Search

The interest on transfer coefficients studies have increased recently, since they are important parameters required understanding and reliably modelling the dispersion of conservative and non-conservative radionuclides in aquatic environments. The approaches, based in the implementation of the uptake kinetics of dissolved radionuclides by solid particles, are more appropriate than those based in the use of the distribution coefficients, kd. In this work, we present a series of tracing experiments to study the uptake of Pu, Am and Tc in natural aqueous suspensions from three aquatic systems (Gergal reservoir, Guadalquivir river, and the estuary of Tinto river) located in the South of Spain. The kinetic transfer coefficient for direct sorption depends on the total available surface of particles and on the concentration of active sites in the surface layer (what depends on the mineral composition, free edges, pores, coatings, etc.). In order to compare results from different environments and to fix the conditions of applicability of the derived coefficients, it is necessary to handle the particle size spectra and the mineral composition of natural occurring suspended loads. The time dependent uptake curves, covering up to a large period, are fitted to the numerical solutions calculated with different models of the uptake kinetics.

The prediction of the stage-discharge relationship for rivers in flood is described by a finite element model of depth-averaged turbulent flow, calibrated using (hree hydraulic coefficients governing local bed friction, lateral eddy viscosity and depth-averaged secondary flow. The resulting lateral distributions of depth-averaged velocity are subsequently integrated to yield the stage-discharge relationship. The calibration of the model involves the establishment of simplifying hypotheses for certain coefficients in order to give the correct depth-mean velocity and boundary shear, both across the channel and with stage. Comparisons against some experimental data from the UK Flood Channel Facility, for channels with trapezoidal and compound cross-sections, help develop the calibration philosophy for both inbank and overbank flows. Numerical experiments with the coherence method for a hypothetical river are used to extend the model calibration to rivers with homogeneous and heterogeneous roughness. Applications of the model to simulating the flow in a number of natural valley and mountain rivers serve to test hypotheses and results obtained at a real scale.

UEV proteins are enzymatically inactive variants of the E2 ubiquitin-conjugating enzymes that regulate noncanonical elongation of ubiquitin chains. In Saccharomyces cerevisiae, UEV is part of the RAD6-mediated error-free DNA repair pathway. In mammalian cells, UEV proteins can modulate c-FOS transcription and the G2-M transition of the cell cycle. Here we show that the UEV genes from phylogenetically distant organisms present a remarkable conservation in their exon-intron structure. We also show that the human UEV1 gene is fused with the previously unknown gene Kua. In Caenorhabditis elegans and Drosophila melanogaster, Kua and UEV are in separated loci, and are expressed as independent transcripts and proteins. In humans, Kua and UEV1 are adjacent genes, expressed either as separate transcripts encoding independent Kua and UEV1 proteins, or as a hybrid Kua-UEV transcript, encoding a two-domain protein. Kua proteins represent a novel class of conserved proteins with juxtamembrane histidine-rich motifs. Experiments with epitope-tagged proteins show that UEV1A is a nuclear protein, whereas both Kua and Kua-UEV localize to cytoplasmic structures, indicating that the Kua domain determines the cytoplasmic localization of Kua-UEV. Therefore, the addition of a Kua domain to UEV in the fused Kua-UEV protein confers new biological properties to this regulator of variant polyubiquitination.

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

Computational methods for automated genome annotation are critical to our community's ability to make full use of the large volume of genomic sequence being generated and released. To explore the accuracy of these automated feature prediction tools in the genomes of higher organisms, we evaluated their performance on a large, well-characterized sequence contig from the Adh region of Drosophila melanogaster. This experiment, known as the Genome Annotation Assessment Project (GASP), was launched in May 1999. Twelve groups, applying state-of-the-art tools, contributed predictions for features including gene structure, protein homologies, promoter sites, and repeat elements. We evaluated these predictions using two standards, one based on previously unreleased high-quality full-length cDNA sequences and a second based on the set of annotations generated as part of an in-depth study of the region by a group of Drosophila experts. Although these standard sets only approximate the unknown distribution of features in this region, we believe that when taken in context the results of an evaluation based on them are meaningful. The results were presented as a tutorial at the conference on Intelligent Systems in Molecular Biology (ISMB-99) in August 1999. Over 95% of the coding nucleotides in the region were correctly identified by the majority of the gene finders, and the correct intron/exon structures were predicted for >40% of the genes. Homology-based annotation techniques recognized and associated functions with almost half of the genes in the region; the remainder were only identified by the ab initio techniques. This experiment also presents the first assessment of promoter prediction techniques for a significant number of genes in a large contiguous region. We discovered that the promoter predictors' high false-positive rates make their predictions difficult to use. Integrating gene finding and cDNA/EST alignments with promoter predictions decreases the number of false-positive classifications but discovers less than one-third of the promoters in the region. We believe that by establishing standards for evaluating genomic annotations and by assessing the performance of existing automated genome annotation tools, this experiment establishes a baseline that contributes to the value of ongoing large-scale annotation projects and should guide further research in genome informatics.

Abstract: The presence of226Ra and224Ra in suspended matter from an estuarine system which surrounds a phosphate fertilizer complex has been investigated. The results have confirmed an important radioactive impact from the industrial complex, since up to 2.5 Bq226Ra/g suspended matter (dry) has been measured. The influence of tides and seasonal conditions, through changes in salinity, has been found to be relevant. The distribution coefficients for226Ra between the suspended matter and the river water have been calculated. The values are in agreement by order of magnitude with those found in the literature, but they clearly depend on tidal state and seasonal conditions.