BackgroundMost diseases are thought to arise from interactions between environmental factors and the host genotype. To detect gene–environment interactions in the development of lifestyle-related diseases, and especially cancer, the Japan Multi-institutional Collaborative Cohort (J-MICC) Study was launched in 2005.MethodsWe initiated a cross-sectional study to examine associations of genotypes with lifestyle and clinical factors, as assessed by questionnaires and medical examinations. The 4519 subjects were selected from among participants in the J-MICC Study in 10 areas throughout Japan. In total, 108 polymorphisms were chosen and genotyped using the Invader assay.ResultsThe study group comprised 2124 men and 2395 women with a mean age of 55.8 ± 8.9 years (range, 35–69 years) at baseline. Among the 108 polymorphisms examined, 4 were not polymorphic in our study population. Among the remaining 104 polymorphisms, most variations were common (minor allele frequency ≥0.05 for 96 polymorphisms). The allele frequencies in this population were comparable with those in the HapMap-JPT data set for 45 Japanese from Tokyo. Only 5 of 88 polymorphisms showed allele-frequency differences greater than 0.1. Of the 108 polymorphisms, 32 showed a highly significant difference in minor allele frequency among the study areas (P < 0.001).ConclusionsThis comprehensive data collection on lifestyle and clinical factors will be useful for elucidating gene–environment interactions. In addition, it is likely to be an informative reference tool, as free access to genotype data for a large Japanese population is not readily available.

BackgroundPandemic influenza A(H1N1) virus infection quickly circulated worldwide in 2009. In Japan, the first case was reported in May 2009, one month after its outbreak in Mexico. Thereafter, A(H1N1) infection spread widely throughout the country. It is of great importance to profile and understand the situation regarding viral mutations and their circulation in Japan to accumulate a knowledge base and to prepare clinical response platforms before a second pandemic (pdm) wave emerges.MethodologyA total of 253 swab samples were collected from patients with influenza-like illness in the Osaka, Tokyo, and Chiba areas both in May 2009 and between October 2009 and January 2010. We analyzed partial sequences of the hemagglutinin (HA) and neuraminidase (NA) genes of the 2009 pdm influenza virus in the collected clinical samples. By phylogenetic analysis, we identified major variants of the 2009 pdm influenza virus and critical mutations associated with severe cases, including drug-resistance mutations.Results and ConclusionsOur sequence analysis has revealed that both HA-S220T and NA-N248D are major non-synonymous mutations that clearly discriminate the 2009 pdm influenza viruses identified in the very early phase (May 2009) from those found in the peak phase (October 2009 to January 2010) in Japan. By phylogenetic analysis, we found 14 micro-clades within the viruses collected during the peak phase. Among them, 12 were new micro-clades, while two were previously reported. Oseltamivir resistance-related mutations, i.e., NA-H275Y and NA-N295S, were also detected in sporadic cases in Osaka and Tokyo.

Robot therapy is expected to have psychological, physiological and social effects similar to animal therapy. The use of a therapeutic seal robot, Paro, in various facilities for the elderly is spreading around the world. However, caregivers use Paro freely, and the ways in which they use Paro differ among them. Therefore, the effects are influenced by their skills. A manual that shows effective ways to use Paro is needed. In this paper, such a manual that shows effective methods for robot therapy is developed and its effectiveness is evaluated in a preliminary study with one caregiver and two patients. 19th IEEE International Symposium on Robot and Human Interactive Communication Principe di Piemonte -Viareggio, Italy, Sept. 12-15, 2010 978-1-4244-7989-4/10/$26.00 ©2010 IEEE 533 978-1-4244-7990-0/10/$26.00 ©2010 IEEE

The data suggest that between 70% and 80% of the variation in failure load of human femora with lytic metastatic defects can be predicted from the BMC and that relations between BMC and failure load are sensitive to the type of loading. Combined with information on the loads associated with the activities of daily living, these data may be used to help identify patients in whom prophylactic stabilization might prevent a pathologic fracture.