Detalolactone: A novel pyranocoumarin from the root bark of Zanthoxylum dipetalum

A novel dipyranocoumarin, dipetalolactone {2-oxo-6,6,10,10-tetramethylbenzo[1,2-b:3,4-b′:5,6-b″]tripyran}, has been isolated from the root bark of Zanthoxylum dipetalum and its structure proven by the synthesis of tetrahydrodipetalolactone. A second new pyranocoumarin, dipetaline, has been assigned the tentative structure of 6-(3,3-dimethylallyl)-5-methoxy-2,2-dimethyl-2H-benzo[1,2-b:3,4-b′]dipyran-8-one on the basis of PMR analysis using the lanthanide shift reagent Eu(fod)₃.     

TT232, A Novel Signal Transduction Inhibitory Compound in the Therapy of Cancer and Inflammatory Diseases

TT-232 is a structural analogue of somatostatin exhibiting strong and selective growth-inhibitory effects, inhibition of neurogenic inflammation, as well as general anti-inflammatory and analgesic potential without the wide-ranging endocrine side effects of the parent hormone and its “traditional” analogues. The anti-inflammatory action of TT-232 is mediated through the SSTR4 receptor, and its antitumor activity is mediated through the SSTR1 receptor and by the tumor-specific isoform of pyruvate kinase. Its mechanism of action is in line with a new era of molecular medicine called signal transduction therapy, where “false” intracellular or intercellular communication is inhibited or corrected without interfering with basic cell functions and machinery. TT232 has passed phase I clinical trials without toxicity and significant side effects, and phase II studies are running for oncological and anti-inflammatory indications, respectively. This compound has the perspective to become the first drug in molecularly targeted therapy of inflammation where a combined effect of anti-inflammatory, analgesic, and neurogenic inflammation-inhibiting activity can be achieved.     

Using a logical model to predict the growth of yeast

Background  

A logical model of the known metabolic processes in S. cerevisiae was constructed from iFF708, an existing Flux Balance Analysis (FBA) model, and augmented with information from the KEGG online pathway database. The use of predicate logic as the knowledge representation for modelling enables an explicit representation of the structure of the metabolic network, and enables logical inference techniques to be used for model identification/improvement.