Extractive Fermentation of Clavulanic Acid by Streptomyces DAUFPE 3060 Using Aqueous Two-Phase System

The influence of four variables, specifically PEG molar mass (400, 1,000, and 8,000 g/mol), concentrations of PEG and phosphate salts (15, 20, and 25% for both), and agitation intensity (110, 150, and 200 rpm), on clavulanic acid (CA) extraction by extractive fermentation with PEG/phosphate salts aqueous two-phase system was investigated in shaken flasks using a 2(4-1)-fractional factorial design. After selection of the two most significant variables (agitation intensity and PEG molar mass), an optimization study conducted according to a 2(2)-central composite design revealed that 25% PEG 8,000 g/mol and phosphate salts at 240 rpm (run 6) were the best conditions for the extractive fermentation, leading to the best results in terms of partition coefficient (k = 8.2), yield of CA in the PEG-rich phase (eta(T) = 93%) and productivity (P = 5.3 mg/Lh). As a first attempt to make a scale-up of these results, the effectiveness of the extractive fermentation was then checked in a bench-scale bioreactor under conditions as close as possible to the optimum ones determined in flasks. The highest CA concentration obtained in the PEG-rich phase (691 mg/L) was 30% higher than in flasks, thus demonstrating the potential of such a new process, integrating the production and extraction steps, as a promising, low-cost tool to obtain high yields of this and similar products. (C) 2010 American Institute of Chemical Engineers Biotechnol. Prog., 27: 95-103, 2011

Endophytic fungi found in association with Smallanthus sonchifolius (Asteraceae) as resourceful producers of cytotoxic bioactive natural products

Smallanthus sonchifolius is a traditional Andean plant which has been cultured mainly in Brazil, Japan and New Zealand due to its medicinal properties. A study of the endophytic fungi associated to the plant was carried out in order to characterize new cytotoxic agents. Thirty two fungal strains were isolated and submitted to cultivation and extraction producing 186 extracts. Of these, 12% displayed moderate to high cytotoxic activities and were considered promising anticancer compound sources. The ethyl acetate fractions of Nigrospora sphaerica and Phoma betae liquid fermentations contained the synergistic compounds 8-hydroxy-6-methoxy-3-methylisocoumarin and (22E,24R)-ergosta-4,6,8(14),22-tetraen-3-one which are potential compounds for drug discovery. Another isolated compound, pimara-7,15-dien-3-beta-ol diterpene is being characterized for the first time through a detailed spectroscopic analysis including GC/MS, homo- and hetero-nuclear correlated NMR experiments (HMQC, HMBC, COSY and NOEdiff) along with its optical rotation.

A Survey on Graphical Methods for Classification Predictive Performance Evaluation

Predictive performance evaluation is a fundamental issue in design, development, and deployment of classification systems. As predictive performance evaluation is a multidimensional problem, single scalar summaries such as error rate, although quite convenient due to its simplicity, can seldom evaluate all the aspects that a complete and reliable evaluation must consider. Due to this, various graphical performance evaluation methods are increasingly drawing the attention of machine learning, data mining, and pattern recognition communities. The main advantage of these types of methods resides in their ability to depict the trade-offs between evaluation aspects in a multidimensional space rather than reducing these aspects to an arbitrarily chosen (and often biased) single scalar measure. Furthermore, to appropriately select a suitable graphical method for a given task, it is crucial to identify its strengths and weaknesses. This paper surveys various graphical methods often used for predictive performance evaluation. By presenting these methods in the same framework, we hope this paper may shed some light on deciding which methods are more suitable to use in different situations.