Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm.

Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)-based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web-based CDSS that provides ranked lists of genetic and rare diseases using HPO-based phenotypic similarities, where top-listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO-based resources.

Reduced lifetime fitness (growth, body condition and survivability) of hatchery-reared tiger pufferfish Takifugu rubripes compared to wild counterparts.

Tiger pufferfish Takifugu rubripes (order Tetraodontiformes, family Tetraodontidae) is a highly exploited species and stocks continue to decline, although hatchery-reared juveniles have been released since 1965 for stock enhancement. To determine why the stock has not recovered through hatchery-release practices, this study investigated and compared the population characteristics of wild and hatchery-origin fish. The length-mass relationship showed that hatchery-origin fish were skinnier, with males weighing less than 90% of the mass of wild males of the same length. The hepatosomatic index tended to be lower in hatchery-origin fish. Age was estimated using the otolith-based method, and the estimates were more accurate and precise than those obtained by the conventional vertebra-based method. At the age of 2.9 years, an age at which specimens were the most abundant in catches, hatchery-origin males weighed only 67% of wild males. The maximum observed age was 12 years for wild fish and 5 years for hatchery-origin fish. The instantaneous total mortality rates of hatchery-origin fish were more than twice as high as those of wild fish. In summary, the hatchery-origin fish had poor health status, poor growth and high mortality, and their fitness in natural environments was therefore hypothesized to be low throughout life.

TogoTable: cross-database annotation system using the Resource Description Framework (RDF) data model.

TogoTable (http://togotable.dbcls.jp/) is a web tool that adds user-specified annotations to a table that a user uploads. Annotations are drawn from several biological databases that use the Resource Description Framework (RDF) data model. TogoTable uses database identifiers (IDs) in the table as a query key for searching. RDF data, which form a network called Linked Open Data (LOD), can be searched from SPARQL endpoints using a SPARQL query language. Because TogoTable uses RDF, it can integrate annotations from not only the reference database to which the IDs originally belong, but also externally linked databases via the LOD network. For example, annotations in the Protein Data Bank can be retrieved using GeneID through links provided by the UniProt RDF. Because RDF has been standardized by the World Wide Web Consortium, any database with annotations based on the RDF data model can be easily incorporated into this tool. We believe that TogoTable is a valuable Web tool, particularly for experimental biologists who need to process huge amounts of data such as high-throughput experimental output.

Discriminative application of string similarity methods to chemical and non-chemical names for biomedical abbreviation clustering.

BACKGROUND: Term clustering, by measuring the string similarities between terms, is known within the natural language processing community to be an effective method for improving the quality of texts and dictionaries. However, we have observed that chemical names are difficult to cluster using string similarity measures. In order to clearly demonstrate this difficulty, we compared the string similarities determined using the edit distance, the Monge-Elkan score, SoftTFIDF, and the bigram Dice coefficient for chemical names with those for non-chemical names. RESULTS: Our experimental results revealed the following: (1) The edit distance had the best performance in the matching of full forms, whereas Cohen et al. reported that SoftTFIDF with the Jaro-Winkler distance would yield the best measure for matching pairs of terms for their experiments. (2) For each of the string similarity measures above, the best threshold for term matching differs for chemical names and for non-chemical names; the difference is especially large for the edit distance. (3) Although the matching results obtained for chemical names using the edit distance, Monge-Elkan scores, or the bigram Dice coefficients are better than the result obtained for non-chemical names, the results were contrary when using SoftTFIDF. (4) A suitable weight for chemical names varies substantially from one for non-chemical names. In particular, a weight vector that has been optimized for non-chemical names is not suitable for chemical names. (5) The matching results using the edit distances improve further by dividing a set of full forms into two subsets, according to whether a full form is a chemical name or not. These results show that our hypothesis is acceptable, and that we can significantly improve the performance of abbreviation-full form clustering by computing chemical names and non-chemical names separately. CONCLUSIONS: In conclusion, the discriminative application of string similarity methods to chemical and non-chemical names may be a simple yet effective way to improve the performance of term clustering.

Insights into genetic variation and demographic history of sharpnose rays: examinations of three species of Telatrygon (Elasmobranchii, Dasyatidae) from the Indo-West Pacific.

Coastal and demersal chondrichthyans (sharks, rays, and skates) are expected to exhibit high levels of genetic differentiation in areas of complex geomorphology. Population genetic studies investigating the extent to which demographic history shapes the genetic structure of these fishes are rare. Here, we combined mitochondrial DNA (Cytb and ND2) and 8 nuclear microsatellite loci from 244 individuals to examine the population genetic structure and demographic history of the 3 Indo-West Pacific species of sharpnose rays (Telatrygon zugei, Telatrygon biasa, and Trygon crozieri). High levels of genetic variation both within and between species were identified. Phylogenetic analysis partitioned haplotypes into 2 lineages supporting divergence of T. zugei from T. crozieri and T. biasa during the Pleistocene. Furthermore, microsatellite-based clustering analyses identified 4 genetic groups (i.e. T. zugei from Japan, T. zugei from coastal China, T. biasa from Gulf of Thailand, and T. crozieri from the Andaman Sea). Measurements of genetic differentiation also support these 4 groups. Additionally, Pleistocene demographic expansions were examined in all genetic groups. The climate oscillations and current hydrologic cycles in the Indo-West Pacific appear to coincide with the hypothesis regarding speciation and the observed demographic history trends of the sharpnose rays. Considering the species group has, until recently, been thought to be one species, these results are critical for defining management units and guiding conservation efforts to preserve stingray biodiversity.

Squalomix: shark and ray genome analysis consortium and its data sharing platform.

The taxon Elasmobranchii (sharks and rays) contains one of the long-established evolutionary lineages of vertebrates with a tantalizing collection of species occupying critical aquatic habitats. To overcome the current limitation in molecular resources, we launched the Squalomix Consortium in 2020 to promote a genome-wide array of molecular approaches, specifically targeting shark and ray species. Among the various bottlenecks in working with elasmobranchs are their elusiveness and low fecundity as well as the large and highly repetitive genomes. Their peculiar body fluid composition has also hindered the establishment of methods to perform routine cell culturing required for their karyotyping. In the Squalomix consortium, these obstacles are expected to be solved through a combination of in-house cytological techniques including karyotyping of cultured cells, chromatin preparation for Hi-C data acquisition, and high fidelity long-read sequencing. The resources and products obtained in this consortium, including genome and transcriptome sequences, a genome browser powered by JBrowse2 to visualize sequence alignments, and comprehensive matrices of gene expression profiles for selected species are accessible through https://github.com/Squalomix/info.

Brain atrophy caused by vitamin B12-deficient anemia in an infant.

Vitamin B12 deficiency in infants often presents with nonspecific hematological, gastrointestinal, and neurological manifestations. It is usually caused by inadequate intake, abnormal absorption, or congenital disorders of vitamin B12 metabolism, including transport disorders. We describe a vitamin B12-deficient infant with severe anemia who was breastfed. His mother had undiagnosed vitamin B12 deficiency having undergone total gastrectomy 18 years earlier. The infant developed normally after taking vitamin B12. It is important to suspect vitamin B12 deficiency in mothers who have undergone gastrectomy. Early diagnosis and treatment of vitamin B12 deficiency in infants is important and will help improve long-term prognosis.

Constructing Japanese MeSH term dictionaries related to the COVID-19 literature.

The coronavirus disease 2019 (COVID-19) pandemic has led to a flood of research papers and the information has been updated with considerable frequency. For society to derive benefits from this research, it is necessary to promote sharing up-to-date knowledge from these papers. However, because most research papers are written in English, it is difficult for people who are not familiar with English medical terms to obtain knowledge from them. To facilitate sharing knowledge from COVID-19 papers written in English for Japanese speakers, we tried to construct a dictionary with an open license by assigning Japanese terms to MeSH unique identifiers (UIDs) annotated to words in the texts of COVID-19 papers. Using this dictionary, 98.99% of all occurrences of MeSH terms in COVID-19 papers were covered. We also created a curated version of the dictionary and uploaded it to PubDictionary for wider use in the PubAnnotation system.

O-JMeSH: creating a bilingual English-Japanese controlled vocabulary of MeSH UIDs through machine translation and mutual information.

Previous approaches to create a controlled vocabulary for Japanese have resorted to existing bilingual dictionary and transformation rules to allow such mappings. However, given the possible new terms introduced due to coronavirus disease 2019 (COVID-19) and the emphasis on respiratory and infection-related terms, coverage might not be guaranteed. We propose creating a Japanese bilingual controlled vocabulary based on MeSH terms assigned to COVID-19 related publications in this work. For such, we resorted to manual curation of several bilingual dictionaries and a computational approach based on machine translation of sentences containing such terms and the ranking of possible translations for the individual terms by mutual information. Our results show that we achieved nearly 99% occurrence coverage in LitCovid, while our computational approach presented average accuracy of 63.33% for all terms, and 84.51% for drugs and chemicals.

Spatial-Temporal Distribution of Megamouth Shark, Megachasma pelagios, Inferred from over 250 Individuals Recorded in the Three Oceans.

The megamouth shark (Megachasma pelagios) is one of the rarest shark species in the three oceans, and its biological and fishery information is still very limited. A total of 261 landing/stranding records were examined, including 132 females, 87 males, and 42 sex unknown individuals, to provide the most detailed information on global megamouth shark records, and the spatial-temporal distribution of M. pelagios was inferenced from these records. The vertical distribution of M. pelagios ranged 0-1203 m in depth, and immature individuals were mostly found in the waters shallower than 200 m. Mature individuals are not only able to dive deeper, but also move to higher latitude waters. The majority of M. pelagios are found in the western North Pacific Ocean (>5° N). The Indian and Atlantic Oceans are the potential nursery areas for this species, immature individuals are mainly found in Indonesia and Philippine waters. Large individuals tend to move towards higher latitude waters (>15° N) for foraging and growth from April to August. Sexual segregation of M. pelagios is found, females tend to move to higher latitude waters (>30° N) in the western North Pacific Ocean, but males may move across the North Pacific Ocean.

A proof-of-concept study of extracting patient histories for rare/intractable diseases from social media.

The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. However, these patient communities are especially active on social media. Data from social media could serve as a source of patient-centric knowledge for these diseases complementary to the information collected in clinical settings and patient registries, and may also have potential for research use. To explore this question, we attempted to extract patient-centric knowledge from social media as a task for the 3-day Biomedical Linked Annotation Hackathon 6 (BLAH6). We selected amyotrophic lateral sclerosis and multiple sclerosis as use cases of rare and intractable diseases, respectively, and we extracted patient histories related to these health conditions from Twitter. Four diagnosed patients for each disease were selected. From the user timelines of these eight patients, we extracted tweets that might be related to health conditions. Based on our experiment, we show that our approach has considerable potential, although we identified problems that should be addressed in future attempts to mine information about rare/intractable diseases from Twitter.

Changes in feeding habits of the starspotted smooth-hound, Mustelus manazo, in Tokyo Bay between periods with different stock size levels.

We investigated differences in the feeding habits of the starspotted smooth-hound, Mustelus manazo, in Tokyo Bay between the mid-1990s (low stock size) and the late 2000s (high stock size). The frequency of M. manazo with empty stomachs increased from 5.9% in the mid-1990s to 16.1% in the late 2000s. A decrease in the relative weight of the stomach contents was evident from the mid-1990s to the late 2000s, especially in the small size classes, along with changes in the species composition in the stomach contents. Although crustaceans were the main constituents of the stomach contents, the proportion of crabs increased while those of shrimps and hermit crabs decreased. Changes in the feeding habits of M. manazo may be associated with shifts in the benthic community structure in Tokyo Bay.

BioHackathon 2015: Semantics of data for life sciences and reproducible research.

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

Split4Blank: Maintaining consistency while improving efficiency of loading RDF data with blank nodes.

In life sciences, accompanied by the rapid growth of sequencing technology and the advancement of research, vast amounts of data are being generated. It is known that as the size of Resource Description Framework (RDF) datasets increases, the more efficient loading to triple stores is crucial. For example, UniProt's RDF version contains 44 billion triples as of December 2018. PubChem also has an RDF dataset with 137 billion triples. As data sizes become extremely large, loading them to a triple store consumes time. To improve the efficiency of this task, parallel loading has been recommended for several stores. However, with parallel loading, dataset consistency must be considered if the dataset contains blank nodes. By definition, blank nodes do not have global identifiers; thus, pairs of identical blank nodes in the original dataset are recognized as different if they reside in separate files after the dataset is split for parallel loading. To address this issue, we propose the Split4Blank tool, which splits a dataset into multiple files under the condition that identical blank nodes are not separated. The proposed tool uses connected component and multiprocessor scheduling algorithms and satisfies the above condition. Furthermore, to confirm the effectiveness of the proposed approach, we applied Split4Blank to two life sciences RDF datasets. In addition, we generated synthetic RDF datasets to evaluate scalability based on the properties of various graphs, such as a scale-free and random graph.

YummyData: providing high-quality open life science data.

Abstract: Many life science datasets are now available via Linked Data technologies, meaning that they are represented in a common format (the Resource Description Framework), and are accessible via standard APIs (SPARQL endpoints). While this is an important step toward developing an interoperable bioinformatics data landscape, it also creates a new set of obstacles, as it is often difficult for researchers to find the datasets they need. Different providers frequently offer the same datasets, with different levels of support: as well as having more or less up-to-date data, some providers add metadata to describe the content, structures, and ontologies of the stored datasets while others do not. We currently lack a place where researchers can go to easily assess datasets from different providers in terms of metrics such as service stability or metadata richness. We also lack a space for collecting feedback and improving data providers' awareness of user needs. To address this issue, we have developed YummyData, which consists of two components. One periodically polls a curated list of SPARQL endpoints, monitoring the states of their Linked Data implementations and content. The other presents the information measured for the endpoints and provides a forum for discussion and feedback. YummyData is designed to improve the findability and reusability of life science datasets provided as Linked Data and to foster its adoption. It is freely accessible at http://yummydata.org/. Database URL: http://yummydata.org/

Oligomeric procyanidins in apple polyphenol are main active components for inhibition of pancreatic lipase and triglyceride absorption.

Inhibitory effects of apple polyphenol extract (AP) and procyanidin contained in AP on in vitro pancreatic lipase activity and in vivo triglyceride absorption in mice and humans were examined. AP and procyanidin considerably inhibited in vitro pancreatic lipase activity. However, polyphenols, except for procyanidin, in AP (i.e., catechins, chalcones, and phenol carboxylic acids) showed weak inhibitory activities on pancreatic lipase. Procyanidins separated by normal-phase chromatography according to the degree of polymerization were also examined. Inhibitory effects of procyanidins increased according to the degree of polymerization from dimer to pentamer. On the other hand, pentamer or greater procyanidins showed maximal inhibitory effects on pancreatic lipase. These results suggested that with respect to in vitro pancreatic lipase inhibition, the degree of polymerization was an important factor and oligomeric procyanidin mainly contributed. Next, we performed a triglyceride tolerance test in mice and humans. Simultaneous ingestion of AP and triglyceride significantly inhibited an increase of plasma triglyceride levels in both models. These results suggested that the oligomeric procyanidins contained in AP inhibited triglyceride absorption by inhibiting pancreatic lipase activity in mice and humans.

The Effect of Aromatherapy Treatment on Fatigue and Relaxation for Mothers during the Early Puerperal Period in Japan: A Pilot Study.

BACKGROUND: Early in the postpartum period, mothers are often nervous and tired from the delivery, breast-feeding and caring for a new-born. The aim of this study was to evaluate the process and outcome of using aromatherapy treatments to increase relaxation and decrease fatigue for mothers during the first to the seventh day of the postpartum period. METHODS: This non-randomized controlled study with a quasi-experimental one-group pretest-posttest design was used to evaluate scores in relaxation and fatigue before and after the intervention. Aromatherapy hand treatments were performed on a purposive sample of 34 postpartum mothers in Tokyo, Japan, from May to July 2016. The single treatment included a choice of one of five essential aroma oils through hand and forearm massage. Relaxation and fatigue were measured by self-administered valid and reliable questionnaires. Wilcoxon signed-rank test was conducted to analyze the data before and after the intervention. The software programs SPSS, v. 23.0 (SPSS, Tokyo), was used to analyze the data, with the significance level set at 5%. RESULTS: Valid responses were obtained from 29 participants. A comparison of the scores before and after aroma treatment intervention indicated that the participants' relaxation scores increased significantly (P<0.001) and fatigue scores were significantly reduced (P<0.001). The majority of participants (77.8%) were satisfied with the treatment. CONCLUSION: The aroma treatments significantly improved relaxation and reduced fatigue for mothers in the early puerperal period and were well received. Therefore, a larger study using a pretest-posttest random control trial is recommended.

Mediators of the effects of rice intake on health in individuals consuming a traditional Japanese diet centered on rice.

Although the Japanese diet is believed to be balanced and healthy, its benefits have been poorly investigated, especially in terms of effects on mental health. We investigated dietary patterns and physical and mental health in the Japanese population using an epidemiological survey to determine the health benefits of the traditional Japanese diet. Questionnaires to assess dietary habits, quality of life, sleep quality, impulsivity, and depression severity were distributed to 550 randomly selected middle-aged and elderly individuals. Participants with any physical or mental disease were excluded. Two-hundred and seventy-eight participants were selected for the final statistical analysis. We determined rice to be one of the most traditional foods in Japanese cuisine. Scores for each questionnaire were computed, and the correlations between rice intake and health indices were assessed. When analyzing the direct correlations between rice intake and health indices, we found only two correlations, namely those with quality of life (vitality) and sleep quality. Path analysis using structural equation modeling was performed to investigate the association between rice intake and health, with indirect effects included in the model. Additional associations between rice intake and health were explained using this model when compared to those using direct correlation analysis. Path analysis was used to identify mediators of the rice-health association. These mediators were miso (soybean paste) soup, green tea, and natto (fermented soybean) intake. Interestingly, these mediators have been major components of the Japanese diet since 1975, which has been considered one of the healthiest diets since the 1960s. Our results indicate that the combination of rice with other healthy foods, which is representative of the traditional Japanese diet, may contribute to improvements in physical and mental health.

KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains.

KCaM (KEGG Carbohydrate Matcher) is a tool for the analysis of carbohydrate sugar chains, or glycans. It consists of a web-based graphical user interface that allows users to enter glycans easily with the mouse. The glycan structure is then transformed into our KCF (KEGG Chemical Function) file format and sent to our program which implements an efficient tree-structure alignment algorithm, similar to sequence alignment algorithms but for branched tree structures. Users can also retrieve glycan tree structures in KCF format from their local computers for visualization over the web. The tree-matching algorithm provides several options for performing different types of tree-matching procedures on glycans. These options consist of whether to incorporate gaps in a match, whether to take the linkage information into consideration and local versus global alignment. The results of this program are returned as a list of glycan structures in order of similarity based on these options. The actual alignment can be viewed graphically, and the annotation information can also be viewed easily since all this information is linked with KEGG's comprehensive suite of genomic data. Analogously to BLAST, users are thus able to compare glycan structures of interest with glycans from different glycan databases using a variety of tree-alignment options. KCaM is currently available at http://glycan.genome.ad.jp.

Structural basis for the recognition of two consecutive mutually interacting DPF motifs by the SGIP1 µ homology domain.

FCHo1, FCHo2, and SGIP1 are key regulators of clathrin-mediated endocytosis. Their µ homology domains (µHDs) interact with the C-terminal region of an endocytic scaffold protein, Eps15, containing fifteen Asp-Pro-Phe (DPF) motifs. Here, we show that the high-affinity µHD-binding site in Eps15 is a region encompassing six consecutive DPF motifs, while the minimal µHD-binding unit is two consecutive DPF motifs. We present the crystal structures of the SGIP1 µHD in complex with peptides containing two DPF motifs. The peptides bind to a novel ligand-binding site of the µHD, which is distinct from those of other distantly related µHD-containing proteins. The two DPF motifs, which adopt three-dimensional structures stabilized by sequence-specific intramotif and intermotif interactions, are extensively recognized by the µHD and are both required for binding. Thus, consecutive and singly scattered DPF motifs play distinct roles in µHD binding.