Tectal stem cells display diverse regenerative capacities
Bibliographic record
Abstract
Abstract How diverse adult stem and progenitor populations regenerate tissue following damage to the CNS remains unknown across most neurogenic domains. To understand the role of quiescent radial-glial (qRG) stem cells during regeneration, we tested the hypothesis that qRG could be induced to proliferate and produce newborn neurons. We designed a stab lesion assay in the midbrain tectum of the adult zebrafish to target an isolated population of qRG, and investigated their proliferative behaviour, differentiation potential, and requirement of Wnt/β-catenin signalling for the regenerative response. EdU-labelling showed that a small proportion of qRG transit to a proliferative state (pRG), but that progeny of pRG are restricted to a radial-glial fate. Lesion promoted upregulation of proliferation and neurogenesis from neuro-epithelial-like amplifying progenitors (NE-Ap) of the tectal marginal zone (TMZ). Homeostatic levels of Wnt/β-catenin signalling persisted under lesioned conditions in the qRG/pRG population, whereby increased β-catenin staining and axin2 expression was present in the NE-Ap progenitor zone. Attenuation of Wnt signalling using Dickkopf-1 , demonstrated that proliferative responses post-injury appeared to be Wnt-independent. Our results align with the emerging view that adult stem/progenitor phenotypes are characterized by discrete, rather than mutual, regenerative programs and that different stem cell domains employ different modes of regeneration.
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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".