A distributed-delay model to predict ageing and survival rates of adults of Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) in granaries filled with wheat

A time-varying distributed-delay model simulating effects of multifactors was developed. Prediction of the ageing rate and survival distribution of adults of the rusty grain beetle, Cryptolestes ferrugineus (Stephens) (Coleoptera: Laemophloeidae) in various environments found in wheat-filled granaries was conducted as an example to illustrate the application of this developed model. Published adult mortalities, determined at different temperatures, relative humidities, and food sources, were directly used to find the average ageing rate and family of cumulative function of adult mortality. The developed model could predict the adult survival rate at constant or transient temperatures with different relative humidities. This model could also simulate the effect of adult acclimation to their environment when they experience temperature and moisture fluctuations inside granaries. To validate the developed model, the simulation results were compared with available experimental data from the literature. There was no difference between predicted and measured mortalities in two granaries in which the mortalities were determined in a 4-month experiment.     

Microprobe studies of aluminum accumulation in association with human central nervous system disease

The neurofibrillary tangle, first described by Alzheimer in 1907, along with the senile plaque, represent the two principle neuropathologic lesions identified in the brains of patients with Alzheimer's disease. Aluminum salts inoculated into the central nervous system of certain experimental animals induces neurofilamentous lesions which are similar, but not identical to the neurofibrillary tangles seen in Alzheimer's disease. Although some reports provide evidence of increased amounts of aluminum in the brains of Alzheimer's disease victims, such bulk analysis studies have been difficult to replicate. Over the past several years we have approached this problem using a variety of microprobe techniques in order to determine the distribution of trace elements within individual nerve cells.Using scanning electron microscopy with X-ray spectrometry, we have identified accumulations of aluminum in the neurofibrillary tangle-bearing neurons of cases of Alzheimer's disease. Similar accumulations have been found in the brains of the indigenous natives of Guam who suffer from parkinsonism with dementia and from amyotrophic lateral sclerosis. Recent studies using laser microprobe mass analysis suggest that the predominance of aluminum identified within the parikaryon of neurofibrillary tangle-bearing neurons is located within the neurofibrillary tangle itself. Although this ongoing research still cannot ascribe a causal role for aluminum in the etiology and/or pathogenesis of the neurofibrillary tangle, the data suggest that certain environmental factors related to trace elemental constituents may play an important role in the formation of this type of cellular pathology.     

On the integration of individual foraging strategies with colony ergonomics in social insects: nectar-collection in honeybees

Summary We experimentally tested whether foraging strategies of nectar-collecting workers of the honeybee (Apis mellifera) vary with colony state. In particular, we tested the prediction that bees from small, fast growing colonies should adopt higher workloads than those from large, mature colonies. Queenright small colonies were set up by assembling 10 000 worker bees with approximately 4100 brood cells. Queenright large colonies contained 35 000 bees and some 14 500 brood cells. Thus, treatments differed in colony size but not in worker/brood ratios. Differences in workload were tested in the context of single foraging cycles. Individuals could forage on a patch of artificial flowers offering given quantities and qualities of nectar rewards. Workers of small colonies took significantly less nectar in an average foraging excursion (small: 40.1 ± 1.1 SE flowers; large: 44.8 ± 1.1), but spent significantly more time handling a flower (small: 7.3 ± 0.4 s ; large: 5.8 ± 0.4 s). When the energy budgets for an average foraging trip were calculated, individuals from all colonies showed a behavior close to maximization of net energetic efficiency (i.e., the ratio of net energetic gains to energetic costs). However, bees from small colonies, while incurring only marginally smaller costs, gained less net energy per foraging trip than those from large colonies, primarily as a result of prolonged handling times. The differences between treatments were largest during the initial phases of the experimental period when also colony development was maximally different. Our results are at variance with simple models that assume natural selection to have shaped behavior in a single foraging trip only so as to maximize colony growth. Offprint requests to: P. Schmid-Hempel     

The hydrolytic products of aluminum and their biological significance

The relative distribution of Al between its various organic and inorganic complexes dictates its mobility in the environment, bioavailability, and toxicity. In recent years, there has been significant progress made in understanding the differential bioavailability and toxicity of various chemical species of Al to plants and certain aquatic organisms. Far less information concerning chemical speciation and differential uptake and transport of Al in humans is available. Among the important inorganic complexes of interest are the hydrolyzed-Al species, particularly the nonequilibrium, metastable polynuclear complexes, which form readily, have a fairly wide stability range, and have been demonstrated toxic to plants and fish. In recent years²⁷Al NMR spectroscopy has provided significant direct information on the polynuclear complexes existing in a wide range of aqueous solutions. The [Al₁₂O₄(OH)_24+n(H₂O)_12–n]^(7–n)+ polynuclear complex is often found to be the predominant species in partially neutralized Al solutions and has recently been demonstrated to be more toxic to certain plants than the hexaaqua Al cation. It is also the principal component of Al-chlorohydrate, a highly soluble antiperspirant, present in many hydrolyzed Al solutions utilized in water and waste water treatment, and, as hypothesized herein, a primary constituent of many hydroxide gels utilized as antacids. This polynuclear has a wide pH stability range, reportedly forms copolynuclears with Si, and contains tetrahedrally coordinated Al within its structure, all features that may be relevant to the recently reported properties of Al associated with neuritic plaque cores.     

Using the expert model PERPEST to translate measured and predicted pesticide exposure data into ecological risks

An important topic in the registration of pesticides and the interpretation of monitoring data is the estimation of the consequences of a certain concentration of a pesticide for the ecology of aquatic ecosystems. Solving these problems requires predictions of the expected response of the ecosystem to chemical stress. Up until now, a dominant approach to come up with such a prediction is the use of simulation models or safety factors. The disadvantage of the use of safety factors is a crude method that does not provide any insight into the concentration–response relationships at the ecosystem level. On the other hand, simulation models also have serious drawbacks like that they are often very complex, lack transparency, their implementation is expensive and there may be a compilation of errors, due to uncertainties in parameters and processes. In this paper, we present the expert model prediction of the ecological risks of pesticides (PERPEST) that overcomes these problems. It predicts the effects of a given concentration of a pesticide based on the outcome of already performed experiments using experimental ecosystems. This has the great advantage that the outcome is more realistic. The paper especially discusses how this model can be used to translate measured and predicted concentrations of pesticides into ecological risks, by taking data on measured and predicted concentrations of atrazine as an example. It is argued that this model can be of great use to evaluate the outcome of chemical monitoring programmes (e.g. performed in the light of the Water Framework Directive) and can even be used to evaluate the effects of mixtures.