Temporal dynamics of spinal cord repair in juvenile and adult zebrafish
Bibliographic record
Abstract
Abstract Understanding the process of successful spinal cord repair in the zebrafish holds significant potential for improving patient health following spinal cord injury (SCI). Presently, beyond early larval stages, we have only limited understanding of the temporal cascade of events facilitating functional recovery, in particular the relationship between the immune response and ependymoglia activity. Here, we investigated this question by comparing the timeline of cellular activity and re-establishment of swimming behaviour in a novel juvenile model of SCI, alongside the commonly studied adult model. We show for the first time that similar to larval SCI, neutrophils are the first responders to injury with peak numbers tightly associated with heightened pro-inflammatory cytokines il-1β and il-8. In both juveniles and adults, maximal microglial recruitment was observed by 3-dpi and sustained onwards, overlapping with peak ependymoglia proliferation. Juveniles reached peak proliferative activity by 3-dpi compared to 7-dpi in adults. Importantly, we found maximum canal diameter directly correlated with peak ependymoglia proliferation, with a greater proportion of cycling cells adjacent the canal. Proliferating ependymoglia produced newborn neurons, including a small number of motor neurons, though output was higher in juveniles. Lastly, we show that functional recovery in juveniles spanned 3-weeks compared to 2-weeks in adults to return to normal swimming activity; both of which exhibited tissue bridging at 14-dpi. Our results map the temporal relationship of critical cellular events leading to functional recovery in post-larval models of SCI, identifying key times during the regenerative process to study the regulatory mechanisms orchestrating the repair process.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".