910 resultados para Classification of causes of death
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Interneuron classification is an important and long-debated topic in neuroscience. A recent study provided a data set of digitally reconstructed interneurons classified by 42 leading neuroscientists according to a pragmatic classification scheme composed of five categorical variables, namely, of the interneuron type and four features of axonal morphology. From this data set we now learned a model which can classify interneurons, on the basis of their axonal morphometric parameters, into these five descriptive variables simultaneously. Because of differences in opinion among the neuroscientists, especially regarding neuronal type, for many interneurons we lacked a unique, agreed-upon classification, which we could use to guide model learning. Instead, we guided model learning with a probability distribution over the neuronal type and the axonal features, obtained, for each interneuron, from the neuroscientists’ classification choices. We conveniently encoded such probability distributions with Bayesian networks, calling them label Bayesian networks (LBNs), and developed a method to predict them. This method predicts an LBN by forming a probabilistic consensus among the LBNs of the interneurons most similar to the one being classified. We used 18 axonal morphometric parameters as predictor variables, 13 of which we introduce in this paper as quantitative counterparts to the categorical axonal features. We were able to accurately predict interneuronal LBNs. Furthermore, when extracting crisp (i.e., non-probabilistic) predictions from the predicted LBNs, our method outperformed related work on interneuron classification. Our results indicate that our method is adequate for multi-dimensional classification of interneurons with probabilistic labels. Moreover, the introduced morphometric parameters are good predictors of interneuron type and the four features of axonal morphology and thus may serve as objective counterparts to the subjective, categorical axonal features.
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Multi-junction solar cells are widely used in high-concentration photovoltaic systems (HCPV) attaining the highest efficiencies in photovoltaic energy generation. This technology is more dependent on the spectral variations of the impinging Direct Normal Irradiance (DNI) than conventional photovoltaics based on silicon solar cells and consequently demands a deeper knowledge of the solar resource characteristics. This article explores the capabilities of spectral indexes, namely, spectral matching ratios (SMR), to spectrally characterize the annual irradiation reaching a particular location on the Earth and to provide the necessary information for the spectral optimization of a MJ solar cell in that location as a starting point for CPV module spectral tuning. Additionally, the relationship between such indexes and the atmosphere parameters, such as the aerosol optical depth (AOD), precipitable water (PW), and air mass (AM), is discussed using radiative transfer models such as SMARTS to generate the spectrally-resolved DNI. The network of ground-based sun and sky-scanning radiometers AERONET (AErosol RObotic NETwork) is exploited to obtain the atmosphere parameters for a selected bunch of 34 sites worldwide. Finally, the SMR indexes are obtained for every location, and a comparative analysis is carried out for four architectures of triple junction solar cells, covering both lattice match and metamorphic technologies. The differences found among cell technologies are much less significant than among locations.
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KIF (kinesin superfamily) proteins are microtubule-dependent molecular motors that play important roles in intracellular transport and cell division. The extent to which KIFs are involved in various transporting phenomena, as well as their regulation mechanism, are unknown. The identification of 16 new KIFs in this report doubles the existing number of KIFs known in the mouse. Conserved nucleotide sequences in the motor domain were amplified by PCR using cDNAs of mouse nervous tissue, kidney, and small intestine as templates. The new KIFs were studied with respect to their expression patterns in different tissues, chromosomal location, and molecular evolution. Our results suggest that (i) there is no apparent tendency among related subclasses of KIFs of cosegregation in chromosomal mapping, and (ii) according to their tissue distribution patterns, KIFs can be divided into two classes–i.e., ubiquitous and specific tissue-dominant. Further characterization of KIFs may elucidate unknown fundamental phenomena underlying intracellular transport. Finally, we propose a straightforward nomenclature system for the members of the mouse kinesin superfamily.
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Sequence-specific transactivation by p53 is essential to its role as a tumor suppressor. A modified tetracycline-inducible system was established to search for transcripts that were activated soon after p53 induction. Among 9,954 unique transcripts identified by serial analysis of gene expression, 34 were increased more than 10-fold; 31 of these had not previously been known to be regulated by p53. The transcription patterns of these genes, as well as previously described p53-regulated genes, were evaluated and classified in a panel of widely studied colorectal cancer cell lines. “Class I” genes were uniformly induced by p53 in all cell lines; “class II” genes were induced in a subset of the lines; and “class III” genes were not induced in any of the lines. These genes were also distinguished by the timing of their induction, their induction by clinically relevant chemotherapeutic agents, the absolute requirement for p53 in this induction, and their inducibility by p73, a p53 homolog. The results revealed substantial heterogeneity in the transcriptional responses to p53, even in cells derived from a single epithelial cell type, and pave the way to a deeper understanding of p53 tumor suppressor action.
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A natural (evolutionary) classification is provided for 242 basic helix–loop–helix (bHLH) motif-containing proteins. Phylogenetic analyses of amino acid sequences describe the patterns of evolutionary change within the motif and delimit evolutionary lineages. These evolutionary lineages represent well known functional groups of proteins and can be further arranged into five groups based on binding to DNA at the hexanucleotide E-box, the amino acid patterns in other components of the motif, and the presence/absence of a leucine zipper. The hypothesized ancestral amino acid sequence for the bHLH transcription factor family is given together with the ancestral sequences of the subgroups. It is suggested that bHLH proteins containing a leucine zipper are not a natural, monophyletic group.
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We provide a complete classification up to conjugacy of the binary shifts of finite commutant index on the hyperfinite II1, factor. There is a natural correspondence between the conjugacy classes of these shifts and polynomials over GF(2) satisfying a certain duality condition.
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Our study of the extended metal environment, particularly of the second shell, focuses in this paper on zinc sites. Key findings include: (i) The second shell of mononuclear zinc centers is generally more polar than hydrophobic and prominently features charged residues engaged in an abundance of hydrogen bonding with histidine ligands. Histidine–acidic or histidine–tyrosine clusters commonly overlap the environment of zinc ions. (ii) Histidine tautomeric metal bonding patterns in ligating zinc ions are mixed. For example, carboxypeptidase A, thermolysin, and sonic hedgehog possess the same ligand group (two histidines, one unibidentate acidic ligand, and a bound water), but their histidine tautomeric geometries markedly differ such that the carboxypeptidase A makes only Nδ1 contacts, thermolysin makes only Nɛ2 contacts, and sonic hedgehog uses one of each. Thus the presence of a similar ligand cohort does not necessarily imply the same topology or function at the active site. (iii) Two close histidine ligands HXmH, m ≤ 5, rarely both coordinate a single metal ion in the Nδ1 tautomeric conformation, presumably to avoid steric conflicts. Mononuclear zinc sites can be classified into six types depending on the ligand composition and geometry. Implications of the results are discussed in terms of divergent and convergent evolution.
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Death-associated protein kinase (DAP-kinase) is a Ca+2/calmodulin-regulated serine/threonine kinase with a multidomain structure that participates in apoptosis induced by a variety of signals. To identify regions in this protein that are critical for its proapoptotic activity, we performed a genetic screen on the basis of functional selection of short DAP-kinase-derived fragments that could protect cells from apoptosis by acting in a dominant-negative manner. We expressed a library of randomly fragmented DAP-kinase cDNA in HeLa cells and treated these cells with IFN-γ to induce apoptosis. Functional cDNA fragments were recovered from cells that survived the selection, and those in the sense orientation were examined further in a secondary screen for their ability to protect cells from DAP-kinase-dependent tumor necrosis factor-α-induced apoptosis. We isolated four biologically active peptides that mapped to the ankyrin repeats, the “linker” region, the death domain, and the C-terminal tail of DAP-kinase. Molecular modeling of the complete death domain provided a structural basis for the function of the death-domain-derived fragment by suggesting that the protective fragment constitutes a distinct substructure. The last fragment, spanning the C-terminal serine-rich tail, defined a new regulatory region. Ectopic expression of the tail peptide (17 amino acids) inhibited the function of DAP-kinase, whereas removal of this region from the complete protein caused enhancement of the killing activity, indicating that the C-terminal tail normally plays a negative regulatory role. Altogether, this unbiased screen highlighted functionally important regions in the protein and revealed an additional level of regulation of DAP-kinase apoptotic function that does not affect the catalytic activity.
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Objective: To establish whether fetal growth rate (as distinct from size at birth) is associated with mortality from ischaemic heart disease.
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The Dali Domain Dictionary (http://www.ebi.ac.uk/dali/domain) is a numerical taxonomy of all known structures in the Protein Data Bank (PDB). The taxonomy is derived fully automatically from measurements of structural, functional and sequence similarities. Here, we report the extension of the classification to match the traditional four hierarchical levels corresponding to: (i) supersecondary structural motifs (attractors in fold space), (ii) the topology of globular domains (fold types), (iii) remote homologues (functional families) and (iv) homologues with sequence identity above 25% (sequence families). The computational definitions of attractors and functional families are new. In September 2000, the Dali classification contained 10 531 PDB entries comprising 17 101 chains, which were partitioned into five attractor regions, 1375 fold types, 2582 functional families and 3724 domain sequence families. Sequence families were further associated with 99 582 unique homologous sequences in the HSSP database, which increases the number of effectively known structures several-fold. The resulting database contains the description of protein domain architecture, the definition of structural neighbours around each known structure, the definition of structurally conserved cores and a comprehensive library of explicit multiple alignments of distantly related protein families.
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The database of Clusters of Orthologous Groups of proteins (COGs), which represents an attempt on a phylogenetic classification of the proteins encoded in complete genomes, currently consists of 2791 COGs including 45 350 proteins from 30 genomes of bacteria, archaea and the yeast Saccharomyces cerevisiae (http://www.ncbi.nlm.nih.gov/COG). In addition, a supplement to the COGs is available, in which proteins encoded in the genomes of two multicellular eukaryotes, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster, and shared with bacteria and/or archaea were included. The new features added to the COG database include information pages with structural and functional details on each COG and literature references, improvements of the COGNITOR program that is used to fit new proteins into the COGs, and classification of genomes and COGs constructed by using principal component analysis.