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Human rhinoviruses (HRVs), in the Enterovirus genus within the family Picornaviridae, are a highly prevalent cause of acute respiratory infection (ARI). Enteroviruses are genetically highly variable, and recombination between serotypes is known to be a major contribution to their diversity. Recently it was reported that recombination events in HRVs cause the diversity of HRV-C. This study analyzed parts of the viral genes spanning the 5' non- coding region (NCR) through to the viral protein (VP) encoding sequences of 105 HRV field isolates from 51 outpatient cases of Acute Respiratory Infectious Network (ARINET) and 54 inpatient cases of severe lower respiratory infection (SLRI) surveillance, in order to identify recombination in field samples. When analyzing parts of the 5'NCR and VP4/VP2 encoding sequences, we found intra- and interspecies recombinants in field strains of HRV-A and -C. Nineteen cases of recombination events (18.1%) were found among 105 field strains. For HRV-A, there were five cases (4.8%) of intraspecies recombination events and three cases (2.8%) of interspecies recombination events. For HRV-C, there were four cases (3.8%) of intraspecies recombination events and seven cases (6.7%) of interspecies recombination events. Recombination events were significantly more frequently observed in the ARINET samples (18 cases) than in the SLRI samples (1 case; P< 0.0001). The recombination breakpoints were located in nucleotides (nt) 472-554, which comprise stem-loop 5 in the internal ribosomal entry site (IRES), based on the HRV-B 35 sequence (accession no. FJ445187). Our findings regarding genomic recombination in circulating HRV-A and -C strains suggest that recombination might play a role in HRV fitness and could be a possible determinant of disease severity caused by various HRV infections in patients with ARI.

Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

A social robot interacts and communicates with humans by using the embodied knowledge gained from interactions with its social environment. In recent years, emotion has emerged as a popular concept for designing social robots. Several studies on social robots reported an increase in robot sociability through emotional imitative interactions between the robot and humans. In this paper conventional emotional interactions are extended by exploiting the aesthetic theories that the sociability of a social robot can be markedly enhanced through aesthetic imitative interactions such as “playful acts”. We applied these aesthetic interactions to child-robot interaction. Children imitate the emotional behaviours of a robot through aesthetic interactions; they play with the robot by mimicking its emotional facial expressions. From the tests, we see that aesthetic judgment is more influential than emotions in playful interactions between children and the robot; the aesthetic imitative interactions would reinforce the positive social relationships of children and enhance their social adaptability. To the best of our knowledge, this is the first social robot study to investigate child-robot interaction on the basis of aesthetics.

Clonorchis sinensis is the causative agent of the life-threatening disease endemic to China, Korea, and Vietnam. It is estimated that about 15 million people are infected with this fluke. C. sinensis provokes inflammation, epithelial hyperplasia, and periductal fibrosis in bile ducts, and may cause cholangiocarcinoma in chronically infected individuals. Accumulation of a large amount of biological information about the adult stage of this liver fluke in recent years has advanced our understanding of the pathological interplay between this parasite and its hosts. However, no developmental gene expression profiles of C. sinensis have been published. In this study, we generated gene expression profiles of three developmental stages of C. sinensis by analyzing expressed sequence tags (ESTs). Complementary DNA libraries were constructed from the adult, metacercaria, and egg developmental stages of C. sinensis. A total of 52,745 ESTs were generated and assembled into 12,830 C. sinensis assembled EST sequences, and then these assemblies were further categorized into groups according to biological functions and developmental stages. Most of the genes that were differentially expressed in the different stages were consistent with the biological and physical features of the particular developmental stage; high energy metabolism, motility and reproduction genes were differentially expressed in adults, minimal metabolism and final host adaptation genes were differentially expressed in metacercariae, and embryonic genes were differentially expressed in eggs. The higher expression of glucose transporters, proteases, and antioxidant enzymes in the adults accounts for active uptake of nutrients and defense against host immune attacks. The types of ion channels present in C. sinensis are consistent with its parasitic nature and phylogenetic placement in the tree of life. We anticipate that the transcriptomic information on essential regulators of development, bile chemotaxis, and physico-metabolic pathways in C. sinensis that presented in this study will guide further studies to identify novel drug targets and diagnostic antigens.

Obesity represents a major global public health problem that increases the risk for cardiovascular or metabolic disease. The pigs represent an exceptional biomedical model related to energy metabolism and obesity in humans. To pinpoint causal genetic factors for a common form of obesity, we conducted local genomic de novo sequencing, 18.2 Mb, of a porcine QTL region affecting fatness traits, and carried out SNP association studies for backfat thickness and intramuscular fat content in pigs. In order to relate the association studies in pigs to human obesity, we performed a targeted genome wide association study for subcutaneous fat thickness in a cohort population of 8,842 Korean individuals. These combined association studies in human and pig revealed a significant SNP located in a gene family with sequence similarity 73, member A (FAM73A) associated with subscapular skin-fold thickness in humans (rs4121165, GC-corrected p-value = 0.0000175) and with backfat thickness in pigs (ASGA0029495, p-value = 0.000031). Our combined association studies also suggest that eight neuronal genes are responsible for subcutaneous fat thickness: NEGR1, SLC44A5, PDE4B, LPHN2, ELTD1, ST6GALNAC3, ST6GALNAC5, and TTLL7. These results provide strong support for a major involvement of the CNS in the genetic predisposition to a common form of obesity.