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Objectives: There are many occasions in modern life when people must deliver presentations in front of audiences. Most people feel nervous before and while giving a speech. If there were a simple way to ease their stress, speakers would be able to perform better and their quality of life would improve. Consequently, this study aimed to alleviate the stress of speakers giving speeches by regulating breathing using a simple device.Methods: To achieve this goal, a popular device, the Apple Watch, was chosen. Twenty-eight participants were divided into two groups: the Breathe app group and the non-Breathe app group. The Breathe app group regulated their breathing using the Breathe app installed on an Apple Watch before speech preparation. The non-Breathe app group listened to an explanation of the experiment so that they could not undertake their own stress-easing strategies. Participants prepared speeches about themselves and delivered them in front of the researcher.Results: The Breathe app exercise eased stress during the exercise itself and the preparation phase of the speech task based on participants’ cardiac activity. However, stress was not alleviated during speech delivery.Conclusions: Based on the experimental setting and results of this study, together with the findings of previous studies, introducing pre-training sessions and performing stress-easing tasks before and/or during a speech, such as sending vibrations to participants’ wearable devices, might be an effective way to reduce stress when delivering speeches immediately after the breath-regulating task.

Summary Human biomedical datasets that are critical for research and clinical studies to benefit human health also often contain sensitive or potentially identifying information of individual participants. Thus, care must be taken when they are processed and made available to comply with ethical and regulatory frameworks and informed consent data conditions. To enable and streamline data access for these biomedical datasets, the Global Alliance for Genomics and Health (GA4GH) Data Use and Researcher Identities (DURI) work stream developed and approved the Data Use Ontology (DUO) standard. DUO is a hierarchical vocabulary of human and machine-readable data use terms that consistently and unambiguously represents a dataset’s allowable data uses. DUO has been implemented by major international stakeholders such as the Broad and Sanger Institutes and is currently used in annotation of over 200,000 datasets worldwide. Using DUO in data management and access facilitates researchers’ discovery and access of relevant datasets. DUO annotations increase the FAIRness of datasets and support data linkages using common data use profiles when integrating the data for secondary analyses. DUO is implemented in the Web Ontology Language (OWL) and, to increase community awareness and engagement, hosted in an open, centralized GitHub repository. DUO, together with the GA4GH Passport standard, offers a new, efficient, and streamlined data authorization and access framework that has enabled increased sharing of biomedical datasets worldwide., Graphical abstract, Highlights Biomedical advances depend on the efficient and compliant re-use of sensitive human data The Data Use Ontology standardizes terms and definitions for consented data uses The Data Use Ontology facilitates discovery of, request for, and access to datasets Over 200,000 datasets worldwide have been annotated using the Data Use Ontology, The GA4GH Data Use Ontology (DUO) provides unambiguous, machine-readable standard language for consent forms and the data sharing policies they represent. Lawson et al. describe the DUO standard and implementations throughout the data access workflow to expedite data access while maintaining or improving compliant processes.

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.

BackgroundResearch infrastructure such as patient registries and biobanks is expected to play important roles by aggregating information and biospecimens to promote research and development for rare diseases. However, both building and maintaining them can be costly. This paper presents results of a survey of patient registries for rare diseases in Japan conducted at the end of 2012, with emphasis on clarifying costs and efforts related to building and maintaining them.ResultsOf 31 patient registries in Japan found by searching a database of research grant reports and by searching the internet, 11 returned valid responses to this survey. Results show that labor and IT system costs are major expenses for developing and maintaining patient registries. Half of the respondent patient registries had no prospect of securing a budget to maintain them. Responders required the following support for patient registries: financial support, motivation of registrants (medical doctors or patients), and improved communication with and visibility to potential data users. These results resemble those reported from another survey conducted almost simultaneously in Europe (EPIRARE survey).ConclusionsSurvey results imply that costs and efforts to build and maintain patient registries for many rare diseases make them unrealistic. Some alternative strategy is necessary to reduce burdens, such as offering a platform that supplies IT infrastructure and basic secretariat functions that can be used commonly among many patient registries.

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.

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.

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.

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 (R2=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.

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.

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.

How vital signs change at the end of life is a frequently asked question by health-care professionals, patients, and families, and research groups have attempted to identify specific changes and indicators associated with impending death. This study proposed a new method for detecting characteristic changes in vital signs associated with patient’s death based on time-series data measured by a pressuresensing mat. The pressure-sensing mat is less invasive and can automatically log heart and respiratory rates with high temporal resolutions. In the proposed method, the probability density functions (PDFs) of vital signs are estimated based on the large amount of data, and temporal changes in the PDFs are evaluated using an information measure, the Jenson-Shannon divergence (JSD). The proposed method was used to detect changes in vital signs of homecare patients to demonstrate its applicability. By tracking the temporal changes in the PDFs and JSD of vital signs, the specific changes associated with death can be detected. The proposed method can be a promising approach in quantitative and simplified prediction of impending death in homecare patients.

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 G1 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.

Determination of agronomically important traits with DNA markers in genetically segregating populations is a key to high-throughput breeding of apple trees. In the present report, we first estimated usefulness of four PCR-based DNA markers of apple in a set of 22 apple cultivars, which include popular cultivars in Japan such as ‘Fuji’, ‘Orin’, and ‘Shinano Gold’. The four DNA markers are reported to determine fruit storage life (ethylene production), fruit skin color, Alternaria resistance, and scab resistance. The target genes/locus of these DNA markers are MdACS1 gene, MdMYB1 gene, MdAlt locus, and MfVf gene. The types of these DNA markers are SSLP, dCAPS, allele-specific, and gene-specific, thus the markers were designated MdACS1-SSLP, MdMYB1-dCAPS(BstEII), MdAlt-AS, and MfVf-GS, respectively. DNA band patterns after gel electrophoresis were reasonable and consistent with previous reports for MdACS1-SSLP and MfVf-GS markers. On the contrary, band patterns of the MdAlt-AS marker were not necessarily consistent with Alternaria tolerance of the apple cultivars. It was also quite difficult to determine genotypes from the band patterns of the BstEII-based dCAPS marker MdMYB1-dCAPS(BstEII). Attachment of DS6 adaptor sequence to the forward primer improved genotype determinations, by making clear difference between the sizes of allelic DNA bands. Further improvement of this DNA marker was also achieved by the MdMYB1-CAPS(PmlI) marker, which is a PmlI-based CAPS marker. MdMYB1 genotypes determined by the MdMYB1-CAPS(PmlI) marker was consistent with apple skin colors and their genetic segregations.

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. Availability and implementation: Toxygates is freely available to the public at http://toxygates.nibio.go.jp. Contact: johan@nibio.go.jp, kenji@nibio.go.jp or y-igarashi@nibio.go.jp Supplementary information: Supplementary data are available at Bioinformatics online.

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.

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 (DeltaF(water)) were observed compared with those in the air phase (DeltaF(air)) 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 [(-DeltaF(water))/(-DeltaF(air)) - 1] could be explained by frictional forces at the interface of proteins with aqueous solutions. When [(-DeltaF(water))/(-DeltaF(air)) - 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 DeltaF(water) than DeltaF(air) 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.

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.

Differential cross sections and decay asymmetries for coherent $\phi$-meson photoproduction from deuterons were measured for the first time at forward angles using linearly polarized photons at $E_{\gamma}$= 1.5-2.4 GeV. This reaction offers a unique way to directly access natural-parity Pomeron dynamics and gluon exchange at low energies. The cross sections at zero degrees increase with increasing photon energy. The decay asymmetries demonstrate a complete dominance of natural-parity exchange processes, showing that isovector unnatural-parity $\pi$-meson exchange is small. Nevertheless the deduced cross sections of $\phi$-mesons from nucleons contributed by isoscalar t-channel exchange processes are not well described by the conventional Pomeron model., Comment: 14 pages, 6 figures. Final published version