Ontological theory for ontological engineering: Biomedical systems information integration

Software application ontologies have the potential to become the keystone in state-of-the-art information management techniques. It is expected that these ontologies will support the sort of reasoning power required to navigate large and complex terminologies correctly and efficiently. Yet, there is one problem in particular that continues to stand in our way. As these terminological structures increase in size and complexity, and the drive to integrate them inevitably swells, it is clear that the level of consistency required for such navigation will become correspondingly difficult to maintain. While descriptive semantic representations are certainly a necessary component to any adequate ontology-based system, so long as ontology engineers rely solely on semantic information, without a sound ontological theory informing their modeling decisions, this goal will surely remain out of reach. In this paper we describe how Language and Computing nv (L&C), along with The Institute for Formal Ontology and Medical Information Sciences (IFOMIS), are working towards developing and implementing just such a theory, combining the open software architecture of L&C’s LinkSuiteTM with the philosophical rigor of IFOMIS’s Basic Formal Ontology. In this way we aim to move beyond the more or less simple controlled vocabularies that have dominated the industry to date

ARGOS policy brief on semantic interoperability

Semantic interoperability requires the use of standards, not only for Electronic Health Record (EHR) data to be transferred and structurally mapped into a receiving repository, but also for the clinical content of the EHR to be interpreted in conformity with the original meanings intended by its authors. Accurate and complete clinical documentation, faithful to the patient’s situation, and interoperability between systems, require widespread and dependable access to published and maintained collections of coherent and quality-assured semantic resources, including models such as archetypes and templates that would (1) provide clinical context, (2) be mapped to interoperability standards for EHR data, (3) be linked to well specified, multi-lingual terminology value sets, and (4) be derived from high quality ontologies. Wide-scale engagement with professional bodies, globally, is needed to develop these clinical information standards

Applications of the ACGT Master Ontology on Cancer

In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the ontology within the ACGT project thus far

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

The P2X7 receptor contributes to seizures and inflammation-driven long-lasting brain hyperexcitability following hypoxia in neonatal mice.

Neonatal seizures represent a clinical emergency. However, current anti-seizure medications fail to resolve seizures in ~50% of infants. The P2X7 receptor (P2X7R) is an important driver of inflammation, and evidence suggests that P2X7R contributes to seizures and epilepsy in adults. However, no genetic proof has yet been provided to determine what contribution P2X7R makes to neonatal seizures, its effects on inflammatory signalling during neonatal seizures, and the therapeutic potential of P2X7R-based treatments on long-lasting brain excitability. Neonatal seizures were induced by global hypoxia in 7-day-old mouse pups (P7). The role of P2X7Rs during seizures was analysed in P2X7R-overexpressing and knockout mice. Treatment of wild-type mice after hypoxia with the P2X7R antagonist JNJ-47965567 was used to determine the effects of the P2X7R on long-lasting brain hyperexcitability. Cell type-specific P2X7R expression was analysed in P2X7R-EGFP reporter mice. RNA sequencing was used to monitor P2X7R-dependent hippocampal downstream signalling. P2X7R deletion reduced seizure severity, whereas P2X7R overexpression exacerbated seizure severity and reduced responsiveness to anti-seizure medication. P2X7R deficiency led to an anti-inflammatory phenotype in microglia, and treatment of mice with a P2X7R antagonist reduced long-lasting brain hyperexcitability. RNA sequencing identified several pathways altered in P2X7R knockout mice after neonatal hypoxia, including a down-regulation of genes implicated in inflammation and glutamatergic signalling. Treatments based on targeting the P2X7R may represent a novel therapeutic strategy for neonatal seizures with P2X7Rs contributing to the generation of neonatal seizures, driving inflammatory processes and long-term hyperexcitability states

Ontologies, Mental Disorders and Prototypes

As it emerged from philosophical analyses and cognitive research, most concepts exhibit typicality effects, and resist to the efforts of defining them in terms of necessary and sufficient conditions. This holds also in the case of many medical concepts. This is a problem for the design of computer science ontologies, since knowledge representation formalisms commonly adopted in this field do not allow for the representation of concepts in terms of typical traits. However, the need of representing concepts in terms of typical traits concerns almost every domain of real world knowledge, including medical domains. In particular, in this article we take into account the domain of mental disorders, starting from the DSM-5 descriptions of some specific mental disorders. On this respect, we favor a hybrid approach to the representation of psychiatric concepts, in which ontology oriented formalisms are combined to a geometric representation of knowledge based on conceptual spaces

EXACT2: the semantics of biomedical protocols

© 2014 Soldatova et al.; licensee BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.This article has been made available through the Brunel Open Access Publishing Fund.Background: The reliability and reproducibility of experimental procedures is a cornerstone of scientific practice. There is a pressing technological need for the better representation of biomedical protocols to enable other agents (human or machine) to better reproduce results. A framework that ensures that all information required for the replication of experimental protocols is essential to achieve reproducibility. Methods: We have developed the ontology EXACT2 (EXperimental ACTions) that is designed to capture the full semantics of biomedical protocols required for their reproducibility. To construct EXACT2 we manually inspected hundreds of published and commercial biomedical protocols from several areas of biomedicine. After establishing a clear pattern for extracting the required information we utilized text-mining tools to translate the protocols into a machine amenable format. We have verified the utility of EXACT2 through the successful processing of previously ‘unseen’ (not used for the construction of EXACT2) protocols. Results: The paper reports on a fundamentally new version EXACT2 that supports the semantically-defined representation of biomedical protocols. The ability of EXACT2 to capture the semantics of biomedical procedures was verified through a text mining use case. In this EXACT2 is used as a reference model for text mining tools to identify terms pertinent to experimental actions, and their properties, in biomedical protocols expressed in natural language. An EXACT2-based framework for the translation of biomedical protocols to a machine amenable format is proposed. Conclusions: The EXACT2 ontology is sufficient to record, in a machine processable form, the essential information about biomedical protocols. EXACT2 defines explicit semantics of experimental actions, and can be used by various computer applications. It can serve as a reference model for for the translation of biomedical protocols in natural language into a semantically-defined format.This work has been partially funded by the Brunel University BRIEF award and a grant from Occams Resources

Panic results in unique molecular and network changes in the amygdala that facilitate fear responses

Recurrent panic attacks (PAs) are a common feature of panic disorder (PD) and post-traumatic stress disorder (PTSD). Several distinct brain regions are involved in the regulation of panic responses, such as perifornical hypothalamus (PeF), periaqueductal grey, amygdala and frontal cortex. We have previously shown that inhibition of GABA synthesis in the PeF produces panic-vulnerable rats. Here, we investigate the mechanisms by which a panic-vulnerable state could lead to persistent fear. We first show that optogenetic activation of glutamatergic terminals from the PeF to the basolateral amygdala (BLA) enhanced the acquisition, delayed the extinction and induced the persistence of fear responses 3 weeks later, confirming a functional PeF-amygdala pathway involved in fear learning. Similar to optogenetic activation of PeF, panic-prone rats also exhibited delayed extinction. Next, we demonstrate that panic-prone rats had altered inhibitory and enhanced excitatory synaptic transmission of the principal neurons, and reduced protein levels of metabotropic glutamate type 2 receptor (mGluR2) in the BLA. Application of an mGluR2 positive allosteric modulator (PAM) reduced glutamate neurotransmission in the BLA slices from panic-prone rats. Treating panic-prone rats with mGluR2 PAM blocked sodium lactate (NaLac)-induced panic responses and normalized fear extinction deficits. Finally, in a subset of patients with comorbid PD, treatment with mGluR2 PAM resulted in complete remission of panic symptoms. These data demonstrate that a panic-prone state leads to specific reduction in mGluR2 function within the amygdala network and facilitates fear, and mGluR2 PAMs could be a targeted treatment for panic symptoms in PD and PTSD patients

A pivotal role for starch in the reconfiguration of 14C-partitioning and allocation in Arabidopsis thaliana under short-term abiotic stress.

Plant carbon status is optimized for normal growth but is affected by abiotic stress. Here, we used 14C-labeling to provide the first holistic picture of carbon use changes during short-term osmotic, salinity, and cold stress in Arabidopsis thaliana. This could inform on the early mechanisms plants use to survive adverse environment, which is important for efficient agricultural production. We found that carbon allocation from source to sinks, and partitioning into major metabolite pools in the source leaf, sink leaves and roots showed both conserved and divergent responses to the stresses examined. Carbohydrates changed under all abiotic stresses applied; plants re-partitioned 14C to maintain sugar levels under stress, primarily by reducing 14C into the storage compounds in the source leaf, and decreasing 14C into the pools used for growth processes in the roots. Salinity and cold increased 14C-flux into protein, but as the stress progressed, protein degradation increased to produce amino acids, presumably for osmoprotection. Our work also emphasized that stress regulated the carbon channeled into starch, and its metabolic turnover. These stress-induced changes in starch metabolism and sugar export in the source were partly accompanied by transcriptional alteration in the T6P/SnRK1 regulatory pathway that are normally activated by carbon starvation