Cells lining the lateral ventricle show dynamic protein expression following tail loss in the leopard gecko
Bibliographic record
Abstract
Neural stem progenitor cells (NSPCs) have been identified in the adult mammalian central nervous system, specifically in the dentate gyrus of the hippocampus and in the subventricular zone of the lateral ventricle. Despite this, mammals are incapable of central nervous system regeneration following injury. In contrast, many lizard species can regenerate their spinal cord (following tail loss) and some can even repair the optic nerve and parts of the brain. However, the source of cells contributing to brain regeneration remains unclear. Here we characterize cells lining the lateral ventricle of the brain in the leopard gecko, Eublepharis macularius. We show that these ventricular lining, or periventricular cells are a potential progenitor population capable of responding to central nervous system injury. Using a bromodeoxyuridine (BrdU) pulse‐chase experiment we determined that, prior to injury, periventricular cells are slow‐cycling. Moreover, periventricular cells show widespread expression of several common NSPC markers, including the transcription factor Sox2 and the intermediate filament glial fibrillary acidic protein (GFAP). In addition, a subset of periventricular cells express the neural progenitor cell marker Sox9. Following injury to the spinal cord (as a result of tail loss) populations of periventricular cells lining the lateral ventricle continue to express NSPC markers but also begin to proliferate, as evidenced by expression of both proliferating cell nuclear antigen (PCNA) and phosphohistone H3. Intriguingly, some of these cells newly express HuC/D, a marker of neuronal differentiation. Dynamic protein expression by periventricular cells indicates that this population is activated in response to injury, and points towards their potential to participate in neural regeneration. Support or Funding Information Natural Sciences and Engineering Research Council (NSERC) Discovery Grant 400358
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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 | 0.000 |
| 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".