Querying semantic catalogues of biomedical databases.

BACKGROUND: Secondary use of health data is a valuable source of knowledge that boosts observational studies, leading to important discoveries in the medical and biomedical sciences. The fundamental guiding principle for performing a successful observational study is the research question and the approach in advance of executing a study. However, in multi-centre studies, finding suitable datasets to support the study is challenging, time-consuming, and sometimes impossible without a deep understanding of each dataset. METHODS: We propose a strategy for retrieving biomedical datasets of interest that were semantically annotated, using an interface built by applying a methodology for transforming natural language questions into formal language queries. The advantages of creating biomedical semantic data are enhanced by using natural language interfaces to issue complex queries without manipulating a logical query language. RESULTS: Our methodology was validated using Alzheimer's disease datasets published in a European platform for sharing and reusing biomedical data. We converted data to semantic information format using biomedical ontologies in everyday use in the biomedical community and published it as a FAIR endpoint. We have considered natural language questions of three types: single-concept questions, questions with exclusion criteria, and multi-concept questions. Finally, we analysed the performance of the question-answering module we used and its limitations. The source code is publicly available at https://bioinformatics-ua.github.io/BioKBQA/. CONCLUSION: We propose a strategy for using information extracted from biomedical data and transformed into a semantic format using open biomedical ontologies. Our method uses natural language to formulate questions to be answered by this semantic data without the direct use of formal query languages.

Elucidating the mode of action of a typical Ras state 1(T) inhibitor.

The small GTPase Ras is an essential component of signal transduction pathways within the cell, controlling proliferation, differentiation, and apoptosis. Only in the GTP-bound form does Ras interact strongly with effector molecules such as Raf-kinase, thus acting as a molecular switch. In the GTP-bound form, Ras exists in a dynamic equilibrium between at least two distinct conformational states, 1(T) and 2(T), offering different functional properties of the protein. Zn2+-cyclen is a typical state 1(T) inhibitor; i.e., it interacts selectively with Ras in conformational state 1(T), a weak effector binding state. Here we report that active K-Ras4B, which is prominently found to be mutated in human tumors, exhibits a dynamic equilibrium like H-Ras, which can be modulated by Zn2+-cyclen. The titration experiments of Ras with Zn2+-cyclen indicate a cooperatively coupled binding of the ligands to the two interaction sites on Ras that could be identified for H-Ras previously. Our data further indicate that as in state 2(T) where induced fit produces the substate 2(T)* after effector binding, a corresponding substate 1(T)* can be detected at the state 1(T) mutant Ras(T35A). The interaction of Zn2+-cyclen with Ras not only shifts the equilibrium toward the weak effector binding state 1(T) but also perturbs the formation of substate 1(T)*, thus enhancing the inhibitory effect. Although Zn2+-cyclen shows an affinity for Ras in only the millimolar range, its potency of inhibition corresponds to a competitive state 2 inhibitor with micromolar binding affinity. Thus, the results demonstrate the mode of action and potency of this class of allosteric Ras inhibitors.

Semantic Data Visualisation for Biomedical Database Catalogues.

Biomedical databases often have restricted access policies and governance rules. Thus, an adequate description of their content is essential for researchers who wish to use them for medical research. A strategy for publishing information without disclosing patient-level data is through database fingerprinting and aggregate characterisations. However, this information is still presented in a format that makes it challenging to search, analyse, and decide on the best databases for a domain of study. Several strategies allow one to visualise and compare the characteristics of multiple biomedical databases. Our study focused on a European platform for sharing and disseminating biomedical data. We use semantic data visualisation techniques to assist in comparing descriptive metadata from several databases. The great advantage lies in streamlining the database selection process, ensuring that sensitive details are not shared. To address this goal, we have considered two levels of data visualisation, one characterising a single database and the other involving multiple databases in network-level visualisations. This study revealed the impact of the proposed visualisations and some open challenges in representing semantically annotated biomedical datasets. Identifying future directions in this scope was one of the outcomes of this work.

Discovery of Biomedical Databases Through Semantic Questioning.

Many clinical studies are greatly dependent on an efficient identification of relevant datasets. This selection can be performed in existing health data catalogues, by searching for available metadata. The search process can be optimised through questioning-answering interfaces, to help researchers explore the available data present. However, when searching the distinct catalogues the lack of metadata harmonisation imposes a few bottlenecks. This paper presents a methodology to allow semantic search over several biomedical database catalogues, by extracting the information using a shared domain knowledge. The resulting pipeline allows the converted data to be published as FAIR endpoints, and it provides an end-user interface that accepts natural language questions.

Biosociological ethodiversity in the social system.

A comprehensive understanding of human sociality needs to embrace the coevolution of genes and culture. Recent advances in biological research about niche construction by organisms, and the development of the concepts of social niche and ethodiversity, can be integrated into a common approach to understand this coevolution, which implies the interaction between sociology and ecology in an integrative framework of knowledge. In this paper the authors propose such inclusive biosociological and heuristic framework to improve the understanding of the evolution of social niche construction. In addition, it allows a better understanding of the concept of sociotype in non-human organisms and explains some aspects of the social or presocial behavior through the concept of ethodiversity.

Virtual Reality Rehabilitation's Impact on Negative Symptoms and Psychosocial Rehabilitation in Schizophrenia Spectrum Disorder: A Systematic Review.

BACKGROUND: Schizophrenia is a chronic psychiatric disorder with symptoms that can severely affect patients' quality of life. While drug administration inhibits most of the positive symptoms, it fails to effectively treat the negative symptoms and in turn relies on rehabilitation therapies. With technological progress, virtual reality (VR) has been the target of recent studies in terms of mental health rehabilitation and has been shown to be a tool with ecological validity in order to introduce the individual to situations similar to their daily life. METHODS: From July to August 2021, we conducted a systematic review with the purpose of understanding the impact of virtual reality rehabilitation on negative symptoms and psychosocial rehabilitation in the schizophrenia spectrum. The searches were performed in the databases Web of Science, Scopus, and PubMed. RESULTS: In our search, we identified 201 results, where 108 duplicates were excluded, resulting in a final balance of 93. After reading and assessing the titles and abstracts, 66 studies were excluded. Of the remaining 27 reports, 23 were excluded for not meeting the previously defined eligibility criteria, resulting in the inclusion of four studies in this systematic review. CONCLUSIONS: The available data on the specific topic was limited and could have been more complete. However, in our review, we were able to identify statistically relevant results demonstrating the effectiveness of intervention. We could find medium to large effects, allowing VR to be an ally for rehabilitation of symptoms related to schizophrenia.

SCALEUS-FD: A FAIR Data Tool for Biomedical Applications.

The Semantic Web and Linked Data concepts and technologies have empowered the scientific community with solutions to take full advantage of the increasingly available distributed and heterogeneous data in distinct silos. Additionally, FAIR Data principles established guidelines for data to be Findable, Accessible, Interoperable, and Reusable, and they are gaining traction in data stewardship. However, to explore their full potential, we must be able to transform legacy solutions smoothly into the FAIR Data ecosystem. In this paper, we introduce SCALEUS-FD, a FAIR Data extension of a legacy semantic web tool successfully used for data integration and semantic annotation and enrichment. The core functionalities of the solution follow the Semantic Web and Linked Data principles, offering a FAIR REST API for machine-to-machine operations. We applied a set of metrics to evaluate its "FAIRness" and created an application scenario in the rare diseases domain.