Fc multimers effectively treat murine models of multiple sclerosis.

Multiple Sclerosis (MS) is a chronic neurodegenerative disease with limited therapeutic options. Recombinant Fc multimers (rFc), designed to mirror many of the anti-inflammatory activities of Intravenous Immunoglobulin (IVIG), have been shown to effectively treat numerous immune-mediated diseases in rodents. In this study we used the experimental autoimmune encephalomyelitis (EAE) murine model of MS to test the efficacy of a rFc, M019, that consists of multimers of the Fc portion of IgG2, in inhibiting disease severity. We show that M019 effectively reduced clinical symptoms when given either pre- or post-symptom onset compared to vehicle treated EAE induced mice. M019 was effective in reducing symptoms in both SJL model of relapsing remitting MS as well as the B6 model of chronic disease. M019 binds to FcγR bearing-monocytes both in vivo and in vitro and prevented immune cell infiltration into the CNS of treated mice. The lack of T cell infiltration into the spinal cord was not due to a decrease in T cell priming; there was an equivalent frequency of Th17 cells in the spleens of M019 and vehicle treated EAE induced mice. Surprisingly, there was an increase in chemokines in the sera but not in the CNS of M019 treated mice compared to vehicle treated animals. We postulate that M019 interacts with a FcγR rich monocyte intermediary to prevent T cell migration into the CNS and demyelination.

ECO: the Evidence and Conclusion Ontology, an update for 2022.

The Evidence and Conclusion Ontology (ECO) is a community resource that provides an ontology of terms used to capture the type of evidence that supports biomedical annotations and assertions. Consistent capture of evidence information with ECO allows tracking of annotation provenance, establishment of quality control measures, and evidence-based data mining. ECO is in use by dozens of data repositories and resources with both specific and general areas of focus. ECO is continually being expanded and enhanced in response to user requests as well as our aim to adhere to community best-practices for ontology development. The ECO support team engages in multiple collaborations with other ontologies and annotating groups. Here we report on recent updates to the ECO ontology itself as well as associated resources that are available through this project. ECO project products are freely available for download from the project website (https://evidenceontology.org/) and GitHub (https://github.com/evidenceontology/evidenceontology). ECO is released into the public domain under a CC0 1.0 Universal license.

ECO-CollecTF: A Corpus of Annotated Evidence-Based Assertions in Biomedical Manuscripts.

Analysis of high-throughput experiments in the life sciences frequently relies upon standardized information about genes, gene products, and other biological entities. To provide this information, expert curators are increasingly relying on text mining tools to identify, extract and harmonize statements from biomedical journal articles that discuss findings of interest. For determining reliability of the statements, curators need the evidence used by the authors to support their assertions. It is important to annotate the evidence directly used by authors to qualify their findings rather than simply annotating mentions of experimental methods without the context of what findings they support. Text mining tools require tuning and adaptation to achieve accurate performance. Many annotated corpora exist to enable developing and tuning text mining tools; however, none currently provides annotations of evidence based on the extensive and widely used Evidence and Conclusion Ontology. We present the ECO-CollecTF corpus, a novel, freely available, biomedical corpus of 84 documents that captures high-quality, evidence-based statements annotated with the Evidence and Conclusion Ontology.