Human T‐cell leukemia virus type I (HTLV‐1) infection is endemic in Japan, particularly clustered in the southwestern district, Kyushu‐Okinawa, which consists of eight prefectures that further consist of 274 municipalities. However, no information is available about the fine‐scale distribution of HTLV‐1 infection within Kyushu‐Okinawa. To assess the municipal‐level distribution of people with HTLV‐1 infection in Kyushu‐Okinawa, we performed a cross‐sectional study using a fine‐scale geographic information system map based on HTLV‐1 screening test results from the Japanese Red Cross database from September 2012 to February 2014. Of the 881 871 (646 914 male, 234 957 female) screened blood donors, 981 were seropositive for HTLV‐1 by confirmatory test. The seroprevalence was 0.11% (95% confidence interval [CI] 0.10%‐0.12%) for all, 0.094% (95% CI, 0.09%‐0.10%) for male, and 0.16% (95% CI, 0.14%‐0.18%) for female individuals. The sex‐ and age‐specific HTLV‐1 seroprevalence varied significantly across municipalities; particularly, the seroprevalence among women aged 50 years was significantly higher than that of men in both the mainland of Kyushu‐Okinawa and the satellite island, in all of which the seroprevalence of HTLV‐1 was more than 1.2%. These results show that, even in the Kyushu‐Okinawa district, there are endemic clusters of HTLV‐1 in small areas. This suggests that public health education programs are needed to eliminate new HTLV‐1 infection in these areas.
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The availability of the human genome sequence has enabled the exploration and exploitation of the human genome and proteome to begin. Research has now focussed on the annotation of the genome and in particular of the proteome. With expert annotation extracted from the literature by biologists as the foundation, it has been possible to expand into the areas of data mining and automatic annotation. With further development and integration of pattern recognition methods and the application of alignments clustering proteome analysis can now be provided in a meaningual way. These various approaches have been integrated to attach, extract and combine as much relevant information as possible to the proteome. This resource should be valuable to users from both research and industry.