Pupal parasitoid attack influences the relative fitness of Drosophila that have encapsulated larval parasitoids

1. The evolution of host resistance to parasitoid attack will be constrained by two factors: the costs of the ability to defend against attack, and the costs of surviving actual attack. These factors have been investigated using Drosophila melanogaster and its parasitoids as a model system. The costs of defensive ability are expressed as a trade-off with larval competitive ability, whereas the costs of actual defence are exhibited in terms of reduced adult fecundity and size. 2. The costs of actual defence may be ameliorated by the host-choice decisions made by Pachycrepoideus vindemiae, a pupal parasitoid. If larvae that have successfully encapsulated a parasitoid develop into poorer quality hosts, then these may be rejected by ovipositing pupal parasitoids. 3. Pupae developing from larvae that have encapsulated the parasitoid Asobara tabida are smaller and have relatively thinner puparia. Thinner puparia are likely to be associated with a reduction in mechanical strength and possibly with a decrease in desiccation tolerance. 4. Pachycrepoideus vindemiae that develop in capsule-bearing pupae are smaller than those that emerge from previously unattacked hosts. This supports the prediction that ovipositing female P. vindemiae should avoid attacking capsule-bearing hosts. However, in choice experiments with 1-day-old pupae, P. vindemiae females oviposited preferentially in hosts containing a capsule, whereas there was no preference found with 4-day-old hosts. This appears to be a maladaptive host choice decision, as the female pupal parasitoids are preferentially attacking hosts that will result in a reduction of their own fitness. 5. The increased likelihood of attack by a pupal parasitoid is another cost of actual defence against larval parasitoid attack.

Influence of temperature on pea aphid Acyrthosiphon pisum (Hemiptera: Aphididae) resistance to natural enemy attack

The ability to resist or avoid natural enemy attack is a critically important insect life history trait, yet little is understood of how these traits may be affected by temperature. This study investigated how different genotypes of the pea aphid Acyrthosiphon pisum Harris, a pest of leguminous crops, varied in resistance to three different natural enemies (a fungal pathogen, two species of parasitoid wasp and a coccinellid beetle), and whether expression of resistance was influenced by temperature. Substantial clonal variation in resistance to the three natural enemies was found. Temperature influenced the number of aphids succumbing to the fungal pathogen Erynia neoaphidis Remaudiere & Hermebert, with resistance increasing at higher temperatures (18 vs. 28degreesC). A temperature difference of 5degreesC (18 vs. 23degreesC) did not affect the ability of A. pisum to resist attack by the parasitoids Aphidius ervi Haliday and A. eadyi Stary Gonzalez & Hall. Escape behaviour from foraging coccinellid beetles (Hippodamia convergens Guerin-Meneville) was not directly influenced by aphid clone or temperature (16 vs. 21degreesC). However, there were significant interactions between clone and temperature (while most clones did not respond to temperature, one was less likely to escape at 16degreesC), and between aphid clone and ladybird presence (some clones showed greater changes in escape behaviour in response to the presence of foraging coccinellids than others). Therefore, while larger temperature differences may alter interactions between Acyrthosiphon pisum and an entomopathogen, there is little evidence to suggest that smaller changes in temperature will alter pea aphid-natural enemy interactions.

Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

Auto-weighted minimum-variance self-tuning controller

A self-tuning controller which automatically assigns weightings to control and set-point following is introduced. This discrete-time single-input single-output controller is based on a generalized minimum-variance control strategy. The automatic on-line selection of weightings is very convenient, especially when the system parameters are unknown or slowly varying with respect to time, which is generally considered to be the type of systems for which self-tuning control is useful. This feature also enables the controller to overcome difficulties with non-minimum phase systems.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Weighted input predictive controller

A discrete-time algorithm is presented which is based on a predictive control scheme in the form of dynamic matrix control. A set of control inputs are calculated and made available at each time instant, the actual input applied being a weighted summation of the inputs within the set. The algorithm is directly applicable in a self-tuning format and is therefore suitable for slowly time-varying systems in a noisy environment.

Adaptive general predictive controller for nonlinear systems

A nonlinear general predictive controller (NLGPC) is described which is based on the use of a Hammerstein model within a recursive control algorithm. A key contribution of the paper is the use of a novel, one-step simple root solving procedure for the Hammerstein model, this being a fundamental part of the overall tuning algorithm. A comparison is made between NLGPC and nonlinear deadbeat control (NLDBC) using the same one-step nonlinear components, in order to investigate NLGPC advantages and disadvantages.

Regulation of the cardiomyocyte transcriptome vs translatome by endothelin-1 and insulin: translational regulation of 5' terminal oligopyrimidine tract (TOP) mRNAs by insulin

Background: Changes in cellular phenotype result from underlying changes in mRNA transcription and translation. Endothelin-1 stimulates cardiomyocyte hypertrophy with associated changes in mRNA/protein expression and an increase in the rate of protein synthesis. Insulin also increases the rate of translation but does not promote overt cardiomyocyte hypertrophy. One mechanism of translational regulation is through 5' terminal oligopyrimidine tracts (TOPs) that, in response to growth stimuli, promote mRNA recruitment to polysomes for increased translation. TOP mRNAs include those encoding ribosomal proteins, but the full panoply remains to be established. Here, we used microarrays to compare the effects of endothelin-1 and insulin on the global transcriptome of neonatal rat cardiomyocytes, and on mRNA recruitment to polysomes (i.e. the translatome). Results: Globally, endothelin-1 and insulin (1 h) promoted >1.5-fold significant (false discovery rate < 0.05) changes in expression of 341 and 38 RNAs, respectively. For these transcripts with this level of change there was little evidence of translational regulation. However, 1336 and 712 RNAs had >1.25-fold significant changes in expression in total and/or polysomal RNA induced by endothelin-1 or insulin, respectively, of which ~35% of endothelin-1-responsive and ~56% of insulin-responsive transcripts were translationally regulated. Of mRNAs for established proteins recruited to polysomes in response to insulin, 49 were known TOP mRNAs with a further 15 probable/possible TOP mRNAs, but 49 had no identifiable TOP sequences or other consistent features in the 5' untranslated region. Conclusions: Endothelin-1, rather than insulin, substantially affects global transcript expression to promote cardiomyocyte hypertrophy. Effects on RNA recruitment to polysomes are subtle, with differential effects of endothelin-1 and insulin on specific transcripts. Furthermore, although insulin promotes recruitment of TOP mRNAs to cardiomyocyte polysomes, not all recruited mRNAs are TOP mRNAs.

Conserved hydrophobic clusters on the surface of the Caf1A usher C-terminal domain are important for F1 antigen assembly

The outer membrane usher protein Caf1A of the plague pathogen Yersinia pestis is responsible for the assembly of a major surface antigen, the F1 capsule. The F1 capsule is mainly formed by thin linear polymers of Caf1 (capsular antigen fraction 1) protein subunits. The Caf1A usher promotes polymerization of subunits and secretion of growing polymers to the cell surface. The usher monomer (811 aa, 90.5 kDa) consists of a large transmembrane β-barrel that forms a secretion channel and three soluble domains. The periplasmic N-terminal domain binds chaperone-subunit complexes supplying new subunits for the growing fiber. The middle domain, which is structurally similar to Caf1 and other fimbrial subunits, serves as a plug that regulates the permeability of the usher. Here we describe the identification, characterization, and crystal structure of the Caf1A usher C-terminal domain (Caf1A(C)). Caf1A(C) is shown to be a periplasmic domain with a seven-stranded β-barrel fold. Analysis of C-terminal truncation mutants of Caf1A demonstrated that the presence of Caf1A(C) is crucial for the function of the usher in vivo, but that it is not required for the initial binding of chaperone-subunit complexes to the usher. Two clusters of conserved hydrophobic residues on the surface of Caf1A(C) were found to be essential for the efficient assembly of surface polymers. These clusters are conserved between the FGL family and the FGS family of chaperone-usher systems.

c-Jun N-terminal kinase (JNK)-mediated modulation of brain mitochondria function: new target proteins for JNK signalling in mitochondrion-dependent apoptosis

The molecular mechanisms underlying the initiation and control of the release of cytochrome c during mitochondrion-dependent apoptosis are thought to involve the phosphorylation of mitochondrial Bcl-2 and Bcl-x(L). Although the c-Jun N-terminal kinase (JNK) has been proposed to mediate the phosphorylation of Bcl-2/Bcl-x(L) the mechanisms linking the modification of these proteins and the release of cytochrome c remain to be elucidated. This study was aimed at establishing interdependency between JNK signalling and mitochondrial apoptosis. Using an experimental model consisting of isolated, bioenergetically competent rat brain mitochondria, these studies show that (i) JNK catalysed the phosphorylation of Bcl-2 and Bcl-x(L) as well as other mitochondrial proteins, as shown by two-dimensional isoelectric focusing/SDS/PAGE; (ii) JNK-induced cytochrome c release, in a process independent of the permeability transition of the inner mitochondrial membrane (imPT) and insensitive to cyclosporin A; (iii) JNK mediated a partial collapse of the mitochondrial inner-membrane potential (Deltapsim) in an imPT- and cyclosporin A-independent manner; and (iv) JNK was unable to induce imPT/swelling and did not act as a co-inducer, but as an inhibitor of Ca-induced imPT. The results are discussed with regard to the functional link between the Deltapsim and factors influencing the permeability transition of the inner and outer mitochondrial membranes. Taken together, JNK-dependent phosphorylation of mitochondrial proteins including, but not limited to, Bcl-2/Bcl-x(L) may represent a potential of the modulation of mitochondrial function during apoptosis.

Joint modelling of obstacle induced and mesoscale changes: current limits and challenges

Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.