Automatic knowledge graph population with model-complete text comprehension for pre-clinical outcomes in the field of spinal cord injury.

The paradigm of evidence-based medicine requires that medical decisions are made on the basis of the best available knowledge published in the literature. Existing evidence is often summarized in the form of systematic reviews and/or meta-reviews and is rarely available in a structured form. Manual compilation and aggregation is costly, and conducting a systematic review represents a high effort. The need to aggregate evidence arises not only in the context of clinical trials, but is also important in the context of pre-clinical animal studies. In this context, evidence extraction is important to support translation of the most promising pre-clinical therapies into clinical trials or to optimize clinical trial design. Aiming at developing methods that facilitate the task of aggregating evidence published in pre-clinical studies, in this paper a new system is presented that automatically extracts structured knowledge from such publications and stores it in a so-called domain knowledge graph. The approach follows the paradigm of model-complete text comprehension by relying on guidance from a domain ontology creating a deep relational data-structure that reflects the main concepts, protocol, and key findings of studies. Focusing on the domain of spinal cord injuries, a single outcome of a pre-clinical study is described by up to 103 outcome parameters. Since the problem of extracting all these variables together is intractable, we propose a hierarchical architecture that incrementally predicts semantic sub-structures according to a given data model in a bottom-up fashion. At the heart of our approach is a statistical inference method that relies on conditional random fields to infer the most likely instance of the domain model given the text of a scientific publication as input. This approach allows modeling dependencies between the different variables describing a study in a semi-joint fashion. We present a comprehensive evaluation of our system to understand the extent to which our system can capture a study in the depth required to enable the generation of new knowledge. We conclude the article with a brief description of some applications of the populated knowledge graph and show the potential implications of our work for supporting evidence-based medicine.

Low-pressure micro-mechanical re-adaptation device sustainably and effectively improves locomotor recovery from complete spinal cord injury.

Traumatic spinal cord injuries result in impairment or even complete loss of motor, sensory and autonomic functions. Recovery after complete spinal cord injury is very limited even in animal models receiving elaborate combinatorial treatments. Recently, we described an implantable microsystem (microconnector) for low-pressure re-adaption of severed spinal stumps in rat. Here we investigate the long-term structural and functional outcome following microconnector implantation after complete spinal cord transection. Re-adaptation of spinal stumps supports formation of a tissue bridge, glial and vascular cell invasion, motor axon regeneration and myelination, resulting in partial recovery of motor-evoked potentials and a thus far unmet improvement of locomotor behaviour. The recovery lasts for at least 5 months. Despite a late partial decline, motor recovery remains significantly superior to controls. Our findings demonstrate that microsystem technology can foster long-lasting functional improvement after complete spinal injury, providing a new and effective tool for combinatorial therapies.

Growth/differentiation factor-15 and its role in peripheral nervous system lesion and regeneration.

Growth/differentiation factor-15 (GDF-15) is a distant member of the transforming growth factor beta (TGF-ß) superfamily. It is widely distributed in the nervous system, where it has been shown to play an important role in neuronal maintenance. The present study investigates the role of endogenous GDF-15 in sciatic nerve (SN) lesions using wild-type (WT) and GDF-15 knock-out (KO) mice. SN of 5-6-month-old mice were crushed or transected. Dorsal root ganglia (DRG) and nerve tissue were analyzed at different time points from 6 h to 9 weeks post-lesion. Both crush and transection induced GDF-15 mRNA and protein in the distal portion of the nerve, with a peak at day 7. DRG neuron death did not significantly differ between the genotypes; similarly, remyelination of regenerating axons was not affected by the genotype. Alternative macrophage activation and macrophage recruitment were more pronounced in the KO nerve. Protrusion speed of axons was similar in the two genotypes but WT axons showed better maturation, as indicated by larger caliber at 9 weeks. Furthermore, the regenerated WT nerve showed better performance in the electromyography test, indicating better functional recovery. We conclude that endogenous GDF-15 is beneficial for axon regeneration following SN crush.