PeECE III - Pelagic Ecosystem CO2 Enrichment Study, Raunefjord, Bergen, Norway, 2005

The effects of CO2-induced seawater acidification on plankton communities were also addressed in a series of 3 mesocosm experiments, called the Pelagic Ecosystem CO2 Enrichment (PeECE I-III) studies, which were conducted in the Large-Scale Mesocosm Facilities of the University of Bergen, Norway in 2001, 2003 and 2005, respectively. Each experiment consisted of 9 mesocosms, in which CO2 was manipulated to initial concentrations of 190, 350 and 750 µatm in 2001 and 2003, and 350, 700 and 1050 µatm in 2005. The present dataset concerns PeECE III.

Arsenic speciation in edible alga samples by microwave-assisted extraction and high performance liquid chromatography coupled to atomic fluorescence spectrometry

Twelve commercially available edible marine algae from France, Japan and Spain and the certified reference material (CRM) NIES No. 9 Sargassum fulvellum were analyzed for total arsenic and arsenic species. Total arsenic concentrations were determined by inductively coupled plasma atomic emission spectrometry (ICP-AES) after microwave digestion and ranged from 23 to 126 μg g−1. Arsenic species in alga samples were extracted with deionized water by microwave-assisted extraction and showed extraction efficiencies from 49 to 98%, in terms of total arsenic. The presence of eleven arsenic species was studied by high performance liquid chromatography–ultraviolet photo-oxidation–hydride generation atomic–fluorescence spectrometry (HPLC–(UV)–HG–AFS) developed methods, using both anion and cation exchange chromatography. Glycerol and phosphate sugars were found in all alga samples analyzed, at concentrations between 0.11 and 22 μg g−1, whereas sulfonate and sulfate sugars were only detected in three of them (0.6-7.2 μg g−1). Regarding arsenic toxic species, low concentration levels of dimethylarsinic acid (DMA) (<0.9 μg g−1) and generally high arsenate (As(V)) concentrations (up to 77 μg g−1) were found in most of the algae studied. The results obtained are of interest to highlight the need to perform speciation analysis and to introduce appropriate legislation to limit toxic arsenic species content in these food products.

Membrane Dissolution in Distributed Architectures of P-Systems

The goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the main results regarding the way membranes can be placed on processors in order to get a software/hardware simulation of P-Systems in a distributed environment. Secondly, we improve some results about the membrane dissolution problem, prove that it is connected, and discuss the possibility of simulating this property in the distributed model. All this yields an improvement in the system parallelism implementation since it gets an increment of the parallelism of the external communication among processors. Also, the number of processors grows in such a way that is notorious the increment of the parallelism in the application of the evolution rules and the internal communica-tionsstudy because it gets an increment of the parallelism in the application of the evolution rules and the internal communications. Proposed ideas improve previous architectures to tackle the communication bottleneck problem, such as reduction of the total time of an evolution step, increase of the number of membranes that could run on a processor and reduction of the number of processors

Monte-Carlo dosimetry on a realistic cell monolayer geometry exposed to alpha particles

The energy and specific energy absorbed in the main cell compartments (nucleus and cytoplasm) in typical radiobiology experiments are usually estimated by calculations as they are not accessible for a direct measurement. In most of the work, the cell geometry is modelled using the combination of simple mathematical volumes. We propose a method based on high resolution confocal imaging and ion beam analysis (IBA) in order to import realistic cell nuclei geometries in Monte-Carlo simulations and thus take into account the variety of different geometries encountered in a typical cell population. Seventy-six cell nuclei have been imaged using confocal microscopy and their chemical composition has been measured using IBA. A cellular phantom was created from these data using the ImageJ image analysis software and imported in the Geant4 Monte-Carlo simulation toolkit. Total energy and specific energy distributions in the 76 cell nuclei have been calculated for two types of irradiation protocols: a 3 MeV alpha particle microbeam used for targeted irradiation and a 239Pu alpha source used for large angle random irradiation. Qualitative images of the energy deposited along the particle tracks have been produced and show good agreement with images of DNA double strand break signalling proteins obtained experimentally. The methodology presented in this paper provides microdosimetric quantities calculated from realistic cellular volumes. It is based on open-source oriented software that is publicly available.

A function using cubic splines for the analysis of alpha--particles spectra from silicon detectors

A function based on the characteristics of the alpha-particle lines obtained with silicon semiconductor detectors and modi"ed by using cubic splines is proposed to parametrize the shape of the peaks. A reduction in the number of parameters initially considered in other proposals was carried out in order to improve the stability of the optimization process. It was imposed by the boundary conditions for the cubic splines term. This function was then able to describe peaks with highly anomalous shapes with respect to those expected from this type of detector. Some criteria were implemented to correctly determine the area of the peaks and their errors. Comparisons with other well-established functions revealed excellent agreement in the "nal values obtained from both "ts. Detailed studies on reliability of the "tting results were carried out and the application of the function is proposed. Although the aim was to correct anomalies in peak shapes, the peaks showing the expected shapes were also well "tted. Accordingly, the validity of the proposal is quite general in the analysis of alpha-particle spectrometry with semiconductor detectors.

Evaluation of the bioaccumulation kinetics of gold nanorods in vital mammalian organs by mean of TXRF spectrometry

This work presents the first application of total-reflection X-ray fluorescence (TXRF) spectrometry, a new and powerful alternative analytical method, to evaluation of the bioaccumulation kinetics of gold nanorods (GNRs) in various tissues upon intravenous administration in mice. The analytical parameters for developed methodology by TXRF were evaluated by means of the parallel analysis of bovine liver certified reference material samples (BCR-185R) doped with 10 μg/g gold. The average values (n = 5) achieved for gold measurements in lyophilized tissue weight were as follows: recovery 99.7%, expanded uncertainty (k = 2) 7%, repeatability 1.7%, detection limit 112 ng/g, and quantification limit 370 ng/g. The GNR bioaccumulation kinetics was analyzed in several vital mammalian organs such as liver, spleen, brain, and lung at different times. Additionally, urine samples were analyzed to study the kinetics of elimination of the GNRs by this excretion route. The main achievement was clearly differentiating two kinds of behaviors. GNRs were quickly bioaccumulated by highly vascular filtration organs such as liver and spleen, while GNRs do not show a bioaccumulation rates in brain and lung for the period of time investigated. In parallel, urine also shows a lack of GNR accumulation. TXRF has proven to be a powerful, versatile, and precise analytical technique for the evaluation of GNRs content in biological systems and, in a more general way, for any kind of metallic nanoparticles.

Proteomic definition of normal human luminal and myoepithelial breast cells purified from reduction mammoplasties

Normal human luminal and myoepithelial breast cells separately purified from a set of 10 reduction mammoplasties by using a double antibody magnetic affinity cell sorting and Dynabead immunomagnetic technique were used in two-dimensional gel proteome studies. A total of 43,302 proteins were detected across the 20 samples, and a master image for each cell type comprising a total of 1,738 unique proteins was derived. Differential analysis identified 170 proteins that were elevated 2-fold or more between the two breast cell types, and 51 of these were annotated by tandem mass spectrometry. Muscle-specific enzyme isoforms and contractile intermediate filaments including tropomyosin and smooth muscle (SM22) alpha protein were detected in the myoepithelial cells, and a large number of cytokeratin subclasses and isoforms characteristic of luminal cells were detected in this cell type. A further 134 nondifferentially regulated proteins were also annotated from the two breast cell types, making this the most extensive study to date of the protein expression map of the normal human breast and the basis for future studies of purified breast cancer cells.

Linking genome and proteome by mass spectrometry: Large-scale identification of yeast proteins from two dimensional gels

The function of many of the uncharacterized open reading frames discovered by genomic sequencing can be determined at the level of expressed gene products, the proteome. However, identifying the cognate gene from minute amounts of protein has been one of the major problems in molecular biology. Using yeast as an example, we demonstrate here that mass spectrometric protein identification is a general solution to this problem given a completely sequenced genome. As a first screen, our strategy uses automated laser desorption ionization mass spectrometry of the peptide mixtures produced by in-gel tryptic digestion of a protein. Up to 90% of proteins are identified by searching sequence data bases by lists of peptide masses obtained with high accuracy. The remaining proteins are identified by partially sequencing several peptides of the unseparated mixture by nanoelectrospray tandem mass spectrometry followed by data base searching with multiple peptide sequence tags. In blind trials, the method led to unambiguous identification in all cases. In the largest individual protein identification project to date, a total of 150 gel spots—many of them at subpicomole amounts—were successfully analyzed, greatly enlarging a yeast two-dimensional gel data base. More than 32 proteins were novel and matched to previously uncharacterized open reading frames in the yeast genome. This study establishes that mass spectrometry provides the required throughput, the certainty of identification, and the general applicability to serve as the method of choice to connect genome and proteome.