Reanalysis of published data can help to characterize neuronal death after Spinal Cord Injury
Spinal cord injury (SCI) is a disabling disorder of the spinal cord resulting from trauma or disease. Neuronal death is a central event in the pathophysiology of spinal cord injury. Despite its importance and the large number of research studies carried out, we only have a fragmentary vision of the process focused on the specific targets of each study. It is our opinion that the research community has accumulated enough information which may be reanalyzed with novel tools to get a much more detailed, integrated vision of neuronal death after SCI. This work embeds this vision by creating NeuroCluedo, an open data repository to store and share images as well as the results from their analysis. We have employed this repository to upload the raw and processed images of spinal cord sections from a mouse model of moderate contusive SCI (Reigada et al., 2015) and used this information to: compare manual-, threshold-, and neuronal network-based neuron identifications; and to explore neuronal death at the injury penumbra 21 days after injury and the neuroprotective effects of the anti-apoptotic drug ucf-101. The results from these analyses i) indicate that the three identification methods yield coherent estimates of the total number of neurons per section; ii) identified the neural network as the optimal method, even in spinal sections with major artifacts and marked autofluorescence associated with spinal damage; iii) characterize neuronal distribution among Rexed laminae in the mice T11; iv) reveal that neuronal death distributes through all the gray matter in the penumbrae sections closer to the injury epicenter but concentrate in the intermediate region in sections located farther away; and that v) antiapoptotic effects of UCF-101 are highest in the intermediate region of the gray substance of the caudal segments closest to the injury epicenter. All methods and results, including raw and processed images, software, macros, and scripts, together with all data matrixes and results have been deposited and documented in the Open Science Framework (OSF) repository Neurocluedo (https://osf.io/n32z9/).