Glycine Promotes the Survival of a Subpopulation of Neural Stem Cells
Bibliographic record
Abstract
Glycine is mainly known as an inhibitory neurotransmitter in adult mature neurons, regulating neuronal network activity in the central nervous system. In contrast, during embryogenesis glycine can act as an excitatory neurotransmitter and generates the first electrical signal in immature neurons. The roles and functional significance of this excitatory glycinergic activity during neurodevelopment are still unclear. Using the zebrafish embryo as a model, we previously showed that glycine regulates proliferation and differentiation of neural stem cells (NSCs) to interneurons. Moreover, we identified that glycine signaling in NSCs is associated with several common developmental pathways and surprisingly also the p53-related apoptosis. Here we investigated how glycine signaling regulates NSC survival. First, we showed by two approaches, acridine orange staining and active caspase 3 immunostaining that defects in glycine signaling induce an early and transient cell death, which was suppressed by knockdown of p53. Then, we developed an NSC transplantation strategy to directly assess NSC-autonomous development upon perturbing glycine signaling. In vivo time-lapse imaging showed that disruption of glycine signaling disturbed the normal NSC interkinetic nuclear migration, leading to cell cycle arrest and apoptosis. Finally, we analyzed two main subpopulations of NSCs, expressing either nestin or GFAP, by in situ labeling and in transgenic lines expressing GFP in either population. We found that disruption of glycine signaling induced a drastic and selective loss of nestin-positive (nestin+) NSCs, which was only partially rescued upon p53 knockdown. Taken together, our findings support a role of glycine signaling in promoting survival of the nestin+ NSC subpopulation early during development.
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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".