The taxonomy of honey bee A. mellifera contains a lot of issues due to the specificity of population structure, features of biology and resolutions of honey bee subspecies discrimination methods. There are a lot of transition zones between ranges of subspecies which led to the gradual changes of characteristics among neighbor subspecies. The modern taxonomic pattern of honey bee Apis mellifera is given in this paper. Thirty-three distinct honey bee subspecies are distributed across all Africa (11 subspecies), Western Asia and the Middle East (9 subspecies), and Europe (13 subspecies). All honey bee subspecies are subdivided into 5 evolutionary lineages: lineage A (10 subspecies) and its sublineage Z (3 subspecies), lineage M (3 subspecies), lineage C (10 subspecies), lineage O (3 subspecies), lineage Y (1 subspecies), lineage C or O (3 subspecies).

Image-based automatic classification of vector mosquitoes has been investigated for decades for its practical applications such as early detection of potential mosquitoes-borne diseases. However, the classification accuracy of previous approaches has never been close to human experts’ and often images of mosquitoes with certain postures and body parts, such as flatbed wings, are required to achieve good classification performance. Deep convolutional neural networks (DCNNs) are state-of-the-art approach to extracting visual features and classifying objects, and, hence, there exists great interest in applying DCNNs for the classification of vector mosquitoes from easy-to-acquire images. In this study, we investigated the capability of state-of-the-art deep learning models in classifying mosquito species having high inter-species similarity and intra-species variations. Since no off-the-shelf dataset was available capturing the variability of typical field-captured mosquitoes, we constructed a dataset with about 3,600 images of 8 mosquito species with various postures and deformation conditions. To further address data scarcity problems, we investigated the feasibility of transferring general features learned from generic dataset to the mosquito classification. Our result demonstrated that more than 97% classification accuracy can be achieved by fine-tuning general features if proper data augmentation techniques are applied together. Further, we analyzed how this high classification accuracy can be achieved by visualizing discriminative regions used by deep learning models. Our results showed that deep learning models exploit morphological features similar to those used by human experts.

Mitochondria are one of the organelles undergoing rapid alteration during the senescence process. Senescent cells show an increase in mitochondrial size, which is attributed to the accumulation of defective mitochondria, which causes mitochondrial oxidative stress. Defective mitochondria are also targets of mitochondrial oxidative stress, and the vicious cycle between defective mitochondria and mitochondrial oxidative stress contributes to the onset and development of aging and age-related diseases. Based on the findings, strategies to reduce mitochondrial oxidative stress have been suggested for the effective treatment of aging and age-related diseases. In this article, we discuss mitochondrial alterations and the consequent increase in mitochondrial oxidative stress. Then, the causal role of mitochondrial oxidative stress on aging is investigated by examining how aging and age-related diseases are exacerbated by induced stress. Furthermore, we assess the importance of targeting mitochondrial oxidative stress for the regulation of aging and suggest different therapeutic strategies to reduce mitochondrial oxidative stress. Therefore, this review will not only shed light on a new perspective on the role of mitochondrial oxidative stress in aging but also provide effective therapeutic strategies for the treatment of aging and age-related diseases through the regulation of mitochondrial oxidative stress.

Mitochondria are one of organelles that undergo significant changes associated with senescence. An increase in mitochondrial size is observed in senescent cells, and this increase is ascribed to the accumulation of dysfunctional mitochondria that generate excessive reactive oxygen species (ROS). Such dysfunctional mitochondria are prime targets for ROS-induced damage, which leads to the deterioration of oxidative phosphorylation and increased dependence on glycolysis as an energy source. Based on findings indicating that senescent cells exhibit mitochondrial metabolic alterations, a strategy to induce mitochondrial metabolic reprogramming has been proposed to treat aging and age-related diseases. In this review, we discuss senescence-related mitochondrial changes and consequent mitochondrial metabolic alterations. We assess the significance of mitochondrial metabolic reprogramming for senescence regulation and propose the appropriate control of mitochondrial metabolism to ameliorate senescence. Learning how to regulate mitochondrial metabolism will provide knowledge for the control of aging and age-related pathologies. Further research focusing on mitochondrial metabolic reprogramming will be an important guide for the development of anti-aging therapies, and will provide novel strategies for anti-aging interventions.

Umami taste perception indicates the presence of amino acids, which are essential nutrients. Although the physiology of umami perception has been described in mammals, how insects detect amino acids remains unknown except in Drosophila melanogaster. We functionally characterized a gustatory receptor responding to L-amino acids in the western honey bee, Apis mellifera. Using a calcium-imaging assay and two-voltage clamp recording, we found that one of the honey bee’s gustatory receptors, AmGr10, functions as a broadly tuned amino acid receptor responding to glutamate, aspartate, asparagine, arginine, lysine, and glutamine, but not to other sweet or bitter compounds. Furthermore, the sensitivity of AmGr10 to these L-amino acids was dramatically enhanced by purine ribonucleotides, like inosine-5′-monophosphate (IMP). Contact sensory hairs in the mouthpart of the honey bee responded strongly to glutamate and aspartate, which house gustatory receptor neurons expressing AmGr10. Interestingly, AmGr10 protein is highly conserved among hymenopterans but not other insects, implying unique functions in eusocial insects.

Apis cerana is an Eastern honeybee species distributed throughout Asia and closely related to the Western honeybee species Apis mellifera distributed across all of Africa, Europe and Western Asia, and subdivided into thirty confirmed subspecies. Currently, A. cerana is an endangered bee species in contrast to A. mellifera. We sequenced and annotated the complete mitochondrial genome of A. cerana from the Jeollanam-do province of South Korea and uploaded to the DDBJ/Genbank database(AP018431). MtDNA sequence is 15.925 bp long, has 84% AT-content and 16% GC-content and contains 22 tRNA genes, 13 protein-coding genes, two ribosomal RNA genes, one AT-rich region and four non-coding intergenic regions ( NC1-4 ). All protein-coding genes are started by ATT and ATG codons, except the genes ATP8 and ND4 , which started by ATC and ATA, respectively, and are stopped by the common codons TAA and TAG. A comparative analysis of the whole mtDNA sequences of A. cerana from Korea and Taiwan, A. c. cerana from China and A. c. japonica from Japan showed that the genetic divergence of the Korean A. cerana sample from subspecies A. c. cerana (2.57%) and A. c. japonica (2.58%) matched to the level of genetic divergence of mtDNA between animal subspecies (0.8-8%). Based on the comparative analysis of complete mtDNA (~16,000 bp), two nuclear gene VG and EF1- α sequences (~8,000 bp) and morphological measurements (six parameters), we assumed that Korean A. cerana , Chinese A. c. cerana and Japanese A. c. japonica are different subspecies at an early stage of sub-speciation and could be called further as subspecies of Apis cerana koreana .