Comparative analyses of mitogenomes in the social bees with insights into evolution of long inverted repeats in the Meliponini

The insect mitogenome is typically a compact circular molecule with highly conserved gene contents.Nonetheless,mitogenome structural variations have been reported in specific taxa,and gene rearrangements,usually the tRNAs,occur in different lineages.Because synapomorphies of mitogenome organizations can provide information for phylogenetic inferences,comparative analyses of mitogenomes have been given increasing attention.However,most studies use a very few species to represent the whole genus,tribe,family,or even order,overlooking potential variations at lower taxonomic levels,which might lead to some incorrect inferences.To provide new insights into mitogenome organizations and their implications for phylogenetic inference,this study conducted comparative analyses for mitogenomes of three social bee tribes(Meliponini,Bombini,and Apini)based on the phylogenetic framework with denser taxonomic sampling at the species and population levels.Comparative analyses revealed that mitogenomes of Apini and Bombini are the typical type,while those of Meliponini show diverse variations in mitogenome sizes and organizations.Large inverted repeats(IRs)cause significant gene rearrangements of protein coding genes(PCGs)and rRNAs in Indo-Malay/Australian stingless bee species.Molecular evolution analyses showed that the lineage with IRs have lower dN/dS ratios for PCGs than lineages without IRs,indicating potential effects of IRs on the evolution of mitochondrial genes.The finding of IRs and different patterns of gene rearrangements suggested that Meliponini is a hotspot in mitogenome evolution.Unlike conserved PCGs and rRNAs whose rearrangements were found only in the mentioned lineages within Meliponini,tRNA rearrangements are common across all three tribes of social bees,and are significant even at the species level,indicating that comprehensive sampling is needed to fully understand the patterns of tRNA rearrangements,and their implications for phylogenetic inference.

Effect of Apis mellifera on community composition of local pollinator bees and their pollination network in Qinling Mountains and surrounding areas

The Qinling Mountains, known for their rich vegetation and diverse pollinating insects, have seen a significant decline in bee species richness and abundance over recent decades, largely due to the introduction and spread of Apis mellifera. This decline has caused cascading effects on the region's community structure and ecosystem stability. To improve the protection of native bees in the natural and agricultural landscape of the Qinling Mountains and its surrounding areas, we investigated 33 sampling sites within three habitats: forest, forest-agriculture ecotones, and farmland. Using a generalized linear mixing model, t-test, and other data analysis methods, we explored the impact of Apis mellifera on local pollinator bee richness, abundance, and the pollination network in different habitats in these regional areas. The results show that(1)Apis mellifera significantly negatively affects the abundance and richness of wild pollinator bees,while Apis cerana abundance is also affected by beekeeping conditions.(2)There are significant negative effects of Apis mellifera on the community structure of pollinator bees in the Qinling Mountains and its surrounding areas: the Shannon-Wiener diversity index, Pielou evenness index, and Margalef richness index of bee communities at sites with Apis mellifera influence were significantly lower than those at sites without Apis mellifera influence.(3)The underlying driver of this effect is the monopolization of flowering resources by Apis mellifera. This species tends to visit flowering plants with large nectar sources, which constitute a significant portion of the local plant community. By maintaining a dominant role in the bee-plant pollination network, Apis mellifera competitively displaces native pollinator bees, reducing their access to floral resources. This ultimately leads to a reduction in local bee-plant interactions, decreasing the complexity and stability of the pollination network. These findings highlight the need for targeted conservation efforts to protect native pollinator species and maintain the ecological balance in the Qinling Mountains.

Adaptive Network Sustainability and Defense Based on Artificial Bees Colony Optimization Algorithm for Nature Inspired Cyber Security

Cyber Defense is becoming a major issue for every organization to keep business continuity intact.The presented paper explores the effectiveness of a meta-heuristic optimization algorithm-Artificial Bees Colony Algorithm(ABC)as an Nature Inspired Cyber Security mechanism to achieve adaptive defense.It experiments on the Denial-Of-Service attack scenarios which involves limiting the traffic flow for each node.Businesses today have adapted their service distribution models to include the use of the Internet,allowing them to effectively manage and interact with their customer data.This shift has created an increased reliance on online services to store vast amounts of confidential customer data,meaning any disruption or outage of these services could be disastrous for the business,leaving them without the knowledge to serve their customers.Adversaries can exploit such an event to gain unauthorized access to the confidential data of the customers.The proposed algorithm utilizes an Adaptive Defense approach to continuously select nodes that could present characteristics of a probable malicious entity.For any changes in network parameters,the cluster of nodes is selected in the prepared solution set as a probable malicious node and the traffic rate with the ratio of packet delivery is managed with respect to the properties of normal nodes to deliver a disaster recovery plan for potential businesses.

Correlation between the Change in the Number of Apis mellifera Worker Bees and Nectar Secretion of Nectariferous Plants

[Objective] This study aimed to clarify the correlation between changes of Apis mel ifera and the nectar secretion characteristics of nectariferous plants. [Method] Considering the nectar secretion characteristics of major and auxiliary nec-tariferous plants, six Apis mel ifera colonies were selected for measure the number of eggs, larvae, pupae and adult bees from Jan. to Dec. in 2012; based on that, their annual change curves were also plotted. [Result] The results showed that there were three peaks of the total number of A. mel ifera workers throughout the year：the first occurred on May 15th, with bees developed into an ideal population for col-lecting pomegranate nectar, and the second and third peaks occurred on July 15th and Oct. 15th, respectively, with bees developed into an ideal population for col ect-ing E. ciliate （Thuab） Hyland. [Conclusion] Prevention of Varroa jacobsoni should be carried out with two or more types of acaricides at the late nectar flow stages of the two nectariferous plants（pomegranate and E. ciliate （Thuab） Hyland） when there was a nectar deficiency. Prevention of Tropilaelaps clareae should be timely per-formed with sublimed sulfur in conjunction with acaricides. This study provides a theoretical basis for the high-quality and high-yielding production of honey, as wel as for the product safety.

Bio-Inspired Binary Bees Algorithm for a Two-Level Distribution Optimisation Problem

Two uncoupleable distributions, assigning missions to robots and allocating robots to home stations, accompany the use ofmobile service robots in hospitals.In the given problem, two workload-related objectives and five groups of constraints areproposed.A bio-mimicked Binary Bees Algorithm (BBA) is introduced to solve this multiobjective multiconstraint combinatorialoptimisation problem, in which constraint handling technique (Multiobjective Transformation, MOT), multiobjectiveevaluation method (nondominance selection), global search strategy (stochastic search in the variable space), local searchstrategy (Hamming neighbourhood exploitation), and post-processing means (feasibility selection) are the main issues.TheBBA is then demonstrated with a case study, presenting the execution process of the algorithm, and also explaining the change ofelite number in evolutionary process.Its optimisation result provides a group of feasible nondominated two-level distributionschemes.

Ornamental Bee Plants as Foraging Resources for Urban Bees in Southern Brazil

Ornamental plants are distinguished by the shape and color of their leaves/flowers and their use in landscaping and gardening. In urban areas, their presence is relevant for the maintenance of bees. Aiming to list the ornamental bee plants species occurring in Santa Catarina State (SC), southern Brazil, a survey of forage resources for bees, recorded in the State, was performed. We refer all published works developed in SC (resulting in the period 1983-2014) which include data from reports of scientific research, monographs, dissertations, Masters Dissertations, Doctoral Thesis, annals of scientific events, scientific articles and books. From the 28 ensuant works, we listed, as ornamental bee plants occurring in SC, 201 species, of 156 genera and 66 botanical families. Of these species, 92 are native (N), 26 endemic to Brazil and 109 exotic (E). Families with more ornamental bee species are: Fabaceae (22 species), Asteraceae (20), Solanaceae (11), Rosaceae (10) and Lamiaceae (8). The most cited species are: Lantana camara L. (N) (Verbenaceae) (9 quotes), Aloysia virgata (N) (Ruiz & Pav.) Juss. (Verbenaceae) (8), Hedychium coronarium J. Koenig (naturalized) (Zingiberaceae) (6) and Brachyscome multifida (E) (Asteraceae) (5), regarding habitus, herbs (48.5%) predominate, followed by bushes (21.5%), trees (16.5%) and vines (10.5%). Preferred colours of flowers by bees are, in decreasing order: white, yellow, red/pink, and others. The genus Ipomoea, Calliandra, Passiflora, Prunus and Senecio have more ornamental bee plant species. A large botanical diversity arises, demonstrating the possibilities for urban bee foraging and ornamental featuring, in a perspective of sustainability.

Design of a Two-dimensional Recursive Filter Using the Bees Algorithm

This paper presents the first application of the bees algorithm to the optimisation of parameters of a two-dimensional （2D） recursive digital filter. The algorithm employs a search technique inspired by the foraging behaviour of honey bees. The results obtained show clear improvement compared to those produced by the widely adopted genetic algorithm （GA）.

Profile Analysis of the Proteome of the Egg of the High Royal Jelly Producing Bees (Apis mellifera L.)

The protein composition of the egg development in the high royal jelly producing bees （Apis mellifera L.） was investigated. This pioneer study was to separate and quantify the proteins in the egg of the high royal jelly producing worker bees （Apis mellifera L.） by using two-dimensional gel electrophoresis along with their three-day development. The results showed that 160, 195, and 176 proteins, with a wide range of molecular weight （17-80 KDa） and relatively narrow scope of pI （4. 00-8.40） could be detected on day 1, day 2, and day 3, respectively, during the developmental process of the egg. Meanwhile 44 protein spots were constantly detected along with the egg development. Among them 36% were in the uptrend along with the egg development, 14% were in the downtrend, and 39% were of the largest expressed volume on day 2. In addition, the specific proteins were expressed on day 1, day 2, and day 3 （89, 77, and 80, respectively）. Besides the coexistent and specific proteins, 24 proteins were expressed on day 1 and day 2, but silenced on day 3, 49 proteins were expressed on day 2 and day 3, but silenced on day 1, only 3 proteins were expressed on day 1 and day 3, but silenced on day 2. The result indicates that egg development is a sequential and complex gene controlled process, where the eggs of day 2 express the most active proteins. The coexistent proteins suggest that it is conservative and indispensable for this event. These specific proteins suggest that the different developmental stage needs specific proteins to regulate it.

Structure of the Venom Apparatus of Large Carpenter Bees, Xylocopa fenestrata （Fabricius） （Hymenoptera： Apidae）

The venom apparatus in the large carpenter bees, Xylocopafenestrata （Fabricius） （Hymenoptera： Apidae） has been studied It consists of typical parts, i.e., the venom sac, free filament, Dufour gland, sting shaft and accessory sclerites. It is highly sclerotized and concealed by the 7th abdominal tergite and sternite. The venom sac serves as a reservoir for the venom which synthesized by the convoluted gland present in it, which is remarkably uniform to that of ants. The median duct extends from lower portion of venom sac, which measures 2.5 ±0.17 mm （mean ＋ SD） （n = 20） in length. The Dufour gland is a tube-like structure which is inserted in the sting-bulb. The triangular plate is attached at terminal portion of rami, which is in turn attached with lancets. The gonostyli are paired long and tubular structure with 5.29 ± 0.23 mm （n = 20） in length. The sting length is 5.29 ±0.23 mm （n = 20）. The fulcral arm is well-developed with an inverse Y-shaped structure present beneath the sting-bulb. Barbs on the sting shaft are weakly developed in X fenestrata but well developed in ants. The venom apparatus ofX. fenestrata when compared is similar to the bees but differs from that of the wasps and ants.

Preliminary Analyses of Expression of Learning and Memory Related Genes in Honey Bees (<i>Apis mellifera</i>) in Free-Choice Learning Paradigms

Honey bees are an established animal model for studying learning and memory related behaviors. In recent years, honey bees have become more common as a model for investigations of molecular biology, including gene expression. Honey bees have been used to extrapolate genetic functions found in other invertebrates, such as Drosophila melanogaster. The honey bee model has also provided a means for isolating novel genes, including non-coding microRNA fragments. Integrating the study of learning and memory with molecular genetics, the present work examines the effect of learning acquisition and memory consolidation in free-choice paradigms on the expression of a suite of genes of interest. Results suggest that short-term learning acquisition causes differential expression of microRNA fragments, while memory consolidation differentially affects the expression of the serine/threonine protein kinase gene in honey bees. These results corroborate previous findings suggesting the importance of protein kinases in the formation of long term memory, and suggest that microRNA may play a large role in regulation of cytoskeletal scaffolding proteins.

Characteristic of Species Composition of Fungi Involved in the Formation of Mycobiota of Honey Bees in Azerbaijan

The purpose of the presented work was dedicated to identifying the species composition of the mycobiota of honey bees in Azerbaijan condition. From the samples taken from bees, materials became clear that in the formation of mycobiota those materials (from bees, from where they live and their products) in generally participate 52 species of fungi. Among the recorded fungi, species take part such as Alternaria alternata (Fr.) Keissl., Aspergillus flavus Link, Candida albicans (C.P. Robin) Berkhout, Cladosporium herbarum (Pers.) Link, Penicillium cuclopium Westling, P. granulatum Bainier and etc. which carry features conditionally pathogenicity, toxicity, allergens and danger to biological productivity of bees and as well as to pollution of their products. It is known for a long time to scientists that these species are dangerous for human health. For this reason, preparation of normative documents that reflect the principles of microbiological safety of bee products is a necessary task.

Identification of Sugar,Amino Acids and Minerals from the Pollen of Jandaíra Stingless Bees(Melipona subnitida)

The aim of this investigation was to analyze two samples of pollen from jandaíra stingless bees (Melipona subnitida) in view of their mineral composition, free amino acids and sugars. Palynological analysis showed that the predominant pollen was monofloral from Senna sp. species (94.5%, pollen 2011) and the second pollen sample showed the presence of two primary species, Chamaecrista sp. (39.2% pollen 2009) and Mimosa tenuiflora (43.5%) (pollen 2009). The highest mineral content was potassium. The bee pollen contained 20.8% and 31.0% of mannitol in samples from 2011 and 2009, respectively. Proline and serine are the predominant amino acids. High content of essential amino acids, minerals and the sugar mannitol confirmed high nutritional value of pollen samples from jandaíra bees.

Asian Honey Bees Use Trace Amount Chemical to Avoid Danger

While foraging,animals can form inter-and intra-specific social signaling(i.e.one organism using signals to alert another about danger)networks to avoid similar predators.Honey bee sting alarm pheromones are multi-component blends,for instance isopentyl acetate(IPA),octyl acetate(OA),benzyl acetate(BA),etc.However,the

Comparative Analyses of Proteome Complement Between Worker Bee Larvae of High Royal Jelly Producing Bees (A. m. ligustica) and Carniolian Bees (A. m. carnica)

This study is to compare the protein composition of the high royal jelly producing bee （A. m. ligustica） with that of Carniolian bee （A. m. carnica） during their worker larval developmental stage. The experiment was carried out by two- dimensional gel electrophoresis. The results showed that significant higher numbers of total proteins （283） were detected in larvae of high royal jelly producing bees （Jelly bee） than those of Carniolian bees （152） on 2-d-old larvae. Among them, 110 proteins were presented on both strains of bee larvae, whereas 173 proteins were specific to larvae of Jelly bees, and 42 proteins were exclusive to Carniolian larvae. However, on the 4th d, a significant higher number of total proteins （290） were detected in larvae of Jelly bees than those of Carniolian bees （240）, 163 proteins resolved to both bee larvae, and 127 proteins were specific to Jelly bees and 77 proteins to Camiolian bees. Until the 6th d, also a significant higher number of total proteins （236） were detected in larvae of Jelly bees than those of Carniolian bees （180）, 132 proteins were constantly expressed in two bee larvae, whereas 104 and 48 proteins are unique to Jelly bee and Carniolian bee larvae, respectively. We tentatively concluded that the metabolic rate and gene expression of Jelly bees larvae is higher than those of Carniolian bees based proteins detected as total proteins and proteins specific to each stage of two strains of bee larvae. Proteins constantly expressed on 3 stages of larval development with some significant differences between two bee strains, and proteins unique to each stage expressed differences in term of quality and quantity, indicating that larval development needed house keeping and specific proteins to regulate its growth at different development phage, but the expression mold is different between two strains of larval development.

Massive Envenomation by Bees Sting in a Child in Togo

Attacks by swarm of bees realize arrays of mass poisoning. We report the case of a 9 years old boy whoes severity was related to the large number of bees which was about 400 and their locations spread throughout the skin surface with a preponderance to the cephalic end. Complications were hemolytic anemia, kidney failure and convulsions. The outcome was favorable with symptomatic care and hemodialysis.

A Survey of Pesticide Residues in Pollen Collected by Honey Bees from Four Different Types of Agricultural Production Areas in Slovenia

150 pollen samples collected between the years 2009 and 2011 from 30 locations, divided according to agricultural practice were analysed for the presence of pesticides. In 2009, residues were found in pollen samples from twelve locations （40%）, in 2010, in samples from four locations （13.3%） and in 2011, in samples from three locations （10%）. Altogether 15 different residues in pollen were found in 2009, two in year 2010 and five in 2011. Residues found in the pollen samples ranged from 0.001 mg/kg to 76 mg/kg. The highest number （twelve） of residues was found in pollen from the intensive fruit farming locations and from the intensive viticulture locations （eight）. The residues were mostly from the fungicide group （69%）. Insecticide residues （chlorpyrifos-ethyl, methoxyfenozide, thiacloprid） were found in the pollen samples from eight locations. Residues in the pollen did not statistically influence the development of the honeybee colonies or infestation rate of Nosema （Nosema spp.）, or viruses ABPV （acute bee paralysis virus）, SBV （sacbrood virus）, DWV （deformed wing virus）, and BQCV （black queen cell virus））.

Graph attention convolutional neural network model for chemical poisoning of honey bees’ prediction

The impact of pesticides on insect pollinators has caused worldwide concern. Both global bee decline and stopping the use of pesticides may have serious consequences for food security. Automated and accurate prediction of chemical poisoning of honey bees is a challenging task owing to a lack of understanding of chemical toxicity and introspection. Deep learning(DL) shows potential utility for general and highly variable tasks across fields. Here, we developed a new DL model of deep graph attention convolutional neural networks(GACNN) with the combination of undirected graph(UG) and attention convolutional neural networks(ACNN) to accurately classify chemical poisoning of honey bees. We used a training dataset of 720 pesticides and an external validation dataset of 90 pesticides, which is one order of magnitude larger than the previous datasets. We tested its performance in two ways: poisonous versus nonpoisonous and GACNN versus other frequently-used machine learning models. The first case represents the accuracy in identifying bee poisonous chemicals. The second represents performance advantages. The GACNN achieved ~6% higher performance for predicting toxic samples and more stable with ~7%Matthews Correlation Coefficient(MCC) higher compared to all tested models, demonstrating GACNN is capable of accurately classifying chemicals and has considerable potential in practical applications.In addition, we also summarized and evaluated the mechanisms underlying the response of honey bees to chemical exposure based on the mapping of molecular similarity. Moreover, our cloud platform(http://beetox.cn) of this model provides low-cost universal access to information, which could vitally enhance environmental risk assessment.

Finite element model updating of a large structure using multi-setup stochastic subspace identification method and bees optimization algorithm

In the present contribution, operational modal analysis in conjunction with bees optimization algorithm are utilized to update the finite element model of a solar power plant structure. The physical parameters which required to be updated are uncertain parameters including geometry, material properties and boundary conditions of the aforementioned structure. To determine these uncertain parameters, local and global sensitivity analyses are performed to increase the solution accuracy. An objective function is determined using the sum of the squared errors between the natural frequencies calculated by finite element method and operational modal analysis, which is optimized using bees optimization algorithm. The natural frequencies of the solar power plant structure are estimated by multi-setup stochastic subspace identification method which is considered as a strong and efficient method in operational modal analysis. The proposed algorithm is efficiently implemented on the solar power plant structure located in Shahid Chamran university of Ahvaz, Iran, to update parameters of its finite element model. Moreover, computed natural frequencies by numerical method are compared with those of the operational modal analysis. The results indicate that, bees optimization algorithm leads accurate results with fast convergence.

Bumblebees adjust protein and lipid collection rules to the presence of brood

Animals have evolved foraging strategies to acquire blends of nutrients that maximize fitness traits. In social insects, nu trie nt regulation is complicated by the fact that few in dividuals, the foragers, must address the diverge nt nutritional n eeds of all colony members simulta neously, includi ng other workers, the reproductives, and the brood. Here we used 3D nutritional geometry design to examine how bumblebee workers regulate their collection of 3 major macronutrients in the presence and absenee of brood. We provided small colonies artificial nectars (liquid diets) and pollens (solid diets) varying in their compositions of proteins, lipids, and carbohydrates during 2 weeks. Colo nies give n a choice betwee n nutrition ally complementary diets self-selected foods to reach a target ratio of 71% proteins, 6% carbohydrates, and 23% lipids, irrespective of the presenee of brood. Whe n con fined to a single nutrition ally imbalanced solid diet, colonies without brood regulated lipid collection and over-collected protein relative to this target ratio, whereas colonies with brood regulated both lipid and protein collection. This brood effect on the regulation of nutrient collection by workers suggests that protein levels are critical for larval development. Our results highlight the importa nee of con sidering bee nu trition as a multidimensi onal phe no men on to better assess the effects of environmental impoverishment and malnutrition on population declines.

Effects of Imidacloprid and Varroa destructor on survival and health of European honey bees, Apis mellifera

There has been growing concern over declines in populations of honey bees and other pollinators which are a vital part to our food security. It is imperative to identify factors responsible for accelerated declines in bee populations and develop solutions for reversing bee losses. While exact causes of colony losses remain elusive, risk factors thought to play key roles are ectoparasitic mites Varroa destructor and neonicotinoid pesticides. The present study aims to investigate effects of a neonicotinoid pesticide Imidacloprid and Varroa mites individually on survivorship, growth, physiology, virus dynamics and immunity of honey bee workers. Our study provides clear evidence that the exposure to sublethal doses of Imidacloprid could exert a significantly negative effect on health and survival of honey bees. We observed a significant reduction in the titer ofvitellogenin （Vg）, an egg yolk precursor that regulates the honey bees development and behavior and often are linked to energy homeostasis, in bees exposed to lmidacloprid. This result indicates that sublethal exposure to neonicotinoid could lead to increased energy usage in honey bees as detoxification is a energy-consuming metabolic process and suggests that Vg could be a useful biomarker for measuring levels of energy stress and sublethal effects of pesticides on honey bees. Measurement of the quantitative effects of different levels of Varroa mite infestation on the replication dynamic of Deformed wing virus （DWV）, an RNA virus associated with Varroa infestation, and expression level of immune genes yields unique insights into how honey bees respond to stressors under laboratory conditions.