著者

Kenichi Komabayashi Junji Seto Shizuka Tanaka Yu Suzuki Tatsuya Ikeda Noriko Onuki Keiko Yamada Tadayuki Ahiko Hitoshi Ishikawa Katsumi Mizuta

出版者

National Institute of Infectious Diseases

雑誌

Japanese Journal of Infectious Diseases (ISSN:13446304)

巻号頁・発行日

vol.71, no.6, pp.413-418, 2018-11-30 (Released:2018-11-22)

参考文献数

26

被引用文献数

28 35

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The incidence of modified measles (M-Me), characterized by milder symptoms than those of typical measles (T-Me), has been increasing in Japan. However, the outbreak dominated by M-Me cases has not been thoroughly investigated worldwide. The largest importation-related outbreak of measles with genotype D8 occurred in Yamagata Prefecture, Japan, from March to April 2017. This phenomenon was observed after Japan had achieved measles elimination in 2015. We confirmed 60 cases by detecting the genome of the measles virus (MeV). Among the cases, 38 were M-Me and 22 were T-Me. Thirty-nine (65.0%) patients were 20–39 years of age. Three out of 7 primary cases produced 50 transmissions, of which each patient caused 9–25 transmissions. These patients were 22–31 years old and were not vaccinated. Moreover, they developed T-Me and kept contact with the public during their symptomatic periods. Considering that M-Me is generally caused by vaccine failure, some individuals in Japan may have insufficient immunity for MeV. Accordingly, additional doses of measles vaccine may be necessary in preventing measles importation and endemicity among individuals aged 20–39 years. Furthermore, to accurately and promptly diagnose individuals with measles, particularly those who can be considered as primary cases, efforts must be exerted to detect all measles cases using epidemiological and genetic approaches in countries where measles elimination had been achieved.

著者

Yu Suzuki

出版者

一般社団法人 情報処理学会

雑誌

Journal of Information Processing (ISSN:18826652)

巻号頁・発行日

vol.23, no.1, pp.22-30, 2015 (Released:2015-01-15)

参考文献数

30

被引用文献数

1 18

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In this paper, we propose a method for assessing quality values of Wikipedia articles from edit history using h-index. One of the major methods for assessing Wikipedia article quality is a peer-review based method. In this method, we assume that if an editor's texts are left by the other editors, the texts are approved by the editors, then the editor is decided as a good editor. However, if an editor edits multiple articles, and the editor is approved at a small number of articles, the quality value of the editor deeply depends on the quality of the texts. In this paper, we apply h-index, which is a simple but resistant to excessive values, to the peer-review based Wikipedia article assessment method. Although h-index can identify whether an editor is a good quality editor or not, h-index cannot identify whether the editor is a vandal or an inactive editor. To solve this problem, we propose p-ratio for identifying which editors are vandals or inactive editors. From our experiments, we confirmed that by integrating h-index with p-ratio, the accuracy of article quality assessment in our method outperforms the existing peer-review based method.

著者

Hiroaki Tanaka Yu Suzuki Shotaro Yamasaki Koichiro Yoshino Ko Kato Satoshi Nakamura

出版者

Information Processing Society of Japan

雑誌

IPSJ Transactions on Bioinformatics (ISSN:18826679)

巻号頁・発行日

vol.11, pp.14-23, 2018 (Released:2018-07-05)

参考文献数

43

被引用文献数

1

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Protein production in plants is a hot topic because there are many benefits relative to bacteria, yeasts, and animals, but the amount of protein expression in plants is less. It is argued that editing 5'UTRs increases the amount of translated proteins. However, obtaining such 5'UTRs is difficult due to the cost, time and effort required in experiments. To solve this, we predict the amount of translated proteins by machine learning. In this paper, we propose a method, named “R-STEINER, ” that generates 5'UTRs that increase the amount of proteins of a given gene. The proposed process involves building a model for predicting the amount of translated proteins, generating 5'UTRs, selecting them and increasing the proteins according to the model. This method enables us to obtain 5'UTRs that increase the amount of translated proteins without real synthesis experiments, resulting in reduced cost, time and effort. In our study, we built a prediction model for Oryza sativa and synthesized the 5'UTRs generated by R-STEINER. We confirmed that the model can predict the amount of translated proteins with a correlation coefficient of 0.89.

著者

Yohei Matoba Chieko Abiko Tatsuya Ikeda Yoko Aoki Yu Suzuki Kazue Yahagi Yoko Matsuzaki Tsutomu Itagaki Fumio Katsushima Yuriko Katsushima Katsumi Mizuta

出版者

National Institute of Infectious Diseases, Japanese Journal of Infectious Diseases Editorial Committee

雑誌

Japanese Journal of Infectious Diseases (ISSN:13446304)

巻号頁・発行日

vol.68, no.2, pp.138-141, 2015 (Released:2015-03-23)

参考文献数

24

被引用文献数

40 74

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The available literature on human coronaviruses (HCoVs) in Japan is limited to epidemiological studies conducted over a maximum of 1 year. We conducted a 4-year study of HCoVs by analyzing 4,342 respiratory specimens obtained in Yamagata, Japan, between January 2010 and December 2013. A pan-coronavirus reverse transcription-PCR screening assay was performed, and all HCoV-positive specimens were subsequently confirmed by sequencing of the PCR products. We detected in 332 (7.6%) HCoV strains during the study period, comprising 133 (3.1%) HCoV-NL63, 83 (1.9%) HCoV-HKU1, 78 (1.8%) HCoV-OC43, and 38 (0.9%) HCoV-229E strains. HCoV detection per year ranged from 3.5% to 9.7%. HCoVs were detected mainly in winter, with January (28.5%) and February (25.3%) 2011 and December 2012 (14.6%) being the only months in which HCoV-NL63 detection per month exceeded 10.0%. HCoV-HKU1 displayed clear biennial peaks in January (18.3%) and February (10.7%) 2010 and in February (18.8%) and March (14.7%) 2012. The peak detection of HCoV-OC43 was 13.6% in November 2010, while that of HCoV-229E was 10.8% in March 2013. Our results indicated that there may be annual variations in the circulation of individual HCoV strains. Further long-term surveillance is necessary to clarify HCoV prevalence and circulation patterns in Japan.

著者

Ikuo KESHI Yu SUZUKI Koichiro YOSHINO Satoshi NAKAMURA

出版者

The Institute of Electronics, Information and Communication Engineers

雑誌

IEICE Transactions on Information and Systems (ISSN:09168532)

巻号頁・発行日

vol.E101.D, no.4, pp.1066-1078, 2018-04-01 (Released:2018-04-01)

参考文献数

24

被引用文献数

1

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The problem with distributed representations generated by neural networks is that the meaning of the features is difficult to understand. We propose a new method that gives a specific meaning to each node of a hidden layer by introducing a manually created word semantic vector dictionary into the initial weights and by using paragraph vector models. We conducted experiments to test the hypotheses using a single domain benchmark for Japanese Twitter sentiment analysis and then evaluated the expandability of the method using a diverse and large-scale benchmark. Moreover, we tested the domain-independence of the method using a Wikipedia corpus. Our experimental results demonstrated that the learned vector is better than the performance of the existing paragraph vector in the evaluation of the Twitter sentiment analysis task using the single domain benchmark. Also, we determined the readability of document embeddings, which means distributed representations of documents, in a user test. The definition of readability in this paper is that people can understand the meaning of large weighted features of distributed representations. A total of 52.4% of the top five weighted hidden nodes were related to tweets where one of the paragraph vector models learned the document embeddings. For the expandability evaluation of the method, we improved the dictionary based on the results of the hypothesis test and examined the relationship of the readability of learned word vectors and the task accuracy of Twitter sentiment analysis using the diverse and large-scale benchmark. We also conducted a word similarity task using the Wikipedia corpus to test the domain-independence of the method. We found the expandability results of the method are better than or comparable to the performance of the paragraph vector. Also, the objective and subjective evaluation support each hidden node maintaining a specific meaning. Thus, the proposed method succeeded in improving readability.