NMR spectrum of lindgomycin from a Marine Fungus of the Lindgomycetaceae

An unusual polyketide with a new carbon skeleton, lindgomycin (1), and the recently described ascosetin (2) were extracted from mycelia and culture broth of different Lindgomycetaceae strains, which were isolated from a sponge of the Kiel Fjord in the Baltic Sea (Germany) and from the Antarctic. Their structures were established by spectroscopic means. In the new polyketide, two distinct domains, a bicyclic hydrocarbon and a tetramic acid, are connected by a bridging carbonyl. The tetramic acid substructure of compound 1 was proved to possess a unique 5-benzylpyrrolidine-2,4-dione unit. The combination of 5-benzylpyrrolidine-2,4-dione of compound 1 in its tetramic acid half and 3-methylbut-3-enoic acid pendant in its decalin half allow the assignment of a new carbon skeleton. The new compound 1 and ascosetin showed antibiotic activities with IC50 value of 5.1 (±0.2) µM and 3.2 (±0.4) µM, respectively, against methicillin-resistant Staphylococcus aureus.

Time series of ZOOSCAN images and results of zooplankton samples at Villefranche from 1966 to 2003

ZooScan with ZooProcess and Plankton Identifier (PkID) software is an integrated analysis system for acquisition and classification of digital zooplankton images from preserved zooplankton samples. Zooplankton samples are digitized by the ZooScan and processed by ZooProcess and PkID in order to detect, enumerate, measure and classify the digitized objects. Here we present a semi-automatic approach that entails automated classification of images followed by manual validation, which allows rapid and accurate classification of zooplankton and abiotic objects. We demonstrate this approach with a biweekly zooplankton time series from the Bay of Villefranche-sur-mer, France. The classification approach proposed here provides a practical compromise between a fully automatic method with varying degrees of bias and a manual but accurate classification of zooplankton. We also evaluate the appropriate number of images to include in digital learning sets and compare the accuracy of six classification algorithms. We evaluate the accuracy of the ZooScan for automated measurements of body size and present relationships between machine measures of size and C and N content of selected zooplankton taxa. We demonstrate that the ZooScan system can produce useful measures of zooplankton abundance, biomass and size spectra, for a variety of ecological studies.