Ionships.Methods As shown in Figure 2, citations related to nervous system trauma were retrieved from PubMed. From these, predications were extracted that contain a substance as the subject or object. These predications were organized into a single network which is then filtered to select for the most highly connected and frequent components. The substances included in this summary network serve as the list of potential mTBI biomarkers.Citation searchforms of injury included under this broad heading in light of their inclusion of common injury pathways such as inflammation and oxidative damage. 99,437 unique citations were returned by this search.Semantic predication selectionA PubMed search for all articles containing the MeSH term Trauma, Nervous System was used to generate a list of PubMed D(+)-Galactosamine (hydrochloride) identification numbers (PMIDs). This term is a parent to Brain Injuries in the MeSH hierarchy and also includes terms such as Spinal Cord Injuries and Cerebrovascular Trauma. The source publications were limited only in requiring that they included neural injury as a topic, with no limitations on journal, species, location, or type of injury. Although this included non-TBI injury and models, (e.g., stroke, spinal cord injury, hypoglossal-nerve injury, etc.), the goal was to undertake as wide a search as possible in order to retrieve remote and ignored possibilities, with the assumption that a significant level of commonality exists between the variousSemantic predications were extracted from SemMedDB using the PMIDs resulting from the above PubMed search, which yielded 26,441 unique predications. Overall, this set contains 6246 unique concepts, including less informative terms, such as rattus, injury, and patients as well as more specific terms, such as glutamate, brainderived neurotrophic factor, and methylprednisolone. We then required the predications to contain at least one concept (subject or object) having a UMLS semantic type with potential as a substance biomarker (amino acid sequence; amino acid, peptide, or protein; biologically active substance; body substance; carbohydrate; carbohydrate sequence; chemical; chemical viewed functionally; chemical viewed structurally; eicosanoid; enzyme; gene or gene product; gene or genome; hormone; immunologic factor; inorganic chemical; lipid; neuroreactive substance or biogenic amine; nucleic acid, nucleoside, or nucleotide; nucleotide sequence; organic chemical;Cairelli et al. Journal of Biomedical Semantics (2015) 6:Page 5 oforganophosphorus compound; receptor; steroid; substance). If only one of the arguments was of this type, the other concept could PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/16989806 be of any semantic type. This resulted in the inclusion of some concepts that indicate that the research was performed in animal models such as Rattus and Animals. We did not discard these nodes because they allow the inclusion of potential biomarkers from basic research in the spirit of translational medicine. Although a given semantic type, for instance "Pharmaceutical Substance", was not included in the list of target semantic types, it could still appear in a resulting predication if the complimentary subject or object met the requirements. As an example, in the predication Dexamethasone INTERACTS_WITH NF-kappa B, the subject, Dexamethasone, is of type Pharmaceutical Substance and the object, NF-kappa B, is of type Amino Acid, Peptide, or Protein. This predication qualifies for inclusion because of the object, not the subject. In the predication Dex.