Synthesis of medium-chain-length polyhydroxyalkanoates in arabidopsis thaliana using intermediates of peroxisomal fatty acid beta-oxidation.

Polyhydroxyalkanoate (PHA) is a family of polymers composed primarily of R-3-hydroxyalkanoic acids. These polymers have properties of biodegradable thermoplastics and elastomers. Medium-chain-length PHAs (MCL-PHAs) are synthesized in bacteria by using intermediates of the beta-oxidation of alkanoic acids. To assess the feasibility of producing MCL-PHAs in plants, Arabidopsis thaliana was transformed with the PhaC1 synthase from Pseudomonas aeruginosa modified for peroxisome targeting by addition of the carboxyl 34 amino acids from the Brassica napus isocitrate lyase. Immunocytochemistry demonstrated that the modified PHA synthase was appropriately targeted to leaf-type peroxisomes in light-grown plants and glyoxysomes in dark-grown plants. Plants expressing the PHA synthase accumulated electron-lucent inclusions in the glyoxysomes and leaf-type peroxisomes, as well as in the vacuole. These inclusions were similar to bacterial PHA inclusions. Analysis of plant extracts by GC and mass spectrometry demonstrated the presence of MCL-PHA in transgenic plants to approximately 4 mg per g of dry weight. The plant PHA contained saturated and unsaturated 3-hydroxyalkanoic acids ranging from six to 16 carbons with 41% of the monomers being 3-hydroxyoctanoic acid and 3-hydroxyoctenoic acid. These results indicate that the beta-oxidation of plant fatty acids can generate a broad range of R-3-hydroxyacyl-CoA intermediates that can be used to synthesize MCL-PHAs.

Effect of cAMP on macromolecule synthesis in the pathogenic protozoa Trypanosoma cruzi

Macromolecule synthesis of Trypanosoma cruzi in culture was monitored using radioactive tracers. Cells of different days in culture displayed a preferential incorporation of precursors as follows: 1 day for (³H)-thymidine cells; 3 days for (³H)-uridine cells, and 4 days for (³H)-leucine cells. Autoradiographic studies showed that (³H)-thymidine was incorporated in the DNA of both kinetoplast and nucleus in this order. Shifts in the intracellular content of cAMP either by addition of dibutyryl-cAMP or by stimulation of the adenylcyclase by isoproterenol, caused an inhibition in the synthesis of DNA, RNA and proteins. Addition to the T. cruzi cultures of these agents which elevate the intracellular content ofcAMP provoked an interruption of cell proliferation as a result of the impairment of macromolecule synthesis. A discrimination was observed among the stereoisomers of isoproterenol, the L configuration showing to be most active.

Urban image classification with semisupervised multiscale cluster kernels

This paper presents a semisupervised support vector machine (SVM) that integrates the information of both labeled and unlabeled pixels efficiently. Method's performance is illustrated in the relevant problem of very high resolution image classification of urban areas. The SVM is trained with the linear combination of two kernels: a base kernel working only with labeled examples is deformed by a likelihood kernel encoding similarities between labeled and unlabeled examples. Results obtained on very high resolution (VHR) multispectral and hyperspectral images show the relevance of the method in the context of urban image classification. Also, its simplicity and the few parameters involved make the method versatile and workable by unexperienced users.

Combinatorial Synthesis and Biological Evaluation of Inhibitors of D-Ala-D-Ala-Ligase

Report for the scientific sojourn carried out at the Max Planck Institut of Molecular Phisiology, Germany, from 2006 to 2008.The work carried out during this postdoctoral stage was focused on two different projects. Firstly, identification of D-Ala D-Ala Inhibitors and the development of new synthethic approaches to obtain lipidated peptides and proteins and the use of these lipidated proteins in biological and biophysical studies. In the first project, new D-Ala D-Ala inhibitors were identified by using structural alignments of the ATP binding sites of the bacterial ligase DDl and protein and lipid kinases in complex with ATP analogs. We tested a series of commercially available kinase inhibitors and found LFM-A13 and Tyrphostine derivatives to inhibit DDl enzyme activity. Based on the initial screening results we synthesized a series of malononitrilamide and salicylamide derivatives and were able to confirm the validity of these scaffolds as inhibitors of DDl. From this investigation we gained a better understanding of the structural requirements and limitations necessary for the preparation of ATP competitive DDl inhibitors. The compounds in this study may serve as starting points for the development of bi-substrate inhibitors that incorporate both, an ATP competitive and a substrate competitive moiety. Bisubstrate inhibitors that block the ATP and D-Ala binding sites should exhibit enhanced selectivity and potency profiles by preferentially inhibiting DDl over kinases. In the second project, an optimized synthesis for tha alkylation of cysteins using the thiol ene reaction was establisehd. This new protocol allowed us to obtain large amounts of hexadecylated cysteine that was required for the synthesis of differently lipidated peptides. Afterwards the synthesis of various N-ras peptides bearing different lipid anchors was performed and the peptides were ligated to a truncated N-ras protein. The influence of this differently lipidated N-ras proteins on the partioning and association of N-Ras in model membrane subdomains was studied using Atomic Force Microscopy.

Solid-phase synthesis and NMR studies of modified oligonucleotides forming triplex helix and of oligonucleopeptides mimicking the topoisomerase I-DNA covalent complex

Report for the scientific sojourn carried out at the Institut de Biologia Molecular de Barcelona of the CSIC –state agency – from april until september 2007. Topoisomerase I is an essential nuclear enzyme that modulates the topological status of DNA, facilitating DNA helix unwinding during replication and transcription. We have prepared the oligonucleotide-peptide conjugate Ac-NLeu-Asn-Tyr(p-3’TTCAGAAGC5’)-LeuC-CONH-(CH2)6-OH as model compound for NMR studies of the Topoisomerase I- DNA complex. Special attention was made on the synthetic aspects for the preparation of this challenging compound especially solid supports and protecting groups. The desired peptide was obtained although we did not achieve the amount of the conjugate needed for NMR studies. Most probably the low yield is due to the intrinsic sensitive to hydrolysis of the phosphate bond between oligonucleotide and tyrosine. We have started the synthesis and the structural characterization of oligonucleotides carrying intercalating compounds. At the present state we have obtained model duplex and quadruplex sequences modified with acridine and NMR studies are underway. In addition to this project we have successfully resolved the structure of a fusion peptide derived from hepatitis C virus envelope synthesized by the group of Dr. Haro and we have synthesized and started the characterization of a modified G-quadruplex.

Imaging liver and brain glycogen metabolism at the nanometer scale.

In mammals, glycogen synthesis and degradation are dynamic processes regulating blood and cerebral glucose-levels within a well-defined physiological range. Despite the essential role of glycogen in hepatic and cerebral metabolism, its spatiotemporal distribution at the molecular and cellular level is unclear. By correlating electron microscopy and ultra-high resolution ion microprobe (NanoSIMS) imaging of tissue from fasted mice injected with (13)C-labeled glucose, we demonstrate that liver glycogenesis initiates in the hepatocyte perinuclear region before spreading toward the cell membrane. In the mouse brain, we observe that (13)C is inhomogeneously incorporated into astrocytic glycogen at a rate ~25 times slower than in the liver, in agreement with prior bulk studies. This experiment, using temporally resolved, nanometer-scale imaging of glycogen synthesis and degradation, provides greater insight into glucose metabolism in mammalian organs and shows how this technique can be used to explore biochemical pathways in healthy and diseased states. FROM THE CLINICAL EDITOR: By correlating electron microscopy and ultra-high resolution ion microprobe imaging of tissue from fasting mice injected with (13)C-labeled glucose, the authors demonstrate a method to image glycogen metabolism at the nanometer scale.

Stereoselective total synthesis of some insect pheromones: (±)-serricornine and (±)-invictolide

An efficient (12 steps, 12% overallyield) and stereoselective total synthesis of (±)-serricornine (1) the sex pheromone of the cigarette beetle (Lasioderma serricornine F) is described. The preparation of intermediate 5, which encompasses the proper relative configuration of three contiguous chiral centers of (±)-invictolide, (3), is discussed.

Methodology in structural determination and synthesis of insect pheromone

By means of ethereal washing of insect pheromone glands of female moths, GC-MS detection along with microchemical reactions and electroantennogram (EAG) survey, six economically important insect species were targeted for pheromone identification. The discovery of a natural pheromone inhibitor, chemo-selectivity and species isolation by pheromone will be described. The modified triple bond migration and triethylamine liganded vinyl cuprate were applied for achiral pheromone synthesis in double bond formation. Some optically active pheromones and their stereoisomers were synthesized through chiral pool or asymmetric synthesis. Some examples of chiral recognition of insects towards their chiral pheromones will be discussed. A CaH2 and silica gel catalyzed Sharpless Expoxidation Reaction was found in shortening the reaction time.

Some variational problems from image processing

"Vegeu el resum a l'inici del document del fitxer adjunt."

Generating controlled image sets in cognitive neuroscience research.

The investigation of perceptual and cognitive functions with non-invasive brain imaging methods critically depends on the careful selection of stimuli for use in experiments. For example, it must be verified that any observed effects follow from the parameter of interest (e.g. semantic category) rather than other low-level physical features (e.g. luminance, or spectral properties). Otherwise, interpretation of results is confounded. Often, researchers circumvent this issue by including additional control conditions or tasks, both of which are flawed and also prolong experiments. Here, we present some new approaches for controlling classes of stimuli intended for use in cognitive neuroscience, however these methods can be readily extrapolated to other applications and stimulus modalities. Our approach is comprised of two levels. The first level aims at equalizing individual stimuli in terms of their mean luminance. Each data point in the stimulus is adjusted to a standardized value based on a standard value across the stimulus battery. The second level analyzes two populations of stimuli along their spectral properties (i.e. spatial frequency) using a dissimilarity metric that equals the root mean square of the distance between two populations of objects as a function of spatial frequency along x- and y-dimensions of the image. Randomized permutations are used to obtain a minimal value between the populations to minimize, in a completely data-driven manner, the spectral differences between image sets. While another paper in this issue applies these methods in the case of acoustic stimuli (Aeschlimann et al., Brain Topogr 2008), we illustrate this approach here in detail for complex visual stimuli.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.