Age determination in individual wild-caught Drosophila serrata using pteridine concentration

Fluorescence spectrophotometry can reliably detect levels of the pteridine 6-biopterin in the heads of individual Drosophila serrata Malloch 1927. Pteridine content in both laboratory and field captured flies is typically a level of magnitude higher than the minimally detectable level (mean(lab)=0.54 units, mean(field)=0.44 units, minimum detectable level=0.01 units) and can be used to predict individual age in laboratory populations with high certainty (r(2)=57%). Laboratory studies of individuals of known age ( from 1 to 48 days old) indicate that while pteridine level increases linearly with age, they also increase in a linear manner with rearing temperature and ambient light levels, but are independent of sex. As expected, the longevity of laboratory-reared males ( at least 48 days) is higher than the range of predicted ages of wild-caught males based on individual pteridine levels (40 days). However, the predictive equation based on pteridine level alone suggested that a number of wild-caught males were less than 0 days old, and the 95% confidence for these predictions based on the inverse regression broad. The age of the oldest wild-caught male is to fall within the range of 2 to 50 days. The effects of temperature and light intensity determined in laboratory study (effect sizes omega(2)=14.3 and respectively) suggests that the calibration of the prediction equation for field populations would significantly improved when combined with fine scaled studies of habitat temperature and light conditions. ability to determine relative age in individual wild-caught D. serrata presents great opportunities for a variety evolutionary studies on the dynamics of populations.

Effect of drying conditions on pyrethrins content

Windrowed pyrethrum stems were air dried under a range of storage conditions to examine whether the current commercial practice of drying crop material is conducive to pyrethrins' degradation. Crop material was stored for up to 12 days in a commercial windrow, a shed receiving indirect light or a dark, 5 degrees C cool-room. Analysis of pyrethrins extracted from flowers of all treatments demonstrated that pyrethrins were not degrading in windrowed crops, plant material stored in the shed or in the 5 degrees C cool-room. The small differences obtained in pyrethrins content among the treatments can be explained by the natural variation in pyrethrins content of pyrethrum crops. The observation that the achenes were unchanged during this drying period supported the pyrethrins analysis. These results demonstrate that pyrethrins in planta do not degrade as rapidly as extracted pyrethrins. (C) 2005 Elsevier B.V. All rights reserved.

Ryk: A novel Wnt receptor regulating axon pathfinding

Members of the Wnt family and their receptors, the Frizzleds, are key regulators of pivotal developmental processes including embryonic patterning, specification of cell fate, and determination of cell polarity. The versatility and complexity of Wnt signaling has been further highlighted by the emergence of a novel family of Wnt receptors, the Ryk family. In mammals and flies, Ryk is a key chemorepulsive axon guidance receptor responsible for the establishment of important axon tracts during nervous system development. Although the function of Ryk is currently best understood with respect to this role, its widespread expression, both in developing tissues and in the adult, suggests that Ryk may regulate many essential biological processes. This hypothesis is supported by the multiple developmental phenotypes apparent in Ryk loss-of-function mice. These mice display a variety of embryonic abnormalities, including disruption of skeletal, craniofacial and cardiac development. Here we review Ryk structure and function focusing on its activity as an axon guidance receptor. (c) 2006 Elsevier Ltd. All rights reserved.

A diverse suite of spiroacetals, including a novel branched representative, is released by female Bactrocera tryoni (Queensland fruit fly)

A remarkably diverse suite of spiroacetals including a novel member of the rare, branched chain class has been identified in the glandular secretions of Bactrocera tryoni, the most destructive horticultural pest in Australia.

Cephalosphaera Enderlein, a genus of Pipunculidae (Diptera) new for Australia, with descriptions of four new species

Cephalosphaera Enderlein is a nearly cosmopolitan genus of big-headed flies (Pipunculidae) which was previously unknown from Australia. Four species have now been found in Australia, all of them undescribed. New species in the subgenus Neocephalosphaera include: C. eukrenaina, C. parthenopipis and C. petila. Only one new species occurs in the nominate subgenus: C. prionotaina. Descriptions and a key to these species are presented.

Time trials on second-order and variable-learning-rate algorithms

The performance of seven minimization algorithms are compared on five neural network problems. These include a variable-step-size algorithm, conjugate gradient, and several methods with explicit analytic or numerical approximations to the Hessian.

Bayesian training of mixture density networks

Mixture Density Networks (MDNs) are a well-established method for modelling the conditional probability density which is useful for complex multi-valued functions where regression methods (such as MLPs) fail. In this paper we extend earlier research of a regularisation method for a special case of MDNs to the general case using evidence based regularisation and we show how the Hessian of the MDN error function can be evaluated using R-propagation. The method is tested on two data sets and compared with early stopping.

Incorporating curvature information into on-line learning

We analyse the dynamics of a number of second order on-line learning algorithms training multi-layer neural networks, using the methods of statistical mechanics. We first consider on-line Newton's method, which is known to provide optimal asymptotic performance. We determine the asymptotic generalization error decay for a soft committee machine, which is shown to compare favourably with the result for standard gradient descent. Matrix momentum provides a practical approximation to this method by allowing an efficient inversion of the Hessian. We consider an idealized matrix momentum algorithm which requires access to the Hessian and find close correspondence with the dynamics of on-line Newton's method. In practice, the Hessian will not be known on-line and we therefore consider matrix momentum using a single example approximation to the Hessian. In this case good asymptotic performance may still be achieved, but the algorithm is now sensitive to parameter choice because of noise in the Hessian estimate. On-line Newton's method is not appropriate during the transient learning phase, since a suboptimal unstable fixed point of the gradient descent dynamics becomes stable for this algorithm. A principled alternative is to use Amari's natural gradient learning algorithm and we show how this method provides a significant reduction in learning time when compared to gradient descent, while retaining the asymptotic performance of on-line Newton's method.

The dynamics of matrix momentum

We analyse the matrix momentum algorithm, which provides an efficient approximation to on-line Newton's method, by extending a recent statistical mechanics framework to include second order algorithms. We study the efficacy of this method when the Hessian is available and also consider a practical implementation which uses a single example estimate of the Hessian. The method is shown to provide excellent asymptotic performance, although the single example implementation is sensitive to the choice of training parameters. We conjecture that matrix momentum could provide efficient matrix inversion for other second order algorithms.

Bayesian error bars for regression

Regression problems are concerned with predicting the values of one or more continuous quantities, given the values of a number of input variables. For virtually every application of regression, however, it is also important to have an indication of the uncertainty in the predictions. Such uncertainties are expressed in terms of the error bars, which specify the standard deviation of the distribution of predictions about the mean. Accurate estimate of error bars is of practical importance especially when safety and reliability is an issue. The Bayesian view of regression leads naturally to two contributions to the error bars. The first arises from the intrinsic noise on the target data, while the second comes from the uncertainty in the values of the model parameters which manifests itself in the finite width of the posterior distribution over the space of these parameters. The Hessian matrix which involves the second derivatives of the error function with respect to the weights is needed for implementing the Bayesian formalism in general and estimating the error bars in particular. A study of different methods for evaluating this matrix is given with special emphasis on the outer product approximation method. The contribution of the uncertainty in model parameters to the error bars is a finite data size effect, which becomes negligible as the number of data points in the training set increases. A study of this contribution is given in relation to the distribution of data in input space. It is shown that the addition of data points to the training set can only reduce the local magnitude of the error bars or leave it unchanged. Using the asymptotic limit of an infinite data set, it is shown that the error bars have an approximate relation to the density of data in input space.

Ecological studies on river pollution control

This collection of papers records a series of studies, carried out over a period of some 50 years, on two aspects of river pollution control - the prevention of pollution by sewage biological filtration and the monitoring of river pollution by biological surveillance. The earlier studies were carried out to develop methods of controlling flies which bred in the filters and caused serious nuisance and possible public health hazard, when they dispersed to surrounding villages. Although the application of insecticides proved effective as an alleviate measure, because it resulted in only a temporary disturbance of the ecological balance, it was considered ecologically unsound as a long-term solution. Subsequent investigations showed that the fly populations in filters were largely determined by the amount of food available to the grazing larval stage in the form of filter film. It was also established that the winter deterioration in filter performance was due to the excessive accumulation of film. Subsequent investigations were therefore carried out to determine the factors responsible for the accumulation of film in different types of filter. Methods of filtration which were considered to control film accumulation by increasing the flushing action of the sewage, were found to control fungal film by creating nutrient limiting conditions. In some filters increasing the hydraulic flushing reduced the grazing fauna population in the surface layers and resulted in an increase in film. The results of these investigations were successfully applied in modifying filters and in the design of a Double Filtration process. These studies on biological filters lead to the conclusion that they should be designed and operated as ecological systems and not merely as hydraulic ones. Studies on the effects of sewage effluents on Birmingham streams confirmed the findings of earlier workers justifying their claim for using biological methods for detecting and assessing river pollution. Further ecological studies showed the sensitivity of benthic riffle communities to organic pollution. Using experimental channels and laboratory studies the different environmental conditions associated with organic pollution were investigated. The degree and duration of the oxygen depletion during the dark hours were found to be a critical factor. The relative tolerance of different taxa to other pollutants, such as ammonia, differed. Although colonisation samplers proved of value in sampling difficult sites, the invertebrate data generated were not suitable for processing as any of the commonly used biotic indexes. Several of the papers, which were written by request for presentation at conferences etc., presented the biological viewpoint on river pollution and water quality issues at the time and advocated the use of biological methods. The information and experiences gained in these investigations was used as the "domain expert" in the development of artificial intelligence systems for use in the biological surveillance of river water quality.

L-carnosine affects the growth of Saccharomyces cerevisiae in a metabolism-dependent manner

The dipeptide L-carnosine (β-alanyl-L-histidine) has been described as enigmatic: it inhibits growth of cancer cells but delays senescence in cultured human fibroblasts and extends the lifespan of male fruit flies. In an attempt to understand these observations, the effects of L-carnosine on the model eukaryote, Saccharomyces cerevisiae, were examined on account of its unique metabolic properties; S. cerevisiae can respire aerobically, but like some tumor cells, it can also exhibit a metabolism in which aerobic respiration is down regulated. L-Carnosine exhibited both inhibitory and stimulatory effects on yeast cells, dependent upon the carbon source in the growth medium. When yeast cells were not reliant on oxidative phosphorylation for energy generation (e.g. when grown on a fermentable carbon source such as 2% glucose), 10-30 mM L-carnosine slowed growth rates in a dose-dependent manner and increased cell death by up to 17%. In contrast, in media containing a non-fermentable carbon source in which yeast are dependent on aerobic respiration (e.g. 2% glycerol), L-carnosine did not provoke cell death. This latter observation was confirmed in the respiratory yeast, Pichia pastoris. Moreover, when deletion strains in the yeast nutrient-sensing pathway were treated with L-carnosine, the cells showed resistance to its inhibitory effects. These findings suggest that L-carnosine affects cells in a metabolism-dependent manner and provide a rationale for its effects on different cell types. © 2012 Cartwright et al.

Saccharomyces Cerevisiae as a biotechnological tool for ageing research:studies on translation and metabolism

The yeast Saccharomyces cerevisiae is an important model organism for the study of cell biology. The similarity between yeast and human genes and the conservation of fundamental pathways means it can be used to investigate characteristics of healthy and diseased cells throughout the lifespan. Yeast is an equally important biotechnological tool that has long been the organism of choice for the production of alcoholic beverages, bread and a large variety of industrial products. For example, yeast is used to manufacture biofuels, lubricants, detergents, industrial enzymes, food additives and pharmaceuticals such as anti-parasitics, anti-cancer compounds, hormones (including insulin), vaccines and nutraceuticals. Its function as a cell factory is possible because of the speed with which it can be grown to high cell yields, the knowledge that it is generally recognized as safe (GRAS) and the ease with which metabolism and cellular pathways, such as translation can be manipulated. In this thesis, these two pathways are explored in the context of their biotechnological application to ageing research: (i) understanding translational processes during the high-yielding production of membrane protein drug targets and (ii) the manipulation of yeast metabolism to study the molecule, L-carnosine, which has been proposed to have anti-ageing properties. In the first of these themes, the yeast strains, spt3?, srb5?, gcn5? and yTHCBMS1, were examined since they have been previously demonstrated to dramatically increase the yields of a target membrane protein (the aquaporin, Fps1) compared to wild-type cells. The mechanisms underlying this discovery were therefore investigated. All high yielding strains were shown to have an altered translational state (mostly characterised by an initiation block) and constitutive phosphorylation of the translational initiation factor, eIF2a. The relevance of the initiation block was further supported by the finding that other strains, with known initiation blocks, are also high yielding for Fps1. A correlation in all strains between increased Fps1 yields and increased production of the transcriptional activator protein, Gcn4, suggested that yields are subject to translational control. Analysis of the 5´ untranslated region (UTR) of FPS1 revealed two upstream open reading frames (uORFs). Mutagenesis data suggest that high yielding strains may circumvent these control elements through either a leaky scanning or a re-initiation mechanism. In the second theme, the dipeptide L-carnosine (ß-alanyl-L-histidine) was investigated: it has previously been shown to inhibit the growth of cancer cells but delay senescence in cultured human fibroblasts and extend the lifespan of male fruit flies. To understand these apparently contradictory properties, the effects of L-carnosine on yeast were studied. S. cerevisiae can respire aerobically when grown on a non-fermentable carbon source as a substrate but has a respiro-fermentative metabolism when grown on a fermentable carbon source; these metabolisms mimic normal cell and cancerous cell metabolisms, respectively. When yeast were grown on fermentable carbon sources, in the presence of L-carnosine, a reduction in cell growth and viability was observed, which was not apparent for cells grown on a non-fermentable carbon source. The metabolism-dependent mechanism was confirmed in the respiratory yeast species Pichia pastoris. Further analysis of S. cerevisiae yeast strains with deletions in their nutrient-sensing pathway, which result in an increase in respiratory metabolism, confirmed the metabolism-dependent effects of L-carnosine.

The interaction between metabolic disease and ageing

Two of the greatest crises that civilisation faces in the 21st century are the predicted rapid increases in the ageing population and levels of metabolic disorders such as obesity and type 2 diabetes. A growing amount of evidence now supports the notion that energy balance is a key determinant not only in metabolism but also in the process of cellular ageing. Much of genetic evidence for a metabolic activity-driven ageing process has come from model organisms such as worms and flies where inactivation of the insulin receptor signalling cascade prolongs lifespan. At its most simplistic, this poses a conundrum for ageing in humans – can reduced insulin receptor signalling really promote lifespan and does this relate to insulin resistance seen in ageing? In higher animals, caloric restriction studies have confirmed a longer lifespan when daily calorie intake is reduced to 60% of normal energy requirement. This suggests that for humans, it is energy excess which is a likely driver of metabolic ageing. Interventions that interfere with the metabolic fate of nutrients offer a potentially important target for delaying biological ageing.