Cortistain is expressed in a distinct subset of cortical interneurons

Cortistatin is a presumptive neuropeptide that shares 11 of its 14 amino acids with somatostatin. In contrast to somatostatin, administration of cortistatin into the rat brain ventricles specifically enhances slow wave sleep, apparently by antagonizing the effects of acetylcholine on cortical excitability. Here we show that preprocortistatin mRNA is expressed in a subset of GABAergic cells in the cortex and hippocampus that partially overlap with those containing somatostatin. A significant percentage of cortistatin-positive neurons is also positive for parvalbumin. In contrast, no colocalization was found between cortistatin and calretinin, cholecystokinin, or vasoactive intestinal peptide. During development there is a transient increase in cortistatin-expressing cells in the second postnatal week in all cortical areas and in the dentate gyrus. A transient expression of preprocortistatin mRNA in the hilar region at P16 is paralleled by electrophysiological changes in dentate granule cells. Together, these observations suggest mechanisms by which cortistatin may regulate cortical activity.

Characterization of thirty two microsatellite loci for three Atlanto-Mediterranean echinoderm species

Thirty two microsatellites were optimized from 454 pyrosequencing libraries for three Atlanto-Mediterranean echinoderms: Coscinasterias tenuispina, Echinaster sepositus and Arbacia lixula. We observed different frequency of microsatellite types (di-, tri-, tetra- and pentanucleotide) throughout the genome of the species, but no significant differences were observed in allele richness among different microsatellite repeats. No loci showed linkage disequilibrium. Heterozygosity deficit and departure from Hardy Weinberg equilibrium were observed for some loci, in two species, probably due to high levels of inbreeding. Heterozygosity excess observed in C. tenuispina could be explained by selection against homozygotes and/or outcrossing.

Ancient dispersal of the human fungal pathogen Cryptococcus gattii from the Amazon rainforest

Over the past two decades, several fungal outbreaks have occurred, including the high-profile 'Vancouver Island' and 'Pacific Northwest' outbreaks, caused by Cryptococcus gattii, which has affected hundreds of otherwise healthy humans and animals. Over the same time period, C. gattii was the cause of several additional case clusters at localities outside of the tropical and subtropical climate zones where the species normally occurs. In every case, the causative agent belongs to a previously rare genotype of C. gattii called AFLP6/VGII, but the origin of the outbreak clades remains enigmatic. Here we used phylogenetic and recombination analyses, based on AFLP and multiple MLST datasets, and coalescence gene genealogy to demonstrate that these outbreaks have arisen from a highly-recombining C. gattii population in the native rainforest of Northern Brazil. Thus the modern virulent C. gattii AFLP6/VGII outbreak lineages derived from mating events in South America and then dispersed to temperate regions where they cause serious infections in humans and animals.

Contribució al coneixement de la flora catalana occidental, III

En aquest treball s'aporten dades sobre la presència de nous tàxons a la plana occidental catalana, i que impliquen, en la majoria dels casos, ampliar de manera notable l'àrea de distribució de l'espècie. Són de destacar Cheirolophus intybaceus (Lam.) Dostál, Iris spuria L., Lathyrus annuus L., Phagnalon rupestre (L.) DC., Succisa pratensis Moench, Trigonella gladiata Steven ex Bieb. i Orchis laxiflora Lam. subsp. palustris (Jacq.) Bonnier & Layens.

Inversion polymorphism in two Serbian natural populations of Drosophila subobscura: Analysis of long-term changes

To study whether inversions (or arrangements) by themselves or karyotypes are the main global warming adaptive target of natural selection, two Drosophila subobscura Serbian populations (Apatin and Petnica) were re analyzed using different statistical approaches. Both populations were sampled in an approximately 15 years period: Apatin in 1994 and 2008 + 2009 and Petnica in 1995 and 2010. For all chromosomes, the four collections studied were in Hardy-Weinberg equilibrium. Thus, it seems that inversions (or arrangements) combined at random to constitute populations" karyotypes. However, there were differences in karyotypic fre quencies along the years, although they were significant only for Apatin population. It is possible to conclude that inversions (or arrangements) are likely the target of natural selection, because they presented long term changes, but combine at random to generate the corresponding karyotypic combinations. As a consequence, the frequencies of karyotypes also change along time.

Characterization of thirty two microsatellite loci for three Atlanto-Mediterranean echinoderm species

Thirty two microsatellites were optimized from 454 pyrosequencing libraries for three Atlanto-Mediterranean echinoderms: Coscinasterias tenuispina, Echinaster sepositus and Arbacia lixula. We observed different frequency of microsatellite types (di-, tri-, tetra- and pentanucleotide) throughout the genome of the species, but no significant differences were observed in allele richness among different microsatellite repeats. No loci showed linkage disequilibrium. Heterozygosity deficit and departure from Hardy Weinberg equilibrium were observed for some loci, in two species, probably due to high levels of inbreeding. Heterozygosity excess observed in C. tenuispina could be explained by selection against homozygotes and/or outcrossing.

Direct Interrogation of Viral Peptides Presented by the Class I HLA of HIV-Infected T Cells

Identification of CD8+ cytotoxic T lymphocyte (CTL) epitopes has traditionally relied upon testing of overlapping peptide libraries for their reactivity with T cells in vitro. Here, we pursued deep ligand sequencing (DLS) as an alternative method of directly identifying those ligands that are epitopes presented to CTLs by the class I human leukocyte antigens (HLA) of infected cells. Soluble class I HLA-A*11:01 (sHLA) was gathered from HIV-1 NL4-3-infected human CD4+ SUP-T1 cells. HLA-A*11:01 harvested from infected cells was immunoaffinity purified and acid boiled to release heavy and light chains from peptide ligands that were then recovered by size-exclusion filtration. The ligands were first fractionated by high-pH high-pressure liquid chromatography and then subjected to separation by nano-liquid chromatography (nano-LC)–mass spectrometry (MS) at low pH. Approximately 10 million ions were selected for sequencing by tandem mass spectrometry (MS/MS). HLA-A*11:01 ligand sequences were determined with PEAKS software and confirmed by comparison to spectra generated from synthetic peptides. DLS identified 42 viral ligands presented by HLA-A*11:01, and 37 of these were previously undetected. These data demonstrate that (i) HIV-1 Gag and Nef are extensively sampled, (ii) ligand length variants are prevalent, particularly within Gag and Nef hot spots where ligand sequences overlap, (iii) noncanonical ligands are T cell reactive, and (iv) HIV-1 ligands are derived from de novo synthesis rather than endocytic sampling. Next-generation immunotherapies must factor these nascent HIV-1 ligand length variants and the finding that CTL-reactive epitopes may be absent during infection of CD4+ T cells into strategies designed to enhance T cell immunity.

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.