MiAMP1, a novel protein from Macadamia integrifolia adopts a Greek key beta-barrel fold unique amongst plant antimicrobial proteins

MiAMP1 is a recently discovered 76 amino acid residue, highly basic protein from the nut kernel of:Macadamia integrifolia which possesses no sequence homology to any known protein and inhibits the growth of several microbial plant pathogens in vitro while having no effect on mammalian or plant cells. It is considered to be a potentially useful tool for the genetic engineering of disease resistance in transgenic crop plants and for the design of new fungicides. The three-dimensional structure of MiAMP1 was determined through homonuclear and heteronuclear (N-15) 2D NMR spectroscopy and subsequent simulated annealing calculations with the ultimate aim of understanding the structure-activity relationships of the protein. MiAMP1 is made up of eight beta-strands which are arranged in two Greek key motifs. These Greek key motifs associate to form a Greek key beta-barrel. This structure is unique amongst plant antimicrobial proteins and forms a new class which we term the beta-barrelins. Interestingly, the structure of MiAMP1 bears remarkable similarity to a yeast killer toxin from Williopsis mrakii. This toxin acts by inhibiting beta-glucan synthesis and thereby cell wall construction in sensitive strains of yeast. The structural similarity of MiAMP1 and WmKT, which originate from plant and fungal phyla respectively, may reflect a similar mode of action. (C) 1999 Academic Press.

Use of the q-Gaussian mutation in evolutionary algorithms

This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms. The shape of the q-Gaussian mutation distribution is controlled by a real parameter q. In the proposed method, the real parameter q of the q-Gaussian mutation is encoded in the chromosome of individuals and hence is allowed to evolve during the evolutionary process. In order to test the new mutation operator, evolution strategy and evolutionary programming algorithms with self-adapted q-Gaussian mutation generated from anisotropic and isotropic distributions are presented. The theoretical analysis of the q-Gaussian mutation is also provided. In the experimental study, the q-Gaussian mutation is compared to Gaussian and Cauchy mutations in the optimization of a set of test functions. Experimental results show the efficiency of the proposed method of self-adapting the mutation distribution in evolutionary algorithms.

What the reasons for no inbreeding and high genetic diversity of the neotropical fig tree Ficus arpazusa ?

Ficus arpazusa Casaretto is a fig tree native to the Atlantic Rain Forest sensu lato. High levels of genetic diversity and no inbreeding were observed in Ficus arpazusa. This genetic pattern is due to the action of its pollinator, Pegoscapus sp., which disperses pollen an estimated distance of 5.6 km, and of Ficus arpazusa`s mating system which, in the study area, is allogamous. This study highlights the importance of adding both ecological and genetic data into population studies, allowing a better understanding of evolutionary processes and in turn increasing the efficacy of forest management and revegetation projects, as well as species conservation.

Genetic covariance between indices of body condition and immunocompetence in a passerine bird

Background: Condition-dependence is a ubiquitous feature of animal life histories and has important implications for both natural and sexual selection. Mate choice, for instance, is typically based on condition-dependent signals. Theory predicts that one reason why condition-dependent signals may be special is that they allow females to scan for genes that confer high parasite resistance. Such explanations require a genetic link between immunocompetence and body condition, but existing evidence is limited to phenotypic associations. It remains unknown, therefore, whether females selecting males with good body condition simply obtain a healthy mate, or if they acquire genes for their offspring that confer high immunocompetence. Results: Here we use a cross-foster experimental design to partition the phenotypic covariance in indices of body condition and immunocompetence into genetic, maternal and environmental effects in a passerine bird, the zebra finch Taeniopygia guttata. We show that there is significant positive additive genetic covariance between an index of body condition and an index of cell-mediated immune response. In this case, genetic variance in the index of immune response explained 56% of the additive genetic variance in the index of body condition. Conclusion: Our results suggest that, in the context of sexual selection, females that assess males on the basis of condition-dependent signals may gain genes that confer high immunocompetence for their offspring. More generally, a genetic correlation between indices of body condition and imuunocompetence supports the hypothesis that parasite resistance may be an important target of natural selection. Additional work is now required to test whether genetic covariance exists among other aspects of both condition and immunocompetence.

Structure optimization combining soft-core interaction functions, the diffusion equation method, and molecular dynamics

Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

Natural Host Relationships and Genetic Diversity of Rodent-Associated Hantaviruses in Southeastern Brazil

Objective: Hantaviruses are rodent-borne RNA viruses that have caused hantavirus cardiopulmonary syndrome in several Brazilian regions. In the present study, geographical distribution, seroprevalence, natural host range, and phylogenetic relations of rodent-associated hantaviruses collected from seven counties of Southeastern Brazil were evaluated. Methods: ELISA, RT-PCR and phylogenetic analysis were used in this study. Results: Antibodies to hantavirus were detected in Bolomys lasiurus, Akodon sp. and Oligoryzomys sp., performing an overall seroprevalence of 5.17%. All seropositive rodents were associated with grasslands or woods surrounded by sugar cane fields. Phylogenetic analysis of partial S- and M-segment sequences showed that viral sequences isolated from B. lasiurus specimens clustered with Araraquara virus. However, a sequence from Akodon sp. shared 100% similarity with Argentinian/Chilean viruses based on the partial S- segment amino acid sequence. Conclusion: These results indicate that there are associations between rodent reservoirs and hantaviruses in some regions of Southeastern Brazil, and suggest the existence of additional hantavirus genetic diversity and host ecology in these areas. Copyright (C) 2008 S. Karger AG, Basel

Genetic and non-genetic factors affecting birth-weight and adult body mass index

Birthweight affects neonatal mortality and morbidity and has been used as a marker of foetal undernutrition in studies of prenatal effects on adult characteristics. It is potentially influenced by genetic and environmental influences on the mother, and effects of foetal genotype, which is partially derived from the maternal genotype. Interpretations of variation in birthweight and associated characteristics as being due to prenatal environment ignore other possible modes of materno-foetal transmission. Subjects were adult twins recruited through the Australian Twin Registry, aged 17 to 87 years, and the sample comprised 1820 men and 4048 women. Twins reported their own birthweight as part of a health questionnaire. Body Mass Index (BMI) was calculated from self-reports of height and weight. Correlations between co-twins' birthweights were high for both monozygotic (r = 0.77) and dizygotic (r = 0.67) pairs, leading to substantial estimates of shared environmental effects (56% of variance) with significant additive genetic (23%) and non-shared environmental (21%) components. Adult BMI was mainly influenced by genetic factors, both additive (36% of variance) and nonadditive (35%). The correlation between birthweight and BMI was positive, in that heavier babies became on average more obese adults. A bivariate model of birthweight and adult BMI showed significant positive genetic (rg = 0.16, p = 0.005) and environmental (re = 0.08, p = 0.000011) correlations. Intra-uterine environmental or perinatal influences shared by cotwins exercise a strong influence on birthweight, but the factors which affect both birthweight and adult BMI are partly genetic and partly non-shared environmental.

Mathematical methods for spatially cohesive reserve design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.

Genetic Covariation between Serum {gamma}-Glutamyltransferase Activity and Cardiovascular Risk Factors

Background: Several studies have shown that variation in serum gamma-glutamyltransferase (GGT) in the population is associated with risk of death or development of cardiovascular disease, type 2 diabetes, stroke, or hypertension. This association is only partly explained by associations between GGT and recognized risk factors. Our aim was to estimate the relative importance of genetic and environmental sources of variation in GGT as well as genetic and environmental sources of covariation between GGT and other liver enzymes and markers of cardiovascular risk in adult twin pairs. Methods: We recruited 1134 men and 2241 women through the Australian Twin Registry. Data were collected through mailed questionnaires, telephone interviews, and by analysis of blood samples. Sources of variation in GGT, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) and of covariation between GGT and cardiovascular risk factors were assessed by maximum-likelihood model-fitting. Results: Serum GGT, ALT, and AST were affected by additive genetic and nonshared environmental factors, with heritabilities estimated at 0.52, 0.48, and 0.32, respectively. One-half of the genetic variance in GGT was shared with ALT, AST, or both. There were highly significant correlations between GGT and body mass index; serum lipids, lipoproteins, glucose, and insulin; and blood pressure. These correlations were more attributable to genes that affect both GGT and known cardiovascular risk factors than to environmental factors. Conclusions: Variation in serum enzymes that reflect liver function showed significant genetic effects, and there was evidence that both genetic and environmental factors that affect these enzymes can also affect cardiovascular risk. (C) 2002 American Association for Clinical Chemistry.

Global distribution and genetic discontinuities of mangroves - emerging patterns in the evolution of Rhizophora

Mangroves are often described as a group of plants with common features and common origins based mostly on their broad distributional patterns, together with an erroneous view of comparable abilities in long-distance dispersal. However, whilst mangroves have common needs to adapt to rigorous environmental constraints associated with regular seawater inundation, individual taxa have developed different strategies and characteristics. Since mangroves are a genetically diverse group of mostly flowering plants, they may also have evolved at quite different geological periods, dispersed at different rates from different locations and developed different adaptive strategies. Current distributions of individual taxa show numerous instances of unusual extant distribution which demonstrate finite dispersal limitations, especially across open water. Our preliminary assessment of broad distribution and discontinuities reveals important patterns. Discontinuities, in the absence of current dispersal barriers, may be explained by persistent past barriers. As we learn more about discontinuities, we are beginning to appreciate their immense implications and what they might tell us about past geological conditions and how these might have influenced the distribution and evolution of mangroves. In this article, we describe emerging patterns in genetic relationships and distributions based on both current knowledge and preliminary results of our studies of molecular and morphometric characteristics of Rhizophora species in the Indo West Pacific region.

Analysis of genetic diversity within Australian lucerne cultivars and implications for future genetic improvement

Lucerne (Medicago sativa L.) is autotetraploid, and predominantly allogamous. This complex breeding structure maximises the genetic diversity within lucerne populations making it difficult to genetically discriminate between populations. The objective of this study was to evaluate the level of random genetic diversity within and between a selection of Australian-grown lucerne cultivars, with tetraploid M. falcata included as a possible divergent control source. This diversity was evaluated using random amplified polymorphic DNA (RAPDs). Nineteen plants from each of 10 cultivars were analysed. Using 11 RAPD primers, 96 polymorphic bands were scored as present or absent across the 190 individuals. Genetic similarity estimates (GSEs) of all pair-wise comparisons were calculated from these data. Mean GSEs within cultivars ranged from 0.43 to 0.51. Cultivar Venus (0.43) had the highest level of intra-population genetic diversity and cultivar Sequel HR (0.51) had the lowest level of intra-population genetic diversity. Mean GSEs between cultivars ranged from 0.31 to 0.49, which overlapped with values obtained for within-cultivar GSE, thus not allowing separation of the cultivars. The high level of intra- and inter-population diversity that was detected is most likely due to the breeding of synthetic cultivars using parents derived from a number of diverse sources. Cultivar-specific polymorphisms were only identified in the M. falcata source, which like M. sativa, is outcrossing and autotetraploid. From a cluster analysis and a principal components analysis, it was clear that M. falcata was distinct from the other cultivars. The results indicate that the M. falcata accession tested has not been widely used in Australian lucerne breeding programs, and offers a means of introducing new genetic diversity into the lucerne gene pool. This provides a means of maximising heterozygosity, which is essential to maximising productivity in lucerne.

Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation

The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant’s pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant’s pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant’s main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant’s pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67±34μm and 108μm, and angular misfits of 0.15±0.08º and 1.4º, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants’ pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

Surgical correction of scoliosis: Numerical analysis and optimization of the procedure

A previously developed model is used to numerically simulate real clinical cases of the surgical correction of scoliosis. This model consists of one-dimensional finite elements with spatial deformation in which (i) the column is represented by its axis; (ii) the vertebrae are assumed to be rigid; and (iii) the deformability of the column is concentrated in springs that connect the successive rigid elements. The metallic rods used for the surgical correction are modeled by beam elements with linear elastic behavior. To obtain the forces at the connections between the metallic rods and the vertebrae geometrically, non-linear finite element analyses are performed. The tightening sequence determines the magnitude of the forces applied to the patient column, and it is desirable to keep those forces as small as possible. In this study, a Genetic Algorithm optimization is applied to this model in order to determine the sequence that minimizes the corrective forces applied during the surgery. This amounts to find the optimal permutation of integers 1, ... , n, n being the number of vertebrae involved. As such, we are faced with a combinatorial optimization problem isomorph to the Traveling Salesman Problem. The fitness evaluation requires one computing intensive Finite Element Analysis per candidate solution and, thus, a parallel implementation of the Genetic Algorithm is developed.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.