Neural stem/progenitor cells are activated during tail regeneration in the leopard gecko (<i>Eublepharis macularius</i>)
Bibliographic record
Abstract
As for many lizards, the leopard gecko (Eublepharis macularius) can self-detach its tail to avoid predation and then regenerate a replacement. The replacement tail includes a regenerated spinal cord with a simple morphology: an ependymal layer surrounded by nerve tracts. We hypothesized that cells within the ependymal layer of the original spinal cord include populations of neural stem/progenitor cells (NSPCs) that contribute to the regenerated spinal cord. Prior to tail loss, we performed a bromodeoxyuridine pulse-chase experiment and found that a subset of ependymal layer cells (ELCs) were label-retaining after a 140-day chase period. Next, we conducted a detailed spatiotemporal characterization of these cells before, during, and after tail regeneration. Our findings show that SOX2, a hallmark protein of NSPCs, is constitutively expressed by virtually all ELCs before, during, and after regeneration. We also found that during regeneration, ELCs express an expanded panel of NSPC and lineage-restricted progenitor cell markers, including MSI-1, SOX9, and TUJ1. Using electron microscopy, we determined that multiciliated, uniciliated, and biciliated cells are present, although the latter was only observed in regenerated spinal cords. Our results demonstrate that cells within the ependymal layer of the original, regenerating and fully regenerate spinal cord represent a heterogeneous population. These include radial glia comparable to Type E and Type B cells, and a neuronal-like population of cerebrospinal fluid-contacting cells. We propose that spinal cord regeneration in geckos represents a truncation of the restorative trajectory observed in some urodeles and teleosts, resulting in the formation of a structurally distinct replacement.
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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 | 0.000 |
| 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".