90 resultados para 1086
Resumo:
The plant actin cytoskeleton is a highly dynamic, fibrous structure essential in many cellular processes including cell division and cytoplasmic streaming. This structure is stimulus responsive, being affected by internal stimuli, by biotic and abiotic stresses mediated in signal transduction pathways by actin-binding proteins. The completion of the Arabidopsis genome sequence has allowed a comparative identification of many actin-binding proteins. However, not all are conserved in plants, which possibly reflects the differences in the processes involved in morphogenesis between plant and other cells. Here we have searched for the Arabidopsis equivalents of 67 animal/fungal actin-binding proteins and show that 36 are not conserved in plants. One protein that is conserved across phylogeny is actin-depolymerizing factor or cofilin and we describe our work on the activity of vegetative tissue and pollen-specific isoforms of this protein in plant cells, concluding that they are functionally distinct.
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Weathering-rind thicknesses on pebble-and cobble-size sediment have been used for the past half-century, at least, as an age indicator of postdepositional time following a geologic event. In mountainous terrain, rind thickness is taken as a measurement of weathering over time frames of 0.5 m.yr.; variable thicknesses are used to discriminate relative ages of glacial deposits. The effects of chemical and physical weathering that together produce rinds are only rarely considered, and most research objectives have centered on lichen alteration of clast surfaces. Recent microscopic analyses of weathering rinds on volcanic clasts of similar to 70.0-ka to similar to 2.0-m.yr. age produced new data on weathering products as well as unexpected incorporated biotic materials undergoing diagenesis. The question as to how much physical/mineral/chemical/ biotic paleoenvironmental data might be archived in rinds is discussed. The character and classification of organic materials undergoing diagenesis are also discussed.
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We present the DONUTS autoguiding algorithm, designed to fix stellar positions at the sub-pixel level for high-cadence time-series photometry, and also capable of autoguiding on defocused stars. DONUTS was designed to calculate guide corrections from a series of science images and recentre telescope pointing between each exposure. The algorithm has the unique ability of calculating guide corrections from undersampled to heavily defocused point spread functions. We present the case for why such an algorithm is important for high precision photometry and give our results from off and on-sky testing. We discuss the limitations of DONUTS and the facilities where it soon will be deployed.
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Prior evidence has supported the existence of multiple susceptibility genes for schizophrenia. Multipoint linkage analysis of the 270 Irish high-density pedigrees that we have studied, as well as results from several other samples, suggest that at least one such gene is located in region 6p24-21. In the present study, family-based association analysis of 36 simple sequence-length-polymorphism markers and of 17 SNP markers implicated two regions, separated by approximately 7 Mb. The first region, and the focus of this report, is 6p22.3. In this region, single-nucleotide polymorphisms within the 140-kb gene DTNBP1 (dystrobrevin-binding protein 1, or dysbindin) are strongly associated with schizophrenia. Uncorrected, empirical P values produced by the program TRANSMIT were significant (P
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Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R(avg)) and then weighted for sample size (N(sqrt)[affected casess]). A permutation test was used to compute the probability of observing, by chance, each bin's average rank (P(AvgRnk)) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P(ord)). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (PAvgRnk
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A randomized controlled trial was used to evaluate the effects of a pro-social behavior after-school program called Mate-Tricks for nine and ten year old children and their parents living in an area of significant socioeconomic disadvantage. The children were randomly assigned to an intervention (n=220) or a control group (n=198). Children were compared on measures of pro-social behavior, anti-social behavior and related outcome measures. The trial found adverse effects on four outcomes among the intervention group compared to the control group: anti-social behavior increased on two different measures (d=+0.20) and (d=+0.18); child reported liberal parenting increased (d=+0.16); and child reported authoritarian parenting also increased (d=+0.20). In addition, parental participation was significantly associated with several program outcomes. It was concluded, that group based after-school behavior programs may have the potential to cause iatrogenic effects and must be designed, piloted, evaluated and implemented with a high degree of care.
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Using pulsed-field gel electrophoresis, we genotyped 21 methicillin-resistant Staphylococcus aureus isolates from patients attending an adult cystic fibrosis unit. Eleven patients exhibited pulsotypes related to 2 locally endemic strains. Eleven chronically colonized patients were assessed over a period of up to 2 years, and all demonstrated a retention of strain type.
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This work examines the conformational ensemble involved in β-hairpin folding by means of advanced molecular dynamics simulations and dimensionality reduction. A fully atomistic description of the protein and the surrounding solvent molecules is used, and this complex energy landscape is sampled by means of parallel tempering metadynamics simulations. The ensemble of configurations explored is analyzed using the recently proposed sketch-map algorithm. Further simulations allow us to probe how mutations affect the structures adopted by this protein. We find that many of the configurations adopted by a mutant are the same as those adopted by the wild-type protein. Furthermore, certain mutations destabilize secondary-structure-containing configurations by preventing the formation of hydrogen bonds or by promoting the formation of new intramolecular contacts. Our analysis demonstrates that machine-learning techniques can be used to study the energy landscapes of complex molecules and that the visualizations that are generated in this way provide a natural basis for examining how the stabilities of particular configurations of the molecule are affected by factors such as temperature or structural mutations.
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Models of complex systems with n components typically have order n<sup>2</sup> parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.
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We have used whole exome sequencing to compare a group of presentation t(4;14) with t(11;14) cases of myeloma to define the mutational landscape. Each case was characterized by a median of 24.5 exonic nonsynonymous single-nucleotide variations, and there was a consistently higher number of mutations in the t(4;14) group, but this number did not reach statistical significance. We show that the transition and transversion rates in the 2 subgroups are similar, suggesting that there was no specific mechanism leading to mutation differentiating the 2 groups. Only 3% of mutations were seen in both groups, and recurrently mutated genes include NRAS, KRAS, BRAF, and DIS3 as well as DNAH5, a member of the axonemal dynein family. The pattern of mutation in each group was distinct, with the t(4;14) group being characterized by deregulation of chromatin organization, actin filament, and microfilament movement. Recurrent RAS pathway mutations identified subclonal heterogeneity at a mutational level in both groups, with mutations being present as either dominant or minor subclones. The presence of subclonal diversity was confirmed at a single-cell level using other tumor-acquired mutations. These results are consistent with a distinct molecular pathogenesis underlying each subgroup and have important impacts on targeted treatment strategies. The Medical Research Council Myeloma IX trial is registered under ISRCTN68454111.
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Chapter describes some of the more common cardiac conditions in neonates
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Understanding the mechanism associated with rates of weathering and evolution of rocks→sediment→soil→paleosol in alpine environments raises questions related to the impact of microbial mediation versus various diverse abiotic chemical/physical processes, even including the overall effect of cosmic impact/airburst during the early stage of weathering in Late Glacial (LG) deposits. This study is of a chronosequence of soils/paleosols, with an age range that spans the post–Little Ice Age (post-LIA; <150 yr), the Little Ice Age (LIA; AD 1500–1850), the middle Neoglacial (∼3 ka)–Younger Dryas (YD; <12.8 ka), and the LG (<15 ka). The goal is to elicit trends in weathering, soil morphogenesis, and related eubacterial population changes over the past 13–15 k.yr. The older LG/YD paleosols in the sequence represent soil morphogenesis that started during the closing stage of Pleistocene glaciation. These are compared with undated soils of midto late Neoglacial age, the youngest of LIA and post-LIA age. All profiles formed in a uniform parentmaterial ofmetabasalt composition and in moraine, rockfall, protalus, and alluvial fan deposits. Elsewhere in Europe,North America, and Asia, the cosmic impact/airburst event at 12.8 ka often produced a distinctive, carbon-rich “black mat” layer that shows evidence of high-temperature melting. At this alpine site, older profiles of similar LG age contain scorched and melted surface sediments that are otherwise similar in composition to the youngest/thinnest profiles developing in the catchment today. Moreover, microbial analysis of the sediments offers new insight into the genesis of these sediments: the C and Cu (u = unweathered) horizons in LG profiles present at 12.8 ka (now Ah/Bw) show bacterial population structures that differ markedly from recent alluvial/protalus sample bacterial populations. We propose here that these differences are, in part, a direct consequence of the age/cosmic impact/weathering processes that have occurred in the chronosequence. Of the several questions that emerge from these sequences, perhaps the most important involve the interaction of biotic-mineral factors, which need to be understood if we are to generally fully appreciate the role played by microbes in rock weathering.