Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

BackgroundUsing knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms?ResultsOur existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important.ConclusionsWith some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels

A Formal Ontology of Subcellular Neuroanatomy

The complexity of the nervous system requires high-resolution microscopy to resolve the detailed 3D structure of nerve cells and supracellular domains. The analysis of such imaging data to extract cellular surfaces and cell components often requires the combination of expert human knowledge with carefully engineered software tools. In an effort to make better tools to assist humans in this endeavor, create a more accessible and permanent record of their data, and to aid the process of constructing complex and detailed computational models, we have created a core of formalized knowledge about the structure of the nervous system and have integrated that core into several software applications. In this paper, we describe the structure and content of a formal ontology whose scope is the subcellular anatomy of the nervous system (SAO), covering nerve cells, their parts, and interactions between these parts. Many applications of this ontology to image annotation, content-based retrieval of structural data, and integration of shared data across scales and researchers are also described

The Neuroscience Information Framework: A Data and Knowledge Environment for Neuroscience

With support from the Institutes and Centers forming the NIH Blueprint for Neuroscience Research, we have designed and implemented a new initiative for integrating access to and use of Web-based neuroscience resources: the Neuroscience Information Framework. The Framework arises from the expressed need of the neuroscience community for neuroinformatic tools and resources to aid scientific inquiry, builds upon prior development of neuroinformatics by the Human Brain Project and others, and directly derives from the Society for Neuroscience’s Neuroscience Database Gateway. Partnered with the Society, its Neuroinformatics Committee, and volunteer consultant-collaborators, our multi-site consortium has developed: (1) a comprehensive, dynamic, inventory of Web-accessible neuroscience resources, (2) an extended and integrated terminology describing resources and contents, and (3) a framework accepting and aiding concept-based queries. Evolving instantiations of the Framework may be viewed at http://nif.nih.gov, http://neurogateway.org, and other sites as they come on line

MyD88-dependent, superoxide-initiated inflammation is necessary for flow-mediated inward remodeling of conduit arteries

Vascular remodeling normalizes abnormal hemodynamic stresses through structural changes affecting vessel size and wall thickness. We investigated the role of inflammation in flow-mediated vascular remodeling using a murine model of partial outflow reduction without flow cessation or neointima formation. Common carotid arteries decreased in size after ipsilateral external carotid artery ligation in wild-type mice, but not in myeloid differentiation protein-88 (MyD88)–deficient mice. Inward remodeling was associated with MyD88-dependent and superoxide-initiated cytokine and chemokine production, as well as transient adventitial macrophage accumulation and activation. Macrophage depletion prevented flow-mediated inward vascular remodeling. Expression of MyD88 by intrinsic vascular cells was necessary for cytokine and chemokine production and changes in vessel size, whereas MyD88 expression by bone marrow–derived cells was obligatory for changes in vessel size. We conclude that there are at least two distinct roles for MyD88 in flow-mediated inward remodeling of conduit arteries. Our findings suggest that inflammation is necessary for vascular adaptation to changes in hemodynamic forces

Comparative analytical performance of multiple plasma Aβ42 and Aβ40 assays and their ability to predict positron emission tomography amyloid positivity

INTRODUCTION: This report details the approach taken to providing a dataset allowing for analyses on the performance of recently developed assays of amyloid beta (Aβ) peptides in plasma and the extent to which they improve the prediction of amyloid positivity. METHODS: Alzheimer's Disease Neuroimaging Initiative plasma samples with corresponding amyloid positron emission tomography (PET) data were run on six plasma Aβ assays. Statistical tests were performed to determine whether the plasma Aβ measures significantly improved the area under the receiver operating characteristic curve for predicting amyloid PET status compared to age and apolipoprotein E (APOE) genotype. RESULTS: The age and APOE genotype model predicted amyloid status with an area under the curve (AUC) of 0.75. Three assays improved AUCs to 0.81, 0.81, and 0.84 (P < .05, uncorrected for multiple comparisons). DISCUSSION: Measurement of Aβ in plasma contributes to addressing the amyloid component of the ATN (amyloid/tau/neurodegeneration) framework and could be a first step before or in place of a PET or cerebrospinal fluid screening study. HIGHLIGHTS: The Foundation of the National Institutes of Health Biomarkers Consortium evaluated six plasma amyloid beta (Aβ) assays using Alzheimer's Disease Neuroimaging Initiative samples. Three assays improved prediction of amyloid status over age and apolipoprotein E (APOE) genotype. Plasma Aβ42/40 predicted amyloid positron emission tomography status better than Aβ42 or Aβ40 alone

DTT - Divertor Tokamak Test facility: A testbed for DEMO

The effective treatment of the heat and power exhaust is a critical issue in the road map to the realization of the fusion energy. In order to provide possible, reliable, well assessed and on-time answers to DEMO, the Divertor Tokamak Test facility (DTT) has been conceived and projected to be carried out and operated within the European strategy in fusion technology. This paper, based on the invited plenary talk at the 31st virtual SOFT Conference 2020, provides an overview of the DTT scientific proposal, which is deeply illustrated in the 2019 DTT Interim Design Report