Investigating the relationship between the immune response and ependymoglial activation during spinal cord regeneration in the adult and juvenile zebrafish model
Bibliographic record
Abstract
Spinal cord injury (SCI) is a life changing condition affecting individuals within Canada and worldwide with no effective treatment to date. A limitation in humans, like other mammals, is that they cannot repair the damaged central nervous system after injury. By contrast, the zebrafish model has a remarkable ability to regenerate the spinal cord following complete transection, due to neural stem cell populations of ependymoglia. Previous work has shown that for ependymoglial-driven neural regeneration to occur, immune cells are a key requirement. However, in zebrafish the involvement of macrophages and the cytokine response during the process of spinal cord regeneration in post-larval stages remains poorly understood. In this study, I hypothesized that for functional recovery to occur, the pro-inflammatory response following SCI in zebrafish must be activated ahead of ependymoglial proliferation to initiate the regenerative process. To study this response, I developed a new juvenile model of SCI to then compare to the established adult model of SCI. By studying the spatiotemporal dynamics of immune cells post-SCI, I observed that overtime macrophages and microglia infiltrate into the injury site and contributed to cytokine release, correlating with a peak in proliferation of ependymoglia around the central canal. Interestingly, analysis of pro- and anti-inflammatory cytokines from RT-qPCR experiments demonstrated that pro-inflammatory cytokines are highly expressed shortly after injury, but are reduced to near control levels already by 3-days post-SCI. By contrast, anti-inflammatory cytokines appeared to play a minor role in the microenvironment post-SCI, remaining near control levels of expression. These findings propose that in order for successful spinal cord regeneration to occur in adult and juvenile zebrafish, a shorter pro-inflammatory response may be required to initiate ependymoglial proliferation in the spinal cord and restore functional repair.
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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 | 0.001 | 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 | 0.000 |
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".