Olfactory selection of Plantago lanceolata by snails declines with seedling age

Background and Aims Despite recent recognition that (1) plant–herbivore interactions during the establishment phase, (2) ontogenetic shifts in resource allocation and (3) herbivore response to plant volatile release are each pivotal to a comprehensive understanding of plant defence, no study has examined how herbivore olfactory response varies during seedling ontogeny. Methods Using a Y-tube olfactometer we examined snail (Helix aspersa) olfactory response to pellets derived from macerated Plantago lanceolata plants harvested at 1, 2, 3, 4, 5, 6 and 8 weeks of age to test the hypothesis that olfactory selection of plants by a generalist herbivore varies with plant age. Plant volatiles were collected for 10 min using solid-phase microextraction technique on 1- and 8-week-old P. lanceolata pellets and analysed by gas chromatography coupled with a mass spectrometer. Key Results Selection of P. lanceolata was strongly negatively correlated with increasing age; pellets derived from 1-week-old seedlings were three times more likely to be selected as those from 8-week-old plants. Comparison of plant selection experiments with plant volatile profiles from GC/MS suggests that patterns of olfactory selection may be linked to ontogenetic shifts in concentrations of green leaf volatiles and ethanol (and its hydrolysis derivatives). Conclusions Although confirmatory of predictions made by contemporary plant defence theory, this is the first study to elucidate a link between seedling age and olfactory selection by herbivores. As a consequence, this study provides a new perspective on the ontogenetic expression of seedling defence, and the role of seedling herbivores, particularly terrestrial molluscs, as selective agents in temperate plant communities.

Visual Object Recognition Using Deformable Models of Vehicles

This workshop paper reports recent developments to a vision system for traffic interpretation which relies extensively on the use of geometrical and scene context. Firstly, a new approach to pose refinement is reported, based on forces derived from prominent image derivatives found close to an initial hypothesis. Secondly, a parameterised vehicle model is reported, able to represent different vehicle classes. This general vehicle model has been fitted to sample data, and subjected to a Principal Component Analysis to create a deformable model of common car types having 6 parameters. We show that the new pose recovery technique is also able to operate on the PCA model, to allow the structure of an initial vehicle hypothesis to be adapted to fit the prevailing context. We report initial experiments with the model, which demonstrate significant improvements to pose recovery.

A Generic Deformable Model for Vehicle Recognition

This paper reports the development of a highly parameterised 3-D model able to adopt the shapes of a wide variety of different classes of vehicles (cars, vans, buses, etc), and its subsequent specialisation to a generic car class which accounts for most commonly encountered types of car (includng saloon, hatchback and estate cars). An interactive tool has been developed to obtain sample data for vehicles from video images. A PCA description of the manually sampled data provides a deformable model in which a single instance is described as a 6 parameter vector. Both the pose and the structure of a car can be recovered by fitting the PCA model to an image. The recovered description is sufficiently accurate to discriminate between vehicle sub-classes.

Sox1-deficient mice suffer from epilepsy associated with abnormal ventral forebrain development and olfactory cortex hyperexcitability

Mutations in several classes of embryonically-expressed transcription factor genes are associated with behavioral disorders and epilepsies. However, there is little known about how such genetic and neurodevelopmental defects lead to brain dysfunction. Here we present the characterization of an epilepsy syndrome caused by the absence of the transcription factor SOX1 in mice. In vivo electroencephalographic recordings from SOX1 mutants established a correlation between behavioral changes and cortical output that was consistent with a seizure origin in the limbic forebrain. In vitro intracellular recordings from three major forebrain regions, neocortex, hippocampus and olfactory (piriform) cortex (OC) showed that only the OC exhibits abnormal enhanced synaptic excitability and spontaneous epileptiform discharges. Furthermore, the hyperexcitability of the OC neurons was present in mutants prior to the onset of seizures but was completely absent from both the hippocampus and neocortex of the same animals. The local inhibitory GABAergic neurotransmission remained normal in the OC of SOX1-deficient brains, but there was a severe developmental deficit of OC postsynaptic target neurons, mainly GABAergic projection neurons within the olfactory tubercle and the nucleus accumbens shell. Our data show that SOX1 is essential for ventral telencephalic development and suggest that the neurodevelopmental defect disrupts local neuronal circuits leading to epilepsy in the SOX1-deficient mice

A novel component of cannabis extract potentiates excitatory synaptic transmission in rat olfactory cortex in vitro

Cannabis is a potential treatment for epilepsy, although the few human studies supporting this use have proved inconclusive. Previously, we showed that a standardized cannabis extract (SCE), isolated Delta(9)-tetrahydrocannabinol (Delta(9)-THC), and even Delta(9)-THC-free SCE inhibited muscarinic agonist-induced epileptiform bursting in rat olfactory cortical brain slices, acting via CB1 receptors. The present work demonstrates that although Delta(9)-THC (1microM) significantly depressed evoked depolarizing postsynaptic potentials (PSPs) in rat olfactory cortex neurones, both SCE and Delta(9)-THC-free SCE significantly potentiated evoked PSPs (all results were fully reversed by the CB1 receptor antagonist SR141716A, 1microM); interestingly, the potentiation by Delta(9)-THC-free SCE was greater than that produced by SCE. On comparing the effects of Delta(9)-THC-free SCE upon evoked PSPs and artificial PSPs (aPSPs; evoked electrotonically following brief intracellular current injection), PSPs were enhanced, whereas aPSPs were unaffected, suggesting that the effect was not due to changes in background input resistance. Similar recordings made using CB1 receptor-deficient knockout mice (CB1(-/-)) and wild-type littermate controls revealed cannabinoid or extract-induced changes in membrane resistance, cell excitability and synaptic transmission in wild-type mice that were similar to those seen in rat neurones, but no effect on these properties were seen in CB1(-/-) cells. It appears that the unknown extract constituent(s) effects over-rode the suppressive effects of Delta(9)-THC on excitatory neurotransmitter release, which may explain some patients' preference for herbal cannabis rather than isolated Delta(9)-THC (due to attenuation of some of the central Delta(9)-THC side effects) and possibly account for the rare incidence of seizures in some individuals taking cannabis recreationally

Host plant recognition by the root feeding clover weevil, Sitona lepidus (Coleoptera : Curculionidae)

This study investigated the ability of neonatal larvae of the root-feeding weevil, Sitona lepidus Gyllenhal, to locate white clover Trifolium repens L. (Fabaceae) roots growing in soil and to distinguish them from the roots of other species of clover and a co-occurring grass species. Choice experiments used a combination of invasive techniques and the novel technique of high resolution X-ray microtomography to non-invasively track larval movement in the soil towards plant roots. Burrowing distances towards roots of different plant species were also examined. Newly hatched S. lepidus recognized T. repens roots and moved preferentially towards them when given a choice of roots of subterranean clover, Trifolium subterraneum L. (Fabaceae), strawberry clover Trifolium fragiferum L. (Fabaceae), or perennial ryegrass Lolium perenne L. (Poaceae). Larvae recognized T. repens roots, whether released in groups of five or singly, when released 25 mm (meso-scale recognition) or 60 mm (macro-scale recognition) away from plant roots. There was no statistically significant difference in movement rates of larvae.

Cross-modal preference acquisition: evaluative conditioning of pictures by affective olfactory and auditory cues

In this research, a cross-model paradigm was chosen to test the hypothesis that affective olfactory and auditory cues paired with neutral visual stimuli bearing no resemblance or logical connection to the affective cues can evoke preference shifts in those stimuli. Neutral visual stimuli of abstract paintings were presented simultaneously with liked and disliked odours and sounds, with neutral-neutral pairings serving as controls. The results confirm previous findings that the affective evaluation of previously neutral visual stimuli shifts in the direction of contingently presented affective auditory stimuli. In addition, this research shows the presence of conditioning with affective odours having no logical connection with the pictures.

Less-is-more effects without the recognition heuristic

Inferences consistent with “recognition-based” decision-making may be drawn for various reasons other than recognition alone. We demonstrate that, for 2-alternative forced-choice decision tasks, less-is-more effects (reduced performance with additional learning) are not restricted to recognition-based inference but can also be seen in circumstances where inference is knowledge-based but item knowledge is limited. One reason why such effects may not be observed more widely is the dependence of the effect on specific values for the validity of recognition and knowledge cues. We show that both recognition and knowledge validity may vary as a function of the number of items recognized. The implications of these findings for the special nature of recognition information, and for the investigation of recognition-based inference, are discussed

Syk-Dependent Cytokine Induction by Dectin-1 Reveals a Novel Pattern Recognition Pathway for C Type Lectins

Pattern-recognition receptors (PRRs) detect molecular signatures of microbes and initiate immune responses to infection. Prototypical PRRs such as Toll-like receptors (TLRs) signal via a conserved pathway to induce innate response genes. In contrast, the signaling pathways engaged by other classes of putative PRRs remain ill defined. Here, we demonstrate that the β-glucan receptor Dectin-1, a yeast binding C type lectin known to synergize with TLR2 to induce TNFα and IL-12, can also promote synthesis of IL-2 and IL-10 through phosphorylation of the membrane proximal tyrosine in the cytoplasmic domain and recruitment of Syk kinase. syk−/− dendritic cells (DCs) do not make IL-10 or IL-2 upon yeast stimulation but produce IL-12, indicating that the Dectin-1/Syk and Dectin-1/TLR2 pathways can operate independently. These results identify a novel signaling pathway involved in pattern recognition by C type lectins and suggest a potential role for Syk kinase in regulation of innate immunity.

Olfactory attractiveness of mixtures of some host plant and conspecific semiochemicals to the banana weevil Cosmopolites sordidus (Germar, 1824)

A simple "Y" shaped olfactometer was used in laboratory studies on the olfactory attractiveness of mixtures in various proportions of industrial analogues of some host plant and conspecific-based semiochemicals, or their combinations with banana rhizome, to the banana weevil. The aim was to identify factors that influence their attractiveness to the weevil, and consider the possibility for their use as lures for trapping the weevil in the field. Cosmopolites sordidus was attracted to the mixtures at specific concentrations and proportions of constituent chemicals. 6-methylhept-5-en-2-one was only attractive on its own at 1 µl/100 ml and in mixture with 4- mercaptophenol, but not at 10 µl, 0.01 µl, or in combination with banana rhizome. 4-mercaptohpenol and 2-n-butylfuran, which were compatible with most host plant-based chemicals and were attractive as a mixture, were perceived to be key elements in the composition of attractants to the weevil. It was concluded that in addition to the composition, other factors that may determine the attractiveness or otherwise of a mixture to C. sordidus are the proportions and concentrations of the constituent chemicals.

Intrinsic disorder prediction from the analysis of multiple protein fold recognition models

Motivation: Intrinsic protein disorder is functionally implicated in numerous biological roles and is, therefore, ubiquitous in proteins from all three kingdoms of life. Determining the disordered regions in proteins presents a challenge for experimental methods and so recently there has been much focus on the development of improved predictive methods. In this article, a novel technique for disorder prediction, called DISOclust, is described, which is based on the analysis of multiple protein fold recognition models. The DISOclust method is rigorously benchmarked against the top.ve methods from the CASP7 experiment. In addition, the optimal consensus of the tested methods is determined and the added value from each method is quantified. Results: The DISOclust method is shown to add the most value to a simple consensus of methods, even in the absence of target sequence homology to known structures. A simple consensus of methods that includes DISOclust can significantly outperform all of the previous individual methods tested.

Benchmarking consensus model quality assessment for protein fold recognition

Background: Selecting the highest quality 3D model of a protein structure from a number of alternatives remains an important challenge in the field of structural bioinformatics. Many Model Quality Assessment Programs (MQAPs) have been developed which adopt various strategies in order to tackle this problem, ranging from the so called "true" MQAPs capable of producing a single energy score based on a single model, to methods which rely on structural comparisons of multiple models or additional information from meta-servers. However, it is clear that no current method can separate the highest accuracy models from the lowest consistently. In this paper, a number of the top performing MQAP methods are benchmarked in the context of the potential value that they add to protein fold recognition. Two novel methods are also described: ModSSEA, which based on the alignment of predicted secondary structure elements and ModFOLD which combines several true MQAP methods using an artificial neural network. Results: The ModSSEA method is found to be an effective model quality assessment program for ranking multiple models from many servers, however further accuracy can be gained by using the consensus approach of ModFOLD. The ModFOLD method is shown to significantly outperform the true MQAPs tested and is competitive with methods which make use of clustering or additional information from multiple servers. Several of the true MQAPs are also shown to add value to most individual fold recognition servers by improving model selection, when applied as a post filter in order to re-rank models. Conclusion: MQAPs should be benchmarked appropriately for the practical context in which they are intended to be used. Clustering based methods are the top performing MQAPs where many models are available from many servers; however, they often do not add value to individual fold recognition servers when limited models are available. Conversely, the true MQAP methods tested can often be used as effective post filters for re-ranking few models from individual fold recognition servers and further improvements can be achieved using a consensus of these methods.

High throughput profile-profile based fold recognition for the entire human proteome

BACKGROUND: In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power.In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. RESULTS: We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. CONCLUSION: This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.