Adult axolotls can regenerate original neuronal diversity in response to brain injury
Bibliographic record
Abstract
The axolotl can regenerate multiple organs, including the brain. It remains, however, unclear whether neuronal diversity, intricate tissue architecture, and axonal connectivity can be regenerated; yet, this is critical for recovery of function and a central aim of cell replacement strategies in the mammalian central nervous system. Here, we demonstrate that, upon mechanical injury to the adult pallium, axolotls can regenerate several of the populations of neurons present before injury. Notably, regenerated neurons acquire functional electrophysiological traits and respond appropriately to afferent inputs. Despite the ability to regenerate specific, molecularly-defined neuronal subtypes, we also uncovered previously unappreciated limitations by showing that newborn neurons organize within altered tissue architecture and fail to re-establish the long-distance axonal tracts and circuit physiology present before injury. The data provide a direct demonstration that diverse, electrophysiologically functional neurons can be regenerated in axolotls, but challenge prior assumptions of functional brain repair in regenerative species.
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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".