Quasispecies diversity determines pathogenesis through cooperative interactions in a viral population

An RNA virus population does not consist of a single genotype; rather, it is an ensemble of related sequences, termed quasispecies. Quasispecies arise from rapid genomic evolution powered by the high mutation rate of RNA viral replication. Although a high mutation rate is dangerous for a virus because it results in nonviable individuals, it has been hypothesized that high mutation rates create a 'cloud' of potentially beneficial mutations at the population level, which afford the viral quasispecies a greater probability to evolve and adapt to new environments and challenges during infection. Mathematical models predict that viral quasispecies are not simply a collection of diverse mutants but a group of interactive variants, which together contribute to the characteristics of the population. According to this view, viral populations, rather than individual variants, are the target of evolutionary selection. Here we test this hypothesis by examining the consequences of limiting genomic diversity on viral populations. We find that poliovirus carrying a high-fidelity polymerase replicates at wild-type levels but generates less genomic diversity and is unable to adapt to adverse growth conditions. In infected animals, the reduced viral diversity leads to loss of neurotropism and an attenuated pathogenic phenotype. Notably, using chemical mutagenesis to expand quasispecies diversity of the high-fidelity virus before infection restores neurotropism and pathogenesis. Analysis of viruses isolated from brain provides direct evidence for complementation between members in the quasispecies, indicating that selection indeed occurs at the population level rather than on individual variants. Our study provides direct evidence for a fundamental prediction of the quasispecies theory and establishes a link between mutation rate, population dynamics and pathogenesis.     

Relativistic ejecta from X-ray flash XRF 060218 and the rate of cosmic explosions

Over the past decade, long-duration gamma-ray bursts (GRBs)--including the subclass of X-ray flashes (XRFs)--have been revealed to be a rare variety of type Ibc supernova. Although all these events result from the death of massive stars, the electromagnetic luminosities of GRBs and XRFs exceed those of ordinary type Ibc supernovae by many orders of magnitude. The essential physical process that causes a dying star to produce a GRB or XRF, and not just a supernova, is still unknown. Here we report radio and X-ray observations of XRF 060218 (associated with supernova SN 2006aj), the second-nearest GRB identified until now. We show that this event is a hundred times less energetic but ten times more common than cosmological GRBs. Moreover, it is distinguished from ordinary type Ibc supernovae by the presence of 10(48) erg coupled to mildly relativistic ejecta, along with a central engine (an accretion-fed, rapidly rotating compact source) that produces X-rays for weeks after the explosion. This suggests that the production of relativistic ejecta is the key physical distinction between GRBs or XRFs and ordinary supernovae, while the nature of the central engine (black hole or magnetar) may distinguish typical bursts from low-luminosity, spherical events like XRF 060218.     

Neural network versus econometric models in forecasting inflation

Artificial neural network modelling has recently attracted much attention as a new technique for estimation and forecasting in economics and finance. The chief advantages of this new approach are that such models can usually find a solution for very complex problems, and that they are free from the assumption of linearity that is often adopted to make the traditional methods tractable. In this paper we compare the performance of Back‐Propagation Artificial Neural Network (BPN) models with the traditional econometric approaches to forecasting the inflation rate. Of the traditional econometric models we use a structural reduced‐form model, an ARIMA model, a vector autoregressive model, and a Bayesian vector autoregression model. We compare each econometric model with a hybrid BPN model which uses the same set of variables. Dynamic forecasts are compared for three different horizons: one, three and twelve months ahead. Root mean squared errors and mean absolute errors are used to compare quality of forecasts. The results show the hybrid BPN models are able to forecast as well as all the traditional econometric methods, and to outperform them in some cases. Copyright © 2000 John Wiley & Sons, Ltd.     

Growth mechanisms of Ag and Cu nanodendrites via Galvanic replacement reactions

Dendritic silver and copper crystals were produced via Galvanic replacement reactions on zinc and aluminum plates, respectively. The growth orientations of these metals were determined using electron microscopy. The results showed that a fast crystal growth associated with a high concentration of metal cations led to kinetically controlled growth along the <112> axes of the cubic close-packed structures. However, a slow growth rate resulted in thermodynamically controlled growth along the ...     

Effect of extrinsic mortality on the evolution of senescence in guppies

Classical theories for the evolution of senescence predict that organisms that experience low mortality rates attributable to external factors, such as disease or predation, will evolve a later onset of senescence. Here we use patterns of senescence in guppies derived from natural populations that differ in mortality risk to evaluate the generality of these predictions. We have previously found that populations experiencing higher mortality rates evolve earlier maturity and invest more in reproduction, as predicted by evolutionary theory. We report here that these same populations do not have an earlier onset of senescence with respect to either mortality or reproduction but do with respect to swimming performance, which assesses neuromuscular function. This mosaic pattern of senescence challenges the generality of the association between decreased extrinsic mortality and delayed senescence and invites consideration of more derived theories for the evolution of senescence.     

Fine-mapping at three loci known to affect fetal hemoglobin levels explains additional genetic variation

We used resequencing and genotyping in African Americans with sickle cell anemia (SCA) to characterize associations with fetal hemoglobin (HbF) levels at the BCL11A, HBS1L-MYB and β-globin loci. Fine-mapping of HbF association signals at these loci confirmed seven SNPs with independent effects and increased the explained heritable variation in HbF levels from 38.6% to 49.5%. We also identified rare missense variants that causally implicate MYB in HbF production.     

Quantal calcium release by purified reconstituted inositol 1,4,5-trisphosphate receptors.

Release of intracellular Ca2+ by inositol 1,4,5-trisphosphate (InsP3) occurs through specific receptor proteins which are ligand-activated Ca2+ channels. Changes in intracellular Ca2+ regulate many cellular functions. This Ca2+ release is a discontinuous quantal process in which successive increments of InsP3 transiently release precise amounts of Ca2+ (refs 4-6). Possible explanations of quantal Ca2+ release have included rapid degradation of InsP3, reciprocity of Ca2+ release and sequestration, desensitization of InsP3 receptors, or actions of InsP3 on discrete compartments of Ca2+ with variable sensitivity to InsP3 (ref. 4). We successfully reconstituted InsP3-induced Ca2+ flux in vesicles containing only purified InsP3 receptor protein. The reconstituted vesicles retain the regulatory features of the InsP3 receptor, including phosphorylation sites and modulation of Ca2+ release by adenine nucleotides. Using these reconstituted vesicles, we show here that quantal flux of Ca2+ elicited by InsP3 is a fundamental property of its receptor.     

Detection of a radio counterpart to the 27 December 2004 giant flare from SGR 1806-20

It was established over a decade ago that the remarkable high-energy transients known as soft gamma-ray repeaters (SGRs) are located in our Galaxy and originate from neutron stars with intense (< or = 10(15)G) magnetic fields-so-called 'magnetars'. On 27 December 2004, a giant flare with a fluence exceeding 0.3 erg cm(-2) was detected from SGR 1806-20. Here we report the detection of a fading radio counterpart to this event. We began a monitoring programme from 0.2 to 250 GHz and obtained a high-resolution 21-cm radio spectrum that traces the intervening interstellar neutral hydrogen clouds. Analysis of the spectrum yields the first direct distance measurement of SGR 1806-20: the source is located at a distance greater than 6.4 kpc and we argue that it is nearer than 9.8 kpc. If correct, our distance estimate lowers the total energy of the explosion and relaxes the demands on theoretical models. The energetics and the rapid decay of the radio source are not compatible with the afterglow model that is usually invoked for gamma-ray bursts. Instead, we suggest that the rapidly decaying radio emission arises from the debris ejected during the explosion.