Spontaneous neuronal regeneration following lesioning in the brain of the leopard gecko ( <i>Eublepharis macularius</i> )
Bibliographic record
Abstract
Among amniotes, lizards are often recognized as demonstrating some of the most striking examples of spontaneous central nervous system repair. These include regeneration of the spinal cord following loss of the tail, and the restoration of the optic nerve following transection. Several species of from one group of lizards (Lacertidae) are also reportedly capable of spontaneous generating new neurons following injury to the forebrain. Whether this regenerative capacity extends to other lizard species remains untested. Here, we address this evolutionary gap by investigating the potential for injury‐mediated neurogenesis in the gekkotan lizard Eublepharis macularius , the leopard gecko. Gekkotans are estimated to have diverged from lacertids ~200 million years ago. Treatment with the antimetabolite 3‐acetylpyridine (3AP) resulted in extensive neuronal loss within the cellular layer of the medial cortex, the presumptive homologue of the mammalian hippocampus. Four days following 3‐AP administration, there was widespread evidence of TUNEL+ nuclei indicating cell death. Compared to untreated controls, the average loss of neurons across the medial cortex at four days post‐treatment was 15.3% (range: 4.6‐22.7%). Degenerative changes were matched by a marked increase in cell proliferation throughout the ventricular zone. Within 30 days, the medial cortex no longer showed evidence of cell death, and the distribution of proliferating cells had returned to baseline. Further, areas of the medial cortex damaged by 3‐AP had become repopulated by NeuN+ neurons. Taken together, these findings indicate that the capacity for injury‐mediated neurogenesis may be an evolutionarily conserved phenomenon among lizards, and that geckos represents a valuable research model for future studies of adult neurogenesis.
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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) | 0.001 | 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".