Spinal cord injury (SCI) results in a cascade of primary and secondary damage, with apoptosis being a prominent cause of neuronal cell death. The X-linked inhibitor of apoptosis (XIAP) plays a critical role in inhibiting apoptosis, but its expression is reduced following SCI, contributing to increased neuronal vulnerability. This study investigates the regulatory role of miR-199a-5p on XIAP expression in the context of SCI. Using bioinformatic tools, luciferase reporter assays, and in vitro and in vivo models of SCI, we identified miR-199a-5p as a post-transcriptional regulator of XIAP. Overexpression of miR-199a-5p significantly reduced XIAP protein levels, although no changes were observed at the mRNA level, suggesting translational repression. In vivo, miR-199a-5p expression was upregulated at 3 and 7 days post-injury, while XIAP expression inversely decreased in both neurons and oligodendrocytes, being particularly significant in the latter at 7 dpi. These findings suggest that miR-199a-5p contributes to the downregulation of XIAP and may exacerbate neuronal apoptosis after SCI. Targeting miR-199a-5p could offer a potential therapeutic strategy to modulate XIAP levels and reduce apoptotic cell death in SCI.

Neuronal death is a central event in spinal cord injury (SCI) pathophysiology. Despite its importance, we have a fragmentary vision of the process. In our opinion, the research community has accumulated enough information to provide a more detailed, integrated vision of neuronal death after SCI. This work embeds this vision by creating an open repository to store and share data and results from their analysis. We have employed this repository to upload raw images of spinal cord sections from a mouse model of contusive SCI and used this information to compare manual-, threshold-, and neural network-based neuron identifications and to explore neuronal death at the injury penumbra 21 days after injury and the effects of the anti-apoptotic drug ucf-101. Results indicate that, whereas the three identification methods assayed yield coherent estimates of the total number of neurons per section, neural network (NN) outperforms the other two methods. Combining NN identification and image registration has allowed us to characterize neuron distribution among Rexed laminae in the mice T11, revealing spatial patterns in the neuronal death that follows injury and in their survival following ucf-101 treatment.

The adult lumbar spinal cord plays a critical role in locomotor control and somatosensory integration, yet its transcriptional architecture remains incompletely characterized under physiological conditions. Here, we present an integrative single-nucleus RNA se-quencing (snRNA-seq) atlas of the healthy adult mouse lumbar spinal cord, assembled from over 86,000 nuclei across five public datasets. Using a harmonized computational pipeline, we identify all major spinal cell lineages and resolve 17 transcriptionally distinct neuronal subtypes. A central novelty of our approach is the systematic inclusion of non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) and pseudogenes. By comparing transcriptomic analyses based on coding-only, non-coding-only, and combined gene sets, we demonstrate that ncRNAs contribute cell type-specific signatures that enhance neuronal subtype resolution. Differential expression analysis highlights lineage-associated ncRNAs enriched in sensory, inhibitory, and ependymal populations. This resource offers a high-resolution, ncRNA-inclusive refer-ence for the adult spinal cord and provides a foundation for future studies on spinal plasticity, injury, and regeneration.