Body size differs in workers produced across time and is associated with variation in the quantity and composition of larval food in Nannotrigona perilampoides (Hymenoptera, Meliponini)

Although variation in body size has been recently reported in stingless bees (Meliponini), empirical evidence evaluating possible factors related to such variation is lacking, and thus it is not clear if it may have an adaptive significance. We evaluated if variation in the body size and weight of workers of stingless bees fluctuates across a seasonal pattern and if this could be related to characteristics of the food consumed during the larval stage. The weight of larval provisions, their protein, and sugar content were evaluated in four colonies of Nannotrigona perilampoides every 2 months across 1 year. Worker-destined larvae from the same combs were allowed to develop and were sampled as callow workers to determine their weight and size using morphometric data. The weight and size of workers were highly correlated and varied across the seasons in established colonies, suggesting that size variation cycles across the year in stingless bees. An increase in the protein content and, to a lesser degree, the quantity of larval food were positively linked to variation in body weight and size; food with richer protein content resulted in larger and heavier workers. This study provides the first evidence of an effect of the quantity and composition of larval food on the size of workers in stingless bees. Although body weight and size of workers differed across seasons, they were not readily noticeable as changes seem to occur as a continuum across the year. Since size polymorphism was of a larger magnitude across time but not within age cohorts and as it was highly determined by food resources, it may not be an adaptive feature in stingless bees. However, more studies are needed to determine the role of the cyclical change in worker body size on colony performance and thus its adaptive significance in stingless bees.

A Critical Review of Screening Methods for the Detection of Chloramphenicol, Thiamphenicol, and Florfenicol Residues in Foodstuffs

This article gives an extensive overview of the wide range of analytical procedures developed for the detection of amphenicol antibiotic residues (chloramphenicol, thiamphenicol, and florfenicol) in many different types of foodstuffs (milk, meat, eggs, honey, seafood). Screening methods such as microbial inhibition methods, antibody-based immunoassays using conventional and biosensor-based detection systems, and some methods based on alternative recognition systems are described. The relative advantages and disadvantages of these methods are discussed and compared. The current status and future trends and developments in the need for accurate and rapid detection of this group of antimicrobials are also discussed.

Reduction of sample matrix effects - The analysis of benzimidazole residues in serum by immunobiosensor

Regulatory authorities, the food industry and the consumer demand reliable determination of chemical contaminants present in foods. A relatively new analytical technique that addresses this need is an immunobiosensor based on surface plasmon resonance (SPR) measurements. Although a range of tests have been developed to measure residues in milk, meat, animal bile and honey, a considerable problem has been encountered with both serum and plasma samples. The high degree of non-specific binding of some sample components can lead to loss of assay robustness, increased rates of false positives and general loss of assay sensitivity. In this paper we describe a straightforward precipitation technique to remove interfering substances from serum samples to be analysed for veterinary anthelmintics by SPR. This technique enabled development of an assay to detect a wide range of benzimidazole residues in serum samples by immunobiosensor. The limit of quantification was below 5 ng/ml and coefficients of variation were about 2%.

RUNX3 downregulation in human lung adenocarcinoma is independent of p53, EGFR or KRAS status

RUNX3 aberrations play a pivotal role in the oncogenesis of breast, gastric, colon, skin and lung tissues. The aim of this study was to characterize further the expression of RUNX3 in lung cancers. To achieve this, a lung cancer tissue microarray (TMA), frozen lung cancer tissues and lung cell lines were examined for RUNX3 expression by immunohistochemistry, while the TMA was also examined for EGFR and p53 expression. RUNX3 promoter methylation status, and EGFR and KRAS mutation status were also investigated. Inactivation of RUNX3 was observed in 70% of the adenocarcinoma samples, and this was associated with promoter hypermethylation but not biased to EGFR/KRAS mutations. Our results suggest a central role of RUNX3 downregulation in pulmonary adenocarcinoma, which may not be dependent of other established cancer-causing pathways and may have important diagnostic and screening implications.

Response of farmland biodiversity to the introduction of bioenergy crops: effects of local factors and surrounding landscape context

The recent growth in bioenergy crop cultivation, stimulated by the need to implement measures to reduce net CO emissions, is driving major land-use changes with consequences for biodiversity and ecosystem service provision. Although the type of bioenergy crop and its associated management is likely to affect biodiversity at the local (field) scale, landscape context and its interaction with crop type may also influence biodiversity on farms. In this study, we assessed the impact of replacing conventional agricultural crops with two model bioenergy crops (either oilseed rape Brassica napus or Miscanthus × giganteus) on vascular plant, bumblebee, solitary bee, hoverfly and carabid beetle richness, diversity and abundance in 50 sites in Ireland. We assessed whether within-field biodiversity was also related to surrounding landscape structure. We found that local- and landscape-scale variables correlated with biodiversity in these agricultural landscapes. Overall, the differences between the bioenergy crops and the conventional crops on farmland biodiversity were mostly positive (e.g. higher vascular plant richness in Miscanthus planted on former conventional tillage, higher solitary bee abundance and richness in Miscanthus and oilseed rape compared with conventional crops) or neutral (e.g. no differences between crop types for hoverflies and bumblebees). We showed that these crop type effects were independent of (i.e. no interactions with) the surrounding landscape composition and configuration. However, surrounding landscape context did relate to biodiversity in these farms, negatively for carabid beetles and positively for hoverflies. Although we conclude that the bioenergy crops compared favourably with conventional crops in terms of biodiversity of the taxa studied at the field scale, the effects of large-scale planting in these landscapes could result in very different impacts. Maintaining ecosystem functioning and the delivery of ecosystem services will require a greater understanding of impacts at the landscape scale to ensure the sustainable development of climate change mitigation measures.

A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed bees

Declining populations of bee pollinators are a cause of concern, with major repercussions for biodiversity loss and food security. RNA viruses associated with honeybees represent a potential threat to other insect pollinators, but the extent of this threat is poorly understood. This study aims to attain a detailed understanding of the current and ongoing risk of emerging infectious disease (EID) transmission between managed and wild pollinator species across a wide range of RNA viruses. Within a structured large-scale national survey across 26 independent sites, we quantify the prevalence and pathogen loads of multiple RNA viruses in co-occurring managed honeybee (Apis mellifera) and wild bumblebee (Bombus spp.) populations. We then construct models that compare virus prevalence between wild and managed pollinators. Multiple RNA viruses associated with honeybees are widespread in sympatric wild bumblebee populations. Virus prevalence in honeybees is a significant predictor of virus prevalence in bumblebees, but we remain cautious in speculating over the principle direction of pathogen transmission. We demonstrate species-specific differences in prevalence, indicating significant variation in disease susceptibility or tolerance. Pathogen loads within individual bumblebees may be high and in the case of at least one RNA virus, prevalence is higher in wild bumblebees than in managed honeybee populations. Our findings indicate widespread transmission of RNA viruses between managed and wild bee pollinators, pointing to an interconnected network of potential disease pressures within and among pollinator species. In the context of the biodiversity crisis, our study emphasizes the importance of targeting a wide range of pathogens and defining host associations when considering potential drivers of population decline.

Spatio-temporal feeding selection of red deer in a mountainous landscape

Understanding the dietary consumption and selection of wild populations of generalist herbivores is hampered by the complex array of factors. Here, we determine the influence of habitat, season, and animal density, sex, and age on the diet consumption and selection of 426 red deer (Cervus elaphus scoticus) culled in Fiordland National Park, New Zealand. Our site differs from studies elsewhere both in habitat (evergreen angiosperm-dominated forests) and the intensity of hunting pressures. We predicted that deer would not consume forage in proportion to its relative availability, and that dietary consumption would change among and within years in response to hunting pressures that would also limit opportunities for age and sex segregation. Using canonical correspondence analysis, we evaluated the relative importance of different drivers of variation in diet consumption assessed from gut content and related these to available forage in the environment. We found that altitude explained the largest proportion of variation in diet consumption, reflecting the ability of deer to alter their consumption and selection in relation to their foraging grounds. Grasses formed a high proportion of the diet consumption, even for deer culled several kilometres from the alpine grasslands. In the winter months, when the alpine grasslands were largely inaccessible, less grass was eaten and deer resorted to woody plants that were avoided in the summer months. Surprisingly, there were no significant dietary differences between adults and juveniles and only subtle differences between the sexes. Sex-based differences in diet consumption are commonly observed in ungulate species and we suggest that they may have been reduced in our study area owing to decreased heterogeneity in available forage as the diversity of palatable species decreased under high deer browsing pressures, or by intense hunting pressure. © 2009 The Authors. Journal compilation © 2009 Ecological Society of Australia.

A Hybrid Swarm Based Approach in Addressing University Timetabling Problems

This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

A Hybrid Imperialist Approach in Solving University Timetabling Problems. Information Sciences. Vol. 283, 1-21

Generating timetables for an institution is a challenging and time consuming task due to different demands on the overall structure of the timetable. In this paper, a new hybrid method which is a combination of a great deluge and artificial bee colony algorithm (INMGD-ABC) is proposed to address the university timetabling problem. Artificial bee colony algorithm (ABC) is a population based method that has been introduced in recent years and has proven successful in solving various optimization problems effectively. However, as with many search based approaches, there exist weaknesses in the exploration and exploitation abilities which tend to induce slow convergence of the overall search process. Therefore, hybridization is proposed to compensate for the identified weaknesses of the ABC. Also, inspired from imperialist competitive algorithms, an assimilation policy is implemented in order to improve the global exploration ability of the ABC algorithm. In addition, Nelder–Mead simplex search method is incorporated within the great deluge algorithm (NMGD) with the aim of enhancing the exploitation ability of the hybrid method in fine-tuning the problem search region. The proposed method is tested on two differing benchmark datasets i.e. examination and course timetabling datasets. A statistical analysis t-test has been conducted and shows the performance of the proposed approach as significantly better than basic ABC algorithm. Finally, the experimental results are compared against state-of-the art methods in the literature, with results obtained that are competitive and in certain cases achieving some of the current best results to those in the literature.