High rates of molecular evolution in hantaviruses

Hantaviruses are rodent-borne Bunyaviruses that infect the Arvicolinae, Murinae, and Sigmodontinae subfamilies of Muridae. The rate of molecular evolution in the hantaviruses has been previously estimated at approximately 10(-7) nucleotide substitutions per site, per year (substitutions/site/year), based on the assumption of codivergence and hence shared divergence times with their rodent hosts. If substantiated, this would make the hantaviruses among the slowest evolving of all RNA viruses. However, as hantaviruses replicate with an RNA-dependent RNA polymerase, with error rates in the region of one mutation per genome replication, this low rate of nucleotide substitution is anomalous. Here, we use a Bayesian coalescent approach to estimate the rate of nucleotide substitution from serially sampled gene sequence data for hantaviruses known to infect each of the 3 rodent subfamilies: Araraquara virus ( Sigmodontinae), Dobrava virus ( Murinae), Puumala virus ( Arvicolinae), and Tula virus ( Arvicolinae). Our results reveal that hantaviruses exhibit shortterm substitution rates of 10(-2) to 10(-4) substitutions/site/year and so are within the range exhibited by other RNA viruses. The disparity between this substitution rate and that estimated assuming rodent-hantavirus codivergence suggests that the codivergence hypothesis may need to be reevaluated.

The plant isoflavenoid genistein activates p53 and Chk2 in an ATM-dependent manner

Genistein is an isoflavenoid that is abundant in soy beans. Genistein has been reported to have a wide range of biological activities and to play a role in the diminished incidence of breast cancer in populations that consume a soy-rich diet. Genistein was originally identified as an inhibitor of tyrosine kinases; however, it also inhibits topoisomerase II by stabilizing the covalent DNA cleavage complex, an event predicted to cause DNA damage. The topoisomerase II inhibitor etoposide acts in a similar manner. Here we show that genistein induces the up-regulation of p53 protein, phosphorylation of p53 at serine 15, activation of the sequence-specific DNA binding properties of p53, and phosphorylation of the hCds1/Chk2 protein kinase at threonine 68. Phosphorylation and activation of p53 and phosphorylation of Chk2 were not observed in ATM-deficient cells. In contrast, the topoisomerase II inhibitor etoposide induced phosphorylation of p53 and Chk2 in ATM-positive and ATM-deficient cells. In addition, genistein-treated ATM-deficient cells were significantly more susceptible to genistein-induced killing than were ATM-positive cells. Together our data suggest that ATM is required for activation of a DNA damage-induced pathway that activates p53 and Chk2 in response to genistein.

Cloning of a catalytic subunit of cAMP-dependent protein kinase from the honeybee (Apis mellifera) and its localization in the brain

In the honeybee the cAMP-dependent signal transduction cascade has been implicated in processes underlying learning and memory, The cAMP-dependent protein kinase (PKA) is the major mediator of cAMP action. To characterize the PKA system in the honeybee brain we cloned a homologue of a PKA catalytic subunit from the honeybee,The deduced amino acid sequence shows 80-94% identity with catalytic subunits of PKA from Drosophila melanogaster, Aplysia californica and mammals. The corresponding gene is predominantly expressed in the mushroom bodies, a structure that is involved in learning and memory processes. However, expression can also be found in the antennal and optic lobes,The level of expression varies within all three neuropiles.

Expression and purification of enzymatically active recombinant RNA-dependent RNA polymerase (NS5) of the flavivirus Kunjin

The NS5 protein of the flavivirus Kunjin (KUN) contains conserved sequence motifs characteristic of RNA-dependent RNA polymerase (RdRp) activity. To investigate this activity in vitro, recombinant NS5 proteins with C-terminal (NS5CHis) and N-terminal (NS5NHis) hexahistidine tags were produced in baculovirus-infected insect cells and purified to near homogeneity by nickel affinity chromatography. Purified NS5CHis exhibited RdRp activity with both specific (9 kb KUN replicon) and non-specific (8.3 kb Semliki Forest virus replicon) RNA templates; this activity did not require the presence of additional viral and/or cellular cofactors. RdRp activity of purified NS5NHis protein was reduced in comparison to NS5CHis, while purified NS5NHis incorporating a GDD -> GVD mutation within the polymerase active site (NS5GVD) lacked RdRp activity. RNase A digestion of the RdRp reaction products indicated that they were double-stranded and of a similar size to the KUN replicative form produced in Vero cells, thus demonstrating that the KUN NS5 protein has an intrinsic, albeit low and non-specific RdRp activity in vitro, similar to that reported for recombinant RdRp of other flaviviruses. However, in contrast to RNA polymerases of other Flavivirus species, purified KUN NS5 polymerase produced a single, full-length replicon RNA product, thus demonstrating efficient processivity. (C) 2001 Elsevier Science B.V. All rights reserved.

Structural characterization of the N-terminal autoregulatory sequence of phenylalanine hydroxylase

Phenylalanine hydroxylase (PAH) is activated by its substrate phenylalanine, and through phosphorylation by cAMP-dependent protein kinase at Ser 16 in the N-terminal autoregulatory sequence of the enzyme. The crystal structures of phosphorylated and unphosphorylated forms of the enzyme showed that, in the absence of phenylalanine, in both cases the N-terminal 18 residues including the phosphorylation site contained no interpretable electron density. We used nuclear magnetic resonance (NMR) spectroscopy to characterize this N-terminal region of the molecule in different stages of the regulatory pathway. A number of sharp resonances are observed in PAH with an intact N-terminal region, but no sharp resonances are present in a truncation mutant lacking the N-terminal 29 residues. The N-terminal sequence therefore represents a mobile flexible region of the molecule. The resonances become weaker after the addition of phenylalanine, indicating a loss of mobility. The peptides corresponding to residues 2-20 of PAH have different structural characteristics in the phosphorylated and unphosphorylated forms, with the former showing increased secondary structure. Our results support the model whereby upon phenylalanine binding, the mobile N-terminal 18 residues of PAH associate with the folded core of the molecule; phosphorylation may facilitate this interaction.

Laying date and laying sequence influence the sex ratio of crimson rosella broods

We examine the patterns of sex allocation in crimson rosellas Platycercus elegans, a socially monogamous Australian parrot. Overall, 41.8% of nestlings were male, a significant female bias. However underlying this population-level bias were non-random patterns of sex allocation within broods. Broods produced early in the season were female-biased, but the proportion of males in a brood increased as the breeding season progressed. Female rosellas may obtain greater fitness benefits from early-fledging daughters than sons because daughters can breed as 1-year-olds whereas sons do not breed until they are at least 2 years old. Laying date and laying sequence also interacted to influence the sex ratio of eggs. The sex of early-laid eggs strongly followed the brood level pattern, whereas the sex of middle- and late-laid eggs did not change significantly as the season progressed. Nevertheless, late-laid eggs were very unlikely to be male at the end of the season. We argue these differing seasonal patterns reflect the relative costs and benefits to producing early-hatched males and females at different times of the season. Female rosellas appear to maximise the probability that daughters are able to breed early but to minimise competitive asymmetries within the brood. In particular, late-hatched male chicks are disadvantaged if their oldest sibling is male, explaining the dearth of broods containing late-hatched males at the end of the breeding season.

SAM (dependent) I AM: the S-adenosylmethionine-dependent methyltransferase fold

The S-adenosylmethionine-dependent methyltransferase enzymes share little sequence identity, but incorporate a highly conserved structural fold. Surprisingly, residues that bind the common cofactor are poorly conserved, although the binding site is localised to the same region of the fold. The substrate-binding region of the fold varies enormously. Over the past two years, there has been a significant increase in the number of structures that are known to incorporate this fold, including several uncharacterised proteins and two proteins that lack methyltransferase activity.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Coronary artery disease, microalbuminuria and lipid profile in patients with non-insulin dependent diabetes mellitus

PURPOSE: To determine the frequency of coronary artery disease, microalbuminuria and the relation to lipid profile disorders, blood pressure and clinical and metabolic features. METHODS: Fifty-five type 2 diabetic patients (32 females, 23 males), aged 59.9±9 years and with known diabetes duration of 11±7.3 years were studied. Coronary artery disease (CAD) was defined as a positive history of myocardial infarction, typical angina, myocardial revascularization or a positive stress testing. Microalbuminuria was defined when two out of three overnight urine samples had a urinary albumin excretion ranging 20 - 200µg/min. RESULTS: CAD was present in 24 patients (43,6%). High blood pressure (HBP) present in 32 patients (58.2%) and was more frequent in CAD group (p=0.05) HBP. Increased the risk of CAD 3.7 times (CI[1.14-12]). Microalbuminuria was present in 25 patients (45.5%) and tended to associate with higher systolic blood pressure (SBP) (p = 0.06), presence of hypertension (p = 0.06) and know diabetes duration (p = 0.08). In the stepwise multiple logistic regression the systolic blood pressure was the only variable that influenced UAE (r = 0.39, r² = 0.14, p = 0.01). The h ypertensive patients had higher cholesterol levels (p = 0.04). CONCLUSION: In our sample the frequency of microalbuminuria, hypertension, hypercholesterolemia and CHD was high. Since diabetes is an independent risk factor for cardiovascular disease, the association of others risk factors suggest the need for an intensive therapeutic intervention in primary and in secundary prevention.

β-Arrestin2 influences the response to methadone in opioid-dependent patients.

β-Arrestin2 (ARRB2) is a component of the G-protein-coupled receptor complex and is involved in μ-opioid and dopamine D(2) receptor signaling, two central processes in methadone signal transduction. We analyzed 238 patients in methadone maintenance treatment (MMT) and identified a haplotype block (rs34230287, rs3786047, rs1045280 and rs2036657) spanning almost the entire ARRB2 locus. Although none of these single nucleotide polymorphisms (SNPs) leads to a change in amino-acid sequence, we found that for all the SNPs analyzed, with exception of rs34230287, homozygosity for the variant allele confers a nonresponding phenotype (n=73; rs1045280C and rs2036657G: OR=3.1, 95% CI=1.5-6.3, P=0.004; rs3786047A: OR=2.5, 95% CI=1.2-5.1, P=0.02) also illustrated by a 12-fold shorter period of negative urine screening (P=0.01). The ARRB2 genotype may thus contribute to the interindividual variability in the response to MMT and help to predict response to treatment.

MC1R-dependent, melanin-based colour polymorphism is associated with cell-mediated response in the Eleonora's falcon.

Colour polymorphism in vertebrates is usually under genetic control and may be associated with variation in physiological traits. The melanocortin 1 receptor (Mc1r) has been involved repeatedly in melanin-based pigmentation but it was thought to have few other physiological effects. However, recent pharmacological studies suggest that MC1R could regulate the aspects of immunity. We investigated whether variation at Mc1r underpins plumage colouration in the Eleonora's falcon. We also examined whether nestlings of the different morphs differed in their inflammatory response induced by phytohemagglutinin (PHA). Variation in colouration was due to a deletion of four amino acids at the Mc1r gene. Cellular immune response was morph specific. In males, but not in females, dark nestling mounted a lower PHA response than pale ones. Although correlative, our results raise the neglected possibility that MC1R has pleiotropic effects, suggesting a potential role of immune capacity and pathogen pressure on the maintenance of colour polymorphism in this species.

Marbofloxacin achieves high concentration in pig tonsils according to a dose dependent fashion

The penetration of marbofloxacin into tonsils was assessed in fattening pigs. Two different dosages were used to treat the animals: 2 mg/kg b.w. every 24 hours during 3 days (P1 group) and 4 mg/kg b.w. every 48 hours two times (P2 group. A ratio between the mean tonsillar concentration of marbofloxacin for both doses 24 hours after the last administration (0.5 and 0.7 µgr/mL) and its MIC90 for APP (0.03 µgr/mL) was calculated. These Ratio values were 16.6 and 23.3 for P1 and P2 group.

Truncation of the receptor carboxyl terminus impairs agonist-dependent phosphorylation and desensitization of the alpha 1B-adrenergic receptor.

The alpha 1B-adrenergic receptor (alpha 1BAR) and its truncated mutant T368 lacking the last 147 amino acids were stably expressed in Rat1 fibroblasts. The wild type alpha 1BAR was rapidly phosphorylated upon exposure to the agonist epinephrine as well as to phorbol ester as assessed by immunoprecipitation of the receptor with antiserum raised against its amino-terminal portion. Exposure of cells expressing the wild type alpha 1BAR to epinephrine resulted also in rapid homologous desensitization of receptor-mediated response on polyphosphoinositide hydrolysis. On the other hand, truncation of the serine- and threonine-rich carboxyl portion of the alpha 1BAR abolished agonist-induced phosphorylation and greatly impaired homologous desensitization of the receptor. The truncated receptor T368 could undergo agonist-induced decrease of cell surface receptors but to a lesser extent, as compared with the wild type alpha 1BAR. These results demonstrate that the carboxyl portion of the alpha 1BAR plays a crucial role in the regulation of receptor function. They also suggest a strong relationship between agonist-induced phosphorylation and desensitization of the alpha 1BAR, which were both insensitive to the inhibitor of protein kinase C RO-318220. Our findings support the emerging hypothesis that the biochemical mechanisms involved in rapid agonist-dependent regulation of G protein-coupled receptors, which activate polyphosphoinositide hydrolysis, do not primarily involve protein kinase C.