Spinal Interneuron Axons Spontaneously Regenerate after Spinal Cord Injury in the Adult Feline
Bibliographic record
Abstract
It is well established that long, descending axons of the adult mammalian spinal cord do not regenerate after a spinal cord injury (SCI). These axons do not regenerate because they do not mount an adequate regenerative response and growth is inhibited at the injury site by growth cone collapsing molecules, such as chondroitin sulfate proteoglycans (CSPGs). However, whether axons of axotomized spinal interneurons regenerate through the inhibitory environment of an SCI site remains unknown. Here, we show that cut axons from adult mammalian spinal interneurons can regenerate through an SCI site and form new synaptic connections in vivo. Using morphological and immunohistochemical analyses, we found that after a midsagittal transection of the adult feline spinal cord, axons of propriospinal commissural interneurons can grow across the lesion despite a close proximity of their growth cones to CSPGs. Furthermore, using immunohistochemical and electrophysiological analyses, we found that the regenerated axons conduct action potentials and form functional synaptic connections with motoneurons, thus providing new circuits that cross the transected commissures. Our results show that interneurons of the adult mammalian spinal cord are capable of spontaneous regeneration after injury and suggest that elucidating the mechanisms that allow these axons to regenerate may lead to useful new therapeutic strategies for restoring function after injury to the adult CNS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".