Uncovering the spectrum of adult zebrafish neural stem cell cycle regulators
Bibliographic record
Abstract
Adult neural stem and progenitor cells (aNSPCs) persist lifelong in teleost models in diverse stem cell niches of the brain and spinal cord. Fish maintain developmental stem cell populations throughout life, including both neuro-epithelial cells (NECs) and radial-glial cells (RGCs). Within stem cell domains of the brain, RGCs persist in a cycling or quiescent state, whereas NECs continuously divide. Heterogeneous populations of RGCs also sit adjacent the central canal of the spinal cord, showing infrequent proliferative activity under homeostasis. With the rise of the zebrafish (Danio rerio) model to study adult neurogenesis and neuroregeneration in the central nervous system (CNS), it has become evident that aNSPC proliferation is regulated by a wealth of stimuli that may be coupled with biological function. Growing evidence suggests that aNSPCs are sensitive to environmental cues, social interactions, nutrient availability, and neurotrauma for example, and that distinct stem and progenitor cell populations alter their cell cycle activity accordingly. Such stimuli appear to act as triggers to either turn on normally dormant aNSPCs or modulate constitutive rates of niche-specific cell cycle behaviour. Defining the various forms of stimuli that influence RGC and NEC proliferation, and identifying the molecular regulators responsible, will strengthen our understanding of the connection between aNSPC activity and their biological significance. In this review, we aim to bring together the current state of knowledge on aNSPCs from studies investigating the zebrafish CNS, while highlighting emerging cell cycle regulators and outstanding questions that will help to advance this fascinating field of stem cell biology.
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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 | 0.001 |
| 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".