lcp expression in Streptomyces coelicolor A3(2).

Streptomyces coelicolor A3(2) is a rubber-degrading actinomycete that harbors one gene coding for a latex clearing protein (lcp). Within the genome of S. coelicolor A3(2), we identified a gene coding for a novel protein of the TetR family (LcpRB) downstream of lcp and demonstrated its binding upstream of lcp.

Testing one or multiple: How beliefs about sparsity affect causal experimentation.

What is the best way of discovering the underlying structure of a causal system composed of multiple variables? One prominent idea is that learners should manipulate each candidate variable in isolation to avoid confounds (sometimes known as the control of variables [CV] strategy). We demonstrate that CV is not always the most efficient method for learning. Using an optimal actor model, which aims to minimize the average number of tests, we show that when a causal system is sparse (i.

LcpRVH2 - regulating the expression of latex-clearing proteins in Gordonia polyisoprenivorans VH2.

Gordonia polyisoprenivorans VH2 harbours two latex clearing proteins, which are responsible for the cleavage of poly(cis-1,4-isoprene) into oligoisoprenes, thereby allowing growth in presence of, e.g. natural rubber.

Elastic materials for tissue engineering applications: Natural, synthetic, and hybrid polymers.

Unlabelled: Elastin and collagen are the two main components of elastic tissues and provide the tissue with elasticity and mechanical strength, respectively. Whereas collagen is adequately produced in vitro, production of elastin in tissue-engineered constructs is often inadequate when engineering elastic tissues. Therefore, elasticity has to be artificially introduced into tissue-engineered scaffolds.

Asking the right questions about the psychology of human inquiry: Nine open challenges.

The ability to act on the world with the goal of gaining information is core to human adaptability and intelligence. Perhaps the most successful and influential account of such abilities is the Optimal Experiment Design (OED) hypothesis, which argues that humans intuitively perform experiments on the world similar to the way an effective scientist plans an experiment. The widespread application of this theory within many areas of psychology calls for a critical evaluation of the theory's core claims.

Strategies to intervene on causal systems are adaptively selected.

How do people choose interventions to learn about causal systems? Here, we considered two possibilities. First, we test an information sampling model, information gain, which values interventions that can discriminate between a learner's hypotheses (i.e.