Language：English   Publishing type：Research paper (scientific journal)  

Recently, research has been conducted to automatically control anesthesia using machine learning, with the aim of alleviating the shortage of anesthesiologists. In this study, we address the problem of predicting decisions made by anesthesiologists during surgery using machine learning; specifically, we formulate a decision making problem by increasing the flow rate at each time point in the continuous administration of analgesic remifentanil as a supervised binary classification problem. The experiments were conducted to evaluate the prediction performance using six machine learning models: logistic regression, support vector machine, random forest, LightGBM, artificial neural network, and long short-term memory (LSTM), using 210 case data collected during actual surgeries. The results demonstrated that when predicting the future increase in flow rate of remifentanil after 1 min, the model using LSTM was able to predict with scores of 0.659 for sensitivity, 0.732 for specificity, and 0.753 for ROC-AUC; this demonstrates the potential to predict the decisions made by anesthesiologists using machine learning. Furthermore, we examined the importance and contribution of the features of each model using Shapley additive explanations-a method for interpreting predictions made by machine learning models. The trends indicated by the results were partially consistent with known clinical findings.

DOI： 10.1038/s41598-021-03112-2

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Elsevier BV  

DOI： 10.1016/j.xgen.2021.100028

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Authorship：Last author,　Corresponding author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Korean Society of Medical Informatics  

DOI： 10.4258/hir.2021.27.3.231

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Other Link： https://www.webofscience.com/wos/woscc/full-record/WOS:000684600200008

Authorship：Lead author,　Last author,　Corresponding author   Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)  

When a global pandemic of infectious diseases occurs, demand for medical supplies such as masks, disinfectants, and personal protective equipment will exceed the production capacity in normal times, consequently leading to serious shortages. Stockpiling is necessary to prepare for such situations. However, because pandemics are infrequent and might occur at any time, stockpile freshness is an important concern. As described in this paper, a “rolling stockpile” of medical supplies is proposed to prevent the medical supply stockpile from becoming too old. A formulation of a model and simulations based on it is presented. Results demonstrate that the method is applicable to the design of warehouses for rolling stockpiles, monitoring stockpile depletion during emergencies, and monitoring the process of recovery from emergencies.

DOI： 10.18926/interdisciplinary/61886

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Authorship：Last author,　Corresponding author   Language：Japanese   Publishing type：Research paper (bulletin of university, research institution)  

DOI： 10.18926/interdisciplinary/61889

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Language：English   Publishing type：Research paper (scientific journal)  

BACKGROUND: Recently, more electronic data sources are becoming available in the healthcare domain. Electronic health records (EHRs), with their vast amounts of potentially available data, can greatly improve healthcare. Although EHR de-identification is necessary to protect personal information, automatic de-identification of Japanese language EHRs has not been studied sufficiently. This study was conducted to raise de-identification performance for Japanese EHRs through classic machine learning, deep learning, and rule-based methods, depending on the dataset. RESULTS: Using three datasets, we implemented de-identification systems for Japanese EHRs and compared the de-identification performances found for rule-based, Conditional Random Fields (CRF), and Long-Short Term Memory (LSTM)-based methods. Gold standard tags for de-identification are annotated manually for age, hospital, person, sex, and time. We used different combinations of our datasets to train and evaluate our three methods. Our best F1-scores were 84.23, 68.19, and 81.67 points, respectively, for evaluations of the MedNLP dataset, a dummy EHR dataset that was virtually written by a medical doctor, and a Pathology Report dataset. Our LSTM-based method was the best performing, except for the MedNLP dataset. The rule-based method was best for the MedNLP dataset. The LSTM-based method achieved a good score of 83.07 points for this MedNLP dataset, which differs by 1.16 points from the best score obtained using the rule-based method. Results suggest that LSTM adapted well to different characteristics of our datasets. Our LSTM-based method performed better than our CRF-based method, yielding a 7.41 point F1-score, when applied to our Pathology Report dataset. This report is the first of study applying this LSTM-based method to any de-identification task of a Japanese EHR. CONCLUSIONS: Our LSTM-based machine learning method was able to extract named entities to be de-identified with better performance, in general, than that of our rule-based methods. However, machine learning methods are inadequate for processing expressions with low occurrence. Our future work will specifically examine the combination of LSTM and rule-based methods to achieve better performance. Our currently achieved level of performance is sufficiently higher than that of publicly available Japanese de-identification tools. Therefore, our system will be applied to actual de-identification tasks in hospitals.

DOI： 10.1186/s13326-020-00227-9

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Hindawi  

Poor quality of biological samples will result in an inaccurate analysis of next-generation sequencing (NGS). Therefore, methods to accurately evaluate sample integrity are needed. Among methods for evaluating RNA quality, the RNA integrity number equivalent (RINe) is widely used, whereas the DV200, which evaluates the percentage of fragments of >200 nucleotides, is also used as a quality assessment standard. In this study, we compared the RINe and DV200 RNA quality indexes to determine the most suitable RNA index for the NGS analysis. Seventy-one RNA samples were extracted from formalin-fixed paraffin-embedded tissue samples (n = 30), fresh-frozen samples (n = 25), or cell lines (n = 16). After assessing RNA quality using the RINe and DV200, we prepared two kinds of stranded mRNA sequencing libraries. Finally, we calculated the correlation between each RNA quality index and the amount of library product (1st PCR product per input RNA). The DV200 measure showed stronger correlation with the amount of library product than the RINe (R 2 = 0.8208 for the DV200 versus 0.6927 for the RINe). Receiver operating characteristic curve analyses revealed that the DV200 was the better marker for predicting efficient library production than the RINe using a threshold of >10 ng/ng for the amount of the 1st PCR product per input RNA (cutoff value for the RINe and DV200, 2.3 and 66.1%; area under the curve, 0.99 and 0.91; sensitivity, 82% and 92%; and specificity, 93% and 100%, respectively). Our results indicate that NGS libraries prepared using RNA samples with the DV200 value > 66.1% exhibit greater sensitivity and specificity than those prepared with the RINe values > 2.3. These findings suggest that the DV200 is superior to the RINe, especially for low-quality RNA, because it is a more consistent assessment of the amount of the 1st NGS library product per input.

DOI： 10.1155/2020/9349132

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The survival rate of cardiac arrest patients is less than 10%; therefore, development of a therapeutic strategy that improves their prognosis is necessary. Herein, we searched data collected from medical facilities throughout Japan for drugs that improve the survival rate of cardiac arrest patients. Candidate drugs, which could improve the prognosis of cardiac arrest patients, were extracted using "TargetMine," a drug discovery tool. We investigated whether the candidate drugs were among the drugs administered within 1 month after cardiac arrest in data of cardiac arrest cases obtained from the Japan Medical Data Center. Logistic regression analysis was performed, with the explanatory variables being the presence or absence of the administration of those candidate drugs that were administered to ≥10 patients and the objective variable being the "survival discharge." Adjusted odds ratios for survival discharge were calculated using propensity scores for drugs that significantly improved the proportion of survival discharge; the influence of covariates, such as patient background, medical history, and treatment factors, was excluded by the inverse probability-of-treatment weighted method. Using the search strategy, we extracted 165 drugs with vasodilator activity as candidate drugs. Drugs not approved in Japan, oral medicines, and external medicines were excluded. Then, we investigated whether the candidate drugs were administered to the 2,227 cardiac arrest patients included in this study. The results of the logistic regression analysis showed that three (isosorbide dinitrate, nitroglycerin, and nicardipine) of seven drugs that were administered to ≥10 patients showed significant association with improvement in the proportion of survival discharge. Further analyses using propensity scores revealed that the adjusted odds ratios for survival discharge for patients administered isosorbide dinitrate, nitroglycerin, and nicardipine were 3.35, 5.44, and 4.58, respectively. Thus, it can be suggested that isosorbide dinitrate, nitroglycerin, and nicardipine could be novel therapeutic agents for improving the prognosis of cardiac arrest patients.

DOI： 10.3389/fphar.2019.01257

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1101/19004770

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Language：English   Publishing type：Research paper (scientific journal)  

The majority of marathon deaths are caused by sudden cardiac arrest (SCA), which occur in approximately 1 in 57,000 runners. Such deaths are more common among older males and usually occur in the last 4 miles of the racecourse. Although prompt resuscitation, including early use of an automated external defibrillator (AED), improves survival, the deployment of enough trained medical staff and AEDs is difficult due to increased cost. Moreover, most victims of exercise-related SCA have no premonitory symptoms. Therefore, we tried to use a novel approach to prevent sudden cardiac deaths (SCD) related to SCA using real-time electrocardiographic tele-monitoring system, as an initial trial to assess operative possibility in a full marathon. As a result, 3 out of 5 runners had reasonable measurement results and sufficient tele-monitoring without complications related to this trial was possible. However, many investigations and improvements, such as improving cost-effectiveness, reducing noise, and automating the monitoring system, are needed for practical application of these devices for athletes. As a next step, we would establish a novel strategy to reduce SCDs in athletes using next-generation devices, which include an alarm system associated with early application of AED. <Learning objectives: Sudden cardiac arrest (SCA) is a major problem in sports cardiology. Here we investigated a novel approach using a real-time tele-monitoring system of electrocardiogram (ECG) to prevent sudden cardiac deaths by making use of an advanced alarm system which responds to SCA risk. Three out of five cases we monitored showed reasonable measurement of ECG with centralized observation in full marathon. This is the first report of this method, which may lead to the effective application of automated external defibrillator in athletes.>.

DOI： 10.1016/j.jccase.2019.03.008

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BACKGROUND: The amount of medical and clinical-related information on the Web is increasing. Among the different types of information available, social media-based data obtained directly from people are particularly valuable and are attracting significant attention. To encourage medical natural language processing (NLP) research exploiting social media data, the 13th NII Testbeds and Community for Information access Research (NTCIR-13) Medical natural language processing for Web document (MedWeb) provides pseudo-Twitter messages in a cross-language and multi-label corpus, covering 3 languages (Japanese, English, and Chinese) and annotated with 8 symptom labels (such as cold, fever, and flu). Then, participants classify each tweet into 1 of the 2 categories: those containing a patient's symptom and those that do not. OBJECTIVE: This study aimed to present the results of groups participating in a Japanese subtask, English subtask, and Chinese subtask along with discussions, to clarify the issues that need to be resolved in the field of medical NLP. METHODS: In summary, 8 groups (19 systems) participated in the Japanese subtask, 4 groups (12 systems) participated in the English subtask, and 2 groups (6 systems) participated in the Chinese subtask. In total, 2 baseline systems were constructed for each subtask. The performance of the participant and baseline systems was assessed using the exact match accuracy, F-measure based on precision and recall, and Hamming loss. RESULTS: The best system achieved exactly 0.880 match accuracy, 0.920 F-measure, and 0.019 Hamming loss. The averages of match accuracy, F-measure, and Hamming loss for the Japanese subtask were 0.720, 0.820, and 0.051; those for the English subtask were 0.770, 0.850, and 0.037; and those for the Chinese subtask were 0.810, 0.880, and 0.032, respectively. CONCLUSIONS: This paper presented and discussed the performance of systems participating in the NTCIR-13 MedWeb task. As the MedWeb task settings can be formalized as the factualization of text, the achievement of this task could be directly applied to practical clinical applications.

DOI： 10.2196/12783

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.24105/ejbi.2018.14.1.9

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：JAPAN SOC INTERNAL MEDICINE  

Objective This study attempted to clarify the current status of female dystrophinopathy carriers, including the numbers of patients, the status of genetic screening, the status of counseling. physicians' understanding. and barriers to registration.Methods We sent out questionnaires to 402 physicians registered in the Remudy dystrophinopathy registry. The total number of responses received was 130 (response rate: 32%).Result In total, 1,212 cases of Duchenne muscular dystrophy, 365 cases of Becker muscular dystrophy, and 132 cases of female dystrophinopathy with a confirmed genetic mutation were encountered, and genetic testing was performed in the mother in 137, 23, and 12 cases, respectively. With respect to the risk of the onset of health problems, 25% of physicians always explained, 29% usually explained, 29% sometimes explained, and 13% never explained the risk to the mothers and female siblings of dystrophinopathy patients. The most common reason for not explaining the risk was a lack of knowledge/information. Thirty-five percent were familiar with the guidelines for testing the heart function of carriers.Conclusion Fewer mothers of dystrophinopathy patients have undergone genetic testing in Japan than in other countries. A significant portion of doctors did not explain the risks of health problems due to a lack of knowledge. We hope this survey will lead to an increased discussion of female dystrophinopathy patients.

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DOI： 10.2169/internalmedicine.0163-17

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：MARY ANN LIEBERT, INC  

File： 17BIO484%組織検体の処理までの時間とRNAの安定性に関する研究（岡大バイオバンク）.pdf

DOI： 10.1089/bio.2017.0076

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Language：English   Publishing type：Research paper (international conference proceedings)  

File： W16-4203.pdf

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Publisher：National Institute of Informatics (NII)  

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Other Link： http://dblp.uni-trier.de/db/conf/ntcir/ntcir2016.html#conf/ntcir/AramakiMKO16

Language：English   Publishing type：Research paper (scientific journal)   Publisher：WILEY  

Human epidermal growth factor receptor 2 (HER2) is a member of the HER family of proteins containing four receptor tyrosine kinases. It plays an important role in the pathogenesis of certain human cancers. In non-small-cell lung cancer (NSCLC), HER2 amplification or mutations have been reported. However, little is known about the benefit of HER2-targeted therapy for NSCLCs harboring HER2 alterations. In this study, we investigated the antitumor effect of afatinib, an irreversible epidermal growth factor receptor (EGFR)-HER2 dual inhibitor, in lung cancers harboring HER2 oncogene alterations, including novel HER2 mutations in the transmembrane domain, which we recently identified. Normal bronchial epithelial cells, BEAS-2B, ectopically overexpressing wild-type HER2 or mutants (A775insYVMA, G776VC, G776LC, P780insGSP, V659E, and G660D) showed constitutive autophosphorylation of HER2 and activation of downstream signaling. They were sensitive to afatinib, but insensitive to gefitinib. Furthermore, we examined the antitumor activity of afatinib and gefitinib in several NSCLC cell lines, and investigated the association between their genetic alterations and sensitivity to afatinib treatment. In HER2-altered NSCLC cells (H2170, Calu-3, and H1781), afatinib downregulated the phosphorylation of HER2 and EGFR as well as their downstream signaling, and induced an antiproliferative effect through G(1) arrest and apoptotic cell death. In contrast, HER2- or EGFR-non-dependent NSCLC cells were insensitive to afatinib. In addition, these effects were confirmed in vivo by using a xenograft mouse model of HER2-altered lung cancer cells. Our results suggest that afatinib is a therapeutic option as a HER2-targeted therapy for NSCLC harboring HER2 amplification or mutations.

DOI： 10.1111/cas.12845

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Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.11188/seisankenkyu.67.281

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：BMC  

Background: Linked Data has gained some attention recently in the life sciences as an effective way to provide and share data. As a part of the Semantic Web, data are linked so that a person or machine can explore the web of data. Resource Description Framework (RDF) is the standard means of implementing Linked Data. In the process of generating RDF data, not only are data simply linked to one another, the links themselves are characterized by ontologies, thereby allowing the types of links to be distinguished. Although there is a high labor cost to define an ontology for data providers, the merit lies in the higher level of interoperability with data analysis and visualization software. This increase in interoperability facilitates the multi-faceted retrieval of data, and the appropriate data can be quickly extracted and visualized. Such retrieval is usually performed using the SPARQL (SPARQL Protocol and RDF Query Language) query language, which is used to query RDF data stores. For the database provider, such interoperability will surely lead to an increase in the number of users.Results: This manuscript describes the experiences and discussions shared among participants of the week-long BioHackathon 2011 who went through the development of RDF representations of their own data and developed specific RDF and SPARQL use cases. Advice regarding considerations to take when developing RDF representations of their data are provided for bioinformaticians considering making data available and interoperable.Conclusions: Participants of the BioHackathon 2011 were able to produce RDF representations of their data and gain a better understanding of the requirements for producing such data in a period of just five days. We summarize the work accomplished with the hope that it will be useful for researchers involved in developing laboratory databases or data analysis, and those who are considering such technologies as RDF and Linked Data.

DOI： 10.1186/2041-1480-6-3

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：Japan Association for Medical Informatics  

DOI： 10.14948/jami.34.197

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Language：Japanese   Publisher：科学技術振興機構  

Medical and health information, including genetic information, can produce important benefits for both individuals and the public, but this extremely sensitive resource demands special care. Therefore, it is strictly controlled in hospitals and research institutes. Nevertheless, the environment around medical and health information has been changing drastically recently, with the introduction of new ideas. Those changes are expanding the area of personal information under control of patients and the public and are strengthening patient and public involvement in medical research. This paper presents perspectives on recent patient-centered medical and health information management, emphasizing dynamic consent (dynamic informed consent) and recent environmental changes.

DOI： 10.1241/johokanri.57.3

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Language：English   Publishing type：Research paper (scientific journal)  

DOI： 10.1186/2041-1480-5-5

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Publishing type：Research paper (international conference proceedings)   Publisher：AAAI Press  

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Other Link： https://dblp.uni-trier.de/conf/aaaiss/2014

Language：English   Publishing type：Research paper (international conference proceedings)  

Detecting the incidence and prevalence of infectious diseases is important because these diseases affect many people, raise the cost of healthcare, and, in some cases, can lead to a great many deaths. Recently, it has been shown that people&#039;s online activity can be applied to detecting the prevalence of influenza. In this study, we compare the characteristics of two kinds of online activities, social media and search activity, as the social sensors capable of supplying information on seasonal epidemics and an unexpected pandemic of influenza. Although both approaches showed quite high performance for the seasonal epidemics, they showed poor performance for the unexpected influenza pandemic. The social media-based approach particularly over-responded to the influenza pandemic.

File： Twitflu-LBM.pdf

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：社団法人人工知能学会  

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Language：English   Publishing type：Research paper (international conference proceedings)  

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：OXFORD UNIV PRESS  

Motivation: In early stage drug development, it is desirable to assess the toxicity of compounds as quickly as possible. Biomarker genes can help predict whether a candidate drug will adversely affect a given individual, but they are often difficult to discover. In addition, the mechanism of toxicity of many drugs and common compounds is not yet well understood. The Japanese Toxicogenomics Project provides a large database of systematically collected microarray samples from rats (liver, kidney and primary hepatocytes) and human cells (primary hepatocytes) after exposure to 170 different compounds in different dosages and at different time intervals. However, until now, no intuitive user interface has been publically available, making it time consuming and difficult for individual researchers to explore the data.
Results: We present Toxygates, a user-friendly integrated analysis platform for this database. Toxygates combines a large microarray dataset with the ability to fetch semantic linked data, such as pathways, compound-protein interactions and orthologs, on demand. It can also perform pattern-based compound ranking with respect to the expression values of a set of relevant candidate genes. By using Toxygates, users can freely interrogate the transcriptome's response to particular compounds and conditions, which enables deep exploration of toxicity mechanisms.

DOI： 10.1093/bioinformatics/btt531

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Language：Japanese   Publishing type：Research paper (scientific journal)   Publisher：一般社団法人情報処理学会  

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Rare diseases, those affecting few patients, are in fact neglected diseases that demand special concern and care. We are constructing an online system to collect health-related data and complaints from rare-disease patients to share that information with stakeholders, thereby facilitating the development of new or improved drugs, treatments, and policies and enhancing the quality of life (QOL) for patients with such diseases. The system will also track and monitor the physical states and conditions of patients, which will facilitate the management of their QOL and improve communication with health professionals. Copyright © 2013 Association for the Advancement of Artificial Intelligence.

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Publisher：National Institute of Informatics (NII)  

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Other Link： http://dblp.uni-trier.de/db/conf/ntcir/ntcir2013.html#conf/ntcir/MoritaKOMA13

Language：Japanese   Publishing type：Research paper (scientific journal)  

DOI： 10.5715/jnlp.19.419

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DOI： 10.7243/2050-2273-1-1

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Background: In the big data era, biomedical research continues to generate a large amount of data, and the generated information is often stored in a database and made publicly available. Although combining data from multiple databases should accelerate further studies, the current number of life sciences databases is too large to grasp features and contents of each database. Findings. We have developed Sagace, a web-based search engine that enables users to retrieve information from a range of biological databases (such as gene expression profiles and proteomics data) and biological resource banks (such as mouse models of disease and cell lines). With Sagace, users can search more than 300 databases in Japan. Sagace offers features tailored to biomedical research, including manually tuned ranking, a faceted navigation to refine search results, and rich snippets constructed with retrieved metadata for each database entry. Conclusions: Sagace will be valuable for experts who are involved in biomedical research and drug development in both academia and industry. Sagace is freely available at. © 2012 Morita et al.
licensee BioMed Central Ltd.

DOI： 10.1186/1756-0500-5-604

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Although web-based information extraction systems draw much attention, most of such systems assume that the web directly reflects the real world. For instance, Google flu trend, which is one of the-state-of-the-art influenza surveillance systems, relies on the basic idea that the amount of the influenza related search queries directly correlates with the number of the influenza patients. However, the real patients suffering from influenza symptoms are invisible in the web, because they do not use Internet. Considering this gap, this paper employs an infectious model, assuming that a potential patient utilizes Internet at the first sign of flu. The proposed model improves two types of the state-of-the-art systems, Google based system (from 0.837 correlation to 0.928) and Twitter based system (from 0.898 correlation to 0.918). This study demonstrated that a simple model could easily improve the web-based surveillance. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

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Background: Protein-lipid interactions play essential roles in the conformational stability and biological functions of membrane proteins. However, few of the previous computational studies have taken into account the atomic details of protein-lipid interactions explicitly.Results: To gain an insight into the molecular mechanisms of the recognition of lipid molecules by membrane proteins, we investigated amino acid propensities in membrane proteins for interacting with the head and tail groups of lipid molecules. We observed a common pattern of lipid tail-amino acid interactions in two different data sources, crystal structures and molecular dynamics simulations. These interactions are largely explained by general lipophilicity, whereas the preferences for lipid head groups vary among individual proteins. We also found that membrane and water-soluble proteins utilize essentially an identical set of amino acids for interacting with lipid head and tail groups.Conclusions: We showed that the lipophilicity of amino acid residues determines the amino acid preferences for lipid tail groups in both membrane and water-soluble proteins, suggesting that tightly-bound lipid molecules and lipids in the annular shell interact with membrane proteins in a similar manner. In contrast, interactions between lipid head groups and amino acids showed a more variable pattern, apparently constrained by each protein's specific molecular function. © 2011 Morita et al
licensee BioMed Central Ltd.

DOI： 10.1186/2046-1682-4-21

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Language：English   Publishing type：Research paper (international conference proceedings)  

With the recent rise in popularity and scale of social media, a growing need exists for systems that can extract useful information from huge amounts of data. We address the issue of detecting influenza epidemics. First, the proposed system extracts influenza related tweets using Twitter API. Then, only tweets that mention actual influenza patients are extracted by the support vector machine (SVM) based classifier. The experiment results demonstrate the feasibility of the proposed approach (0.89 correlation to the gold standard). Especially at the outbreak and early spread (early epidemic stage), the proposed method shows high correlation (0.97 correlation), which outperforms the state-of-the-art methods. This paper describes that Twitter texts reflect the real world, and that NLP techniques can be applied to extract only tweets that contain useful information. © 2011 Association for Computational Linguistics.

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Background: Elucidating molecular recognition by proteins, such as in enzyme-substrate and receptor-ligand interactions, is a key to understanding biological phenomena. To delineate these protein interactions, it is important to perform structural bioinformatics studies relevant to molecular recognition. Such studies require a dataset of protein structure pairs between ligand-bound and unbound states. In many studies, the same well-designed and high-quality dataset has been used repeatedly, which has spurred the development of subsequent relevant research. Using previously constructed datasets, researchers are able to fairly compare obtained results with those of other studies
in addition, much effort and time is saved. Therefore, it is important to construct a refined dataset that will appeal to many researchers. However, constructing such datasets is not a trivial task. Findings. We have developed the BUDDY-system, a web site designed to support the building of a dataset comprising pairs of protein structures between ligand-bound and unbound states, which are widely used in various areas associated with molecular recognition. In addition to constructing a dataset, the BUDDY-system also allows the user to search for ligand-bound protein structures by its unbound state or by its ligand
and to search for ligands by a particular receptor protein. Conclusions: The BUDDY-system receives input from the user as a single entry or a dataset consisting of a list of ligand-bound state protein structures, unbound state protein structures, or ligands and returns to the user a list of protein structure pairs between the ligand-bound and the corresponding unbound states. This web site is designed for researchers who are involved not only in structural bioinformatics but also in experimental studies. The BUDDY-system is freely available on the web. © 2011 Morita et al
licensee BioMed Central Ltd.

DOI： 10.1186/1756-0500-4-143

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Carbohydrate-binding proteins are proteins that can interact with sugar chains but do not modify them. They are involved in many physiological functions, and we have developed a method for predicting them from their amino acid sequences. Our method is based on support vector machines (SVMs). We first clarified the definition of carbohydrate-binding proteins and then constructed positive and negative datasets with which the SVMs were trained. By applying the leave-one-out test to these datasets, our method delivered 0.92 of the area under the receiver operating characteristic (ROC) curve. We also examined two amino acid grouping methods that enable effective learning of sequence patterns and evaluated the performance of these methods. When we applied our method in combination with the homology-based prediction method to the annotated human genome database, H-invDB, we found that the true positive rate of prediction was improved. © 2010 Seizi Someya et al.

DOI： 10.1155/2010/289301

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：Nature Publishing Group  

Allelic mutations of the lysosomal beta-galactosidase gene cause heterogeneous clinical phenotypes, such as GM1 gangliosidosis and Morquio B disease, the former being further classified into three variants, namely infantile, juvenile and adult forms; and heterogeneous biochemical phenotypes were shown in these forms. We tried to elucidate the bases of these diseases from a structural viewpoint. We first constructed a three-dimensional structural model of human beta-galactosidase by means of homology modeling. The human beta-galactosidase consists of three domains, such as, a TIM barrel fold domain, which functions as a catalytic domain, and two galactose-binding domain-like fold domains. We then constructed structural models of representative mutant beta-galactosidase proteins (G123R, R201C, I51T and Y83H) and predicted the structural change associated with each phenotype by calculating the number of affected atoms, determining the root-mean-square deviation and the solvent-accessible surface area, and by color imaging. The results show that there is a good correlation between the structural changes caused by amino-acid substitutions in the beta-galactosidase molecule, as well as biochemical and clinical phenotypes in these representative cases. Protein structural study is useful for elucidating the bases of these diseases. Journal Human Genetics (2009) 54, 510-515; doi:10.1038/jhg.2009.70; published online 31 July 2009

DOI： 10.1038/jhg.2009.70

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：6  

During the immobilization process of proteins onto an Au-surface of a 27 MHz quartz crystal microbalance (QCM) in aqueous solutions, apparent large frequency changes (ΔFwater) were observed compared with those in the air phase (ΔFair) due to the interaction with surrounding water of proteins. On the basis of an energy-transfer model for the QCM, the apparent added mass in the aqueous solution [(-ΔF water)/(-ΔFair) - 1] could be explained by frictional forces at the interface of proteins with aqueous solutions. When [(-ΔFwater)/(-ΔFair) -1] values for various proteins were plotted against values relating to the friction (antimobility), such as values of the molecular weight divided by the sedimentation coefficient (Mw/s), the inverse of the diffusion coefficient (1/D), and the volume divided by the surface area (volume/surface area) apparent radius) of proteins, there were good linear correlations. Thus, observations of the larger ΔF water than ΔFair for protein immobilizations on the QCM can be simply explained by the friction effect at the interface between proteins and the aqueous solution. Thus, QCM would be a mass sensor based on mechanical oscillation motion even in aqueous solutions.

DOI： 10.1021/ac802412t

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Authorship：Lead author   Language：English   Publishing type：Research paper (scientific journal)   Publisher：Wiley-Liss  

This article describes a new method for predicting ligand-binding sites of proteins. The method involves calculating the van der Waals interaction energy between a protein and probes placed on the protein surface, and then clustering the probes with attractive interaction to find the energetically most favorable locus. In 80% (28/35) of the test cases, the ligand-binding site was successfully predicted on a ligand-bound protein structure, and in 77% (27/35) was successfully predicted on an unbound structure. Our method was used to successfully predict ligand-binding sites unaffected by induced-fit as long as its scales were not very large, and it contributed to a significant improvement in prediction with unbound state protein structures. This represents a significant advance over conventional methods in detecting ligand-binding sites on uncharacterized proteins. Moreover, our method can predict ligand-binding sites with a narrower locus than those achieved using conventional methods.

DOI： 10.1002/prot.22067

Web of Science

PubMed

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Language：English   Publishing type：Research paper (scientific journal)   Publisher：American Chemical Society  

By using a 27-MHz piezoelectric quartz oscillator connected with a vector network analyzer, we obtained resonance frequency decreases (-Delta F-water) and energy dissipation increases (Delta D-water) during binding of biotinylated bovine serum albumin, biotinylated ssDNA, biotinylated dsDNA, and biotinylated pullulan to a NeutrAvidin-immobilized 27-MHz quartz crystal microbalance (QCM) plate in aqueous solution, as well as in the wet air phase (98% humidity, -Delta F-wet and Delta D-wet) and in the dry air phase (-Delta F-air and Delta D-air). -Delta F-water indicates the total mass of the molecule, bound water, and vibrated water in aqueous solutions. -Delta F-wet indicates the total mass of the molecule and bound water. -Delta F-air simply shows the real mass of the molecule on the QCM. In terms of results, (-Delta F-wet)/(-Delta F-air) values indicated the bound water ratios per unit biomolecular mass were on the order of pullulan (2.1-2.2) &gt; DNAs = proteins (1.4-1.6) &gt; polystyrene (1.0). The (-Delta F-water)/(-Delta F-air) values indicated the hydrodynamic water (bound and vibrated water) ratios per unit biomolecular mass were on the order of dsDNA (6.5) &gt; ssDNA = pullulan (3.5-4.4) &gt; proteins (2.4-2.5) &gt; polystyrene (1.0). Energy dissipation parameters per unit mass in water (Delta D-water/(-Delta F-air)) were on the order of pullulan &gt; dsDNA &gt; ssDNA &gt; proteins &gt; polystyrene. Energy dissipation in the wet and dry air phases (Delta D-wet and Delta D-air) were negligibly small, which indicates even these biomolecules act as elastic membranes in the air phase (without aqueous solution). We obtained a good linear relationship between [(-Delta F-water)/(-Delta F-air) - 1], which is indicative of hydration and Delta D-water/(-Delta F-air) of proteins. The aforementioned values suggest that the energy dissipation of proteins was mainly caused by hydration and that proteins themselves are elastic molecules without energy dissipation in aqueous solutions. On the contrary, plots in cases of denatured proteins, DNAs, and pullulans were relatively deviant toward the large hydration and energy dissipation from the theoretical line as perfect elastic materials, meaning that the large energy dissipation occurs because of viscoelastic properties of denatured proteins, linear DNAs, and pullulans in the water phase, in addition to energy dissipation due to the hydration of molecules. These two parameters could characterize various biomolecules with structural properties in aqueous solutions.

DOI： 10.1021/ac060873x

Web of Science

PubMed

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)   Publisher：羊土社  

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Authorship：Lead author,　Last author,　Corresponding author   Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)   Publisher：Hokuryukan  

File： PM_2021_02_055_森田瑞樹先生_amed_2.pdf

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Language：Japanese   Publishing type：Meeting report  

The development of specialized training programs for medical personnel, particularly nurses, clinical laboratory technicians, and pharmacists, is considered critical for the promotion of genomic medicine throughout Japan. Specifically, medical personnel skilled at analyzing and understanding high-throughput genomic data are in high demand. In this symposium, we will introduce the basic knowledge and skills necessary for processing genomic data.

DOI： 10.1248/yakushi.19-00217-2

PubMed

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

DOI： 10.11477/mf.1543207770

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (other)  

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

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Publishing type：Article, review, commentary, editorial, etc. (international conference proceedings)  

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：Okayama Medical Association  

DOI： 10.4044/joma.128.237

CiNii Article

CiNii Books

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Language：Japanese  

J-GLOBAL

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Language：Japanese   Publisher：(一社)日本外科学会  

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Language：Japanese   Publishing type：Research paper, summary (national, other academic conference)   Publisher：日本難病医療ネットワーク学会  

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Language：Japanese   Publisher：The Institute of Electronics, Information and Communication Engineers  

Useful pseudo data generator that is used in case that real data were not necessary in the medical and other fields, are discussed and partially implemented. The implementation consist of four parts included generating engine and interface layer to input difference equations with random variables. We used perl, python and some of free libraries for our system. Applying for actual uses, we will develop proposed filter programs for modifying time series in future.

CiNii Article

CiNii Books

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Authorship：Lead author   Language：Japanese   Publisher：(一社)日本医療情報学会  

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Authorship：Lead author   Language：Japanese   Publishing type：Research paper, summary (national, other academic conference)  

J-GLOBAL

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Language：Japanese   Publisher：日本難病医療ネットワーク学会  

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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Language：Japanese  

J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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Language：Japanese  

J-GLOBAL

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J-GLOBAL

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J-GLOBAL

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Language：Japanese  

J-GLOBAL

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J-GLOBAL

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Language：Japanese   Publishing type：Article, review, commentary, editorial, etc. (scientific journal)   Publisher：日本生物物理学会  

DOI： 10.2142/biophys.49.151

CiNii Article

CiNii Books

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Event date： 2024.8.2 - 2024.8.3

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Venue：仙台（宮城県）  

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Event date： 2024.8.2 - 2024.8.3

Language：Japanese   Presentation type：Poster presentation  

Venue：仙台（宮城県）  

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Event date： 2024.3.8 - 2024.3.9

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：愛媛県  

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Event date： 2024.3.7 - 2024.3.9

Language：Japanese   Presentation type：Poster presentation  

Venue：大阪府  

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Event date： 2024.2.17 - 2024.2.18

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：岡山県  

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Event date： 2024.2.17 - 2024.2.18

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：岡山県  

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Event date： 2023.10.23 - 2023.10.26

Language：Japanese   Presentation type：Oral presentation (general)  

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Other Link： https://cbi-society.jp/files/annual-meetings/2023/CBI2023_proceedings.pdf

Event date： 2023.7.29

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：千葉  

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Event date： 2023.7.28 - 2023.7.29

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：千葉  

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Event date： 2023.7.28 - 2023.7.29

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：千葉  

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Event date： 2023.7.28 - 2023.7.29

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：千葉  

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Event date： 2023.7.28 - 2023.7.29

Language：Japanese   Presentation type：Poster presentation  

Venue：千葉  

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Event date： 2023.7.28 - 2023.7.29

Language：Japanese   Presentation type：Poster presentation  

Venue：千葉  

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Event date： 2023.3.10 - 2023.3.11

Language：English   Presentation type：Poster presentation  

Venue：Tokyo  

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Event date： 2023.2.9 - 2023.2.10

Language：Japanese   Presentation type：Poster presentation  

Venue：石川県  

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Event date： 2022.11.30 - 2022.12.3

Language：Japanese   Presentation type：Poster presentation  

Venue：横浜（神奈川）  

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Event date： 2022.11.11 - 2022.11.12

Language：Japanese   Presentation type：Poster presentation  

Venue：京都  

岡山大学病院では手術件数が増加する中でも重篤な患者の手術をより安全・安心に行うために，多職種連携のチームによって術前評価・ 術中管理・術後疼痛管理などを行う周術期管理センター（通称PERIO）を2008年に開設した。PERIOによって患者の早期回復や在院日数の短縮などが期待されるが，これまでPERIO導入の評価は十分にできていなかった。そこで本研究では，PERIO導入の効果を定量的に明らかにすることを目的とし，DPCおよびPERIO台帳のデータを利用した後ろ向き観察研究を行なった。2011年から2017年までに脳神経外科（2014年にPERIOを開始）で手術を受けた患者を対象とし，PERIO導入前後の比較を単変量解析および差分の差分法（DID）によって行なった。評価項目は平均在院日数（全体，術前，術後），手術直前中止率，術後合併症発生率（肺炎，肺塞栓症，虚血性心疾患）とした。すべての項目でいずれの方法でも減少傾向が見られた。平均在院日数（全体）と平均在院日数（術前）はいずれの方法でも統計的な有意差が見られ（平均在院日数（全体）は単変量解析で2日減少，DIDで2.5日減少，いずれもP＜0.05），術後合併症発生率はいずれの方法でも有意差が見られなかった。

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Event date： 2022.9.16 - 2022.9.17

Language：Japanese   Presentation type：Poster presentation  

Venue：千葉，オンライン  

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Event date： 2022.8.26

Language：Japanese  

Venue：東京  

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Event date： 2022.7.8 - 2022.7.9

Language：Japanese   Presentation type：Poster presentation  

Venue：岡山  

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Event date： 2022.7.8 - 2022.7.9

Language：Japanese   Presentation type：Poster presentation  

Venue：岡山  

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Event date： 2022.7.8 - 2022.7.9

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：Okayama  

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Event date： 2022.7.8 - 2022.7.9

Language：Japanese   Presentation type：Poster presentation  

Venue：岡山  

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Event date： 2022.7.7 - 2022.7.8

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：Osaka  

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Event date： 2022.2.3 - 2022.2.4

Language：English   Presentation type：Oral presentation (general)  

Venue：Online  

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Event date： 2021.11.8 - 2021.11.10

Language：English   Presentation type：Poster presentation  

Venue：Online  

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Event date： 2021.9.11

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：オンライン  

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Event date： 2021.5.29 - 2021.5.30

Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：オンライン  

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Event date： 2021.5.10 - 2021.5.14

Language：English   Presentation type：Oral presentation (invited, special)  

Venue：Online  

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Event date： 2021.5.10 - 2021.5.14

Language：English   Presentation type：Poster presentation  

Venue：Online  

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Event date： 2021.3.6

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：オンライン  

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Event date： 2021.2.11 - 2021.2.25

Language：Japanese  

Venue：群馬県，オンライン  

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Event date： 2020.10.22 - 2020.10.23

Language：English   Presentation type：Poster presentation  

Venue：Online  

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Event date： 2020.10.22 - 2020.10.23

Language：English   Presentation type：Poster presentation  

Venue：Online  

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Event date： 2020.10.22 - 2020.10.23

Language：English   Presentation type：Poster presentation  

Venue：Online  

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Event date： 2020.9.29 - 2020.9.30

Language：English   Presentation type：Poster presentation  

Venue：Online  

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Event date： 2020.5.25 - 2020.5.27

Language：Japanese   Presentation type：Poster presentation  

Venue：Okayama  

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Event date： 2020.1.18 - 2020.1.19

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京  

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Event date： 2019.10

Language：Japanese  

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Event date： 2019.7.5 - 2019.7.7

Language：Japanese   Presentation type：Poster presentation  

Venue：福岡  

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Event date： 2019.5.7 - 2019.5.10

Language：English   Presentation type：Poster presentation  

Venue：Shanghai  

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Event date： 2019.3.20 - 2019.3.23

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

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Event date： 2019.3

Language：Japanese  

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Event date： 2019.1.25 - 2019.1.26

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：東京  

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Event date： 2018.11.20 - 2018.11.25

Language：Japanese   Presentation type：Poster presentation  

Venue：福岡  

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Event date： 2018.9.19 - 2018.9.21

Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Venue：Tsuruoka (Yamagata)  

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Event date： 2018.8.30 - 2018.9.1

Language：Japanese   Presentation type：Poster presentation  

Venue：Fukuoka (Fukuoka)  

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Event date： 2018.7

Language：Japanese  

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Event date： 2017.11.20 - 2017.11.23

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：大阪  

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Event date： 2017.9.13 - 2017.9.15

Language：English   Presentation type：Poster presentation  

Venue：Stockholm  

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Event date： 2017.7.20

Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：岡山  

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Event date： 2016.11

Language：Japanese  

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Event date： 2016.7.23 - 2016.7.24

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：北海道  

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Event date： 2016.7.23 - 2016.7.24

Language：Japanese   Presentation type：Oral presentation (general)  

Venue：北海道  

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Event date： 2016.7

Language：English  

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Event date： 2016.4.14 - 2016.4.16

Language：Japanese   Presentation type：Poster presentation  

Venue：大阪  

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Event date： 2016.1.27 - 2016.1.29

Language：Japanese   Presentation type：Poster presentation  

Venue：長崎  

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Event date： 2016

Language：Japanese  

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Event date： 2016

Language：Japanese  

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Event date： 2015

Language：Japanese  

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Event date： 2014.11.6

Language：Japanese  

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Event date： 2012.11

Language：Japanese  

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Event date： 2012

Language：English  

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Language：Japanese   Presentation type：Poster presentation  

Venue：岡山  

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Language：Japanese   Presentation type：Symposium, workshop panel (nominated)  

Venue：岡山大学（岡山）  

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Language：Japanese   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Poster presentation  

Venue：沖縄コンベンションセンター（沖縄）  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：慶應義塾大学  

医学・生物学の70%以上の論文は結果が再現できないと言われている。原因の１つに臨床検体の品質がある。つまり，臨床検体の採取・処理・保管・輸送などの各工程をどのように管理するかが重要である。臨床検査においては以前より品質管理の取り組みが進められてきたが，近年は遺伝子関連検査における品質管理も注目を集めている。本講演では，臨床検体を大規模に扱うバイオバンクにおける品質管理について紹介する。

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Language：Japanese   Presentation type：Symposium, workshop panel (public)  

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

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Language：Japanese   Presentation type：Symposium, workshop panel (public)  

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Language：Japanese   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Poster presentation  

Venue：Toyonaka (Osaka)  

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Language：English   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Poster presentation  

Venue：仙台国際センター（宮城県）  

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Language：Japanese   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Okayama  

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Language：Japanese   Presentation type：Poster presentation  

Venue：Bunkyo-ku (Tokyo)  

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Language：Japanese   Presentation type：Oral presentation (invited, special)  

Venue：Kobe  

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Language：Japanese   Presentation type：Poster presentation  

Venue：Fukuoka  

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Language：English   Presentation type：Poster presentation  

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Language：English   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Oral presentation (general)  

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Language：Japanese   Presentation type：Poster presentation  

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Language：English   Presentation type：Oral presentation (general)  

Venue：San Francisco (USA)  

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Language：Japanese   Presentation type：Poster presentation  

Venue：Kobe (Japan)  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Kobe (Japan)  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Tokyo (Japan)  

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Language：English   Presentation type：Oral presentation (invited, special)  

Venue：Valencia (Spain)  

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Language：English   Presentation type：Poster presentation  

Venue：Tokyo (Japan)  

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Language：English   Presentation type：Oral presentation (general)  

Venue：San Francisco (USA)  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：Tokyo (Japan)  

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Language：Japanese  

The exponential growth in the amount of text data requires a method of a text de-identification. So far, most of de-identification methods detect the named entities, such as a person name, location name, IDs and so on, from the texts, and remove them. However, the named entity based methods suffer from a case that non-named entity conveys the personal information. To deal with this problem, this study proposes a new de-identification method that removes document specific expressions. By using this method, possible expression in a document appears in at least other k-1 documents. The experimental results demonstrated that 84% of the health record texts and 37% of the technical papers are preserved after enforcing k-anonymity. This paper also proposes a method to estimate a preservation ratio of the proposed text k-anonymity.

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Language：English  

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Language：English   Presentation type：Oral presentation (general)  

Venue：San Francisco (USA)  

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Language：English   Presentation type：Poster presentation  

Venue：Tokyo (Japan)  

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Language：English   Presentation type：Poster presentation  

Venue：Tokyo (Japan)  

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Language：English   Presentation type：Poster presentation  

Venue：Tokyo (Japan)  

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Language：Japanese  

With the recent rise in popularity and size of social media, there is a growing need for systems that can extract useful information from this amount of data. We address the problem of detecting influenza epidemics. First, the proposed system extracts the influenza related tweets using Twitter API. Then, the SVM based classifies extracts only tweets that include real influenza patients. The experiments demonstrated the feasibility of the proposed approach (0.89 of the correlation to the gold standard). Especially in the rise of the influenza (early stage of the epidemics), the proposed method shows the high accuracy (0.97 correlation), which is the same accuracy to the state-of-the-art method. This paper demonstrated that Twitter texts reflect the real world, and Natural Language Processing (NLP) technique could extracts the information.

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：豊橋技術科学大学（愛知県）  

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Language：English   Presentation type：Poster presentation  

Venue：Cambridge (UK)  

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Language：English  

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Language：English  

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Language：English  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：日本大学理工学部船橋キャンパス（千葉県）  

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Language：Japanese   Presentation type：Public lecture, seminar, tutorial, course, or other speech  

Venue：産総研臨海副都心センター（東京都）  

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Language：English   Presentation type：Poster presentation  

Venue：Tokyo (Japan)  

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Language：English   Presentation type：Poster presentation  

Venue：Toronto (Canada)  

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Language：English   Presentation type：Poster presentation  

Venue：Tokyo (Japan)  

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Language：English   Presentation type：Poster presentation  

Venue：Yokohama (Japan)  

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Language：English   Presentation type：Poster presentation  

Venue：Okinawa (Japan)  

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Language：English   Presentation type：Poster presentation  

Venue：Okinawa (Japan)  

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Language：English   Presentation type：Poster presentation  

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Language：English   Presentation type：Poster presentation  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：神奈川大学横浜キャンパス（横浜県）  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：関西学院大学西宮上ケ原キャンパス（兵庫県）  

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Language：Japanese   Presentation type：Oral presentation (general)  

Venue：熊本大学工学部（熊本県）  

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Audience： General

Type：Lecture

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Audience： Researchesrs,　General,　Scientific,　Company,　Governmental agency

Type：Seminar, workshop

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Audience： High school students,　College students,　Graduate students,　General

Type：Science cafe

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