Glutamate and Regulation of Proliferation in the Developing Mammalian Telencephalon
Bibliographic record
Abstract
Increasing evidence suggests that classical neurotransmitters play an important morphogenetic role during development of the mammalian central nervous system. Using in vitro and in vivo models, we have previously identified a role for the N-methyl-D-aspartate (NMDA) subclass of glutamate receptors in the proliferation of striatal progenitors. Here, we compare the roles of ionotropic glutamate receptors in the proliferation of either striatal or cortical progenitors. In culture, glutamate receptor activation promoted proliferation of both striatal and cortical neuroblasts. However, cortical and striatal neuroblasts responded to distinct ionotropic receptors. Cortical cultures were sensitive to AMPA/KA receptor blockade, whereas striatal neuroblast proliferation was altered by NMDA antagonists. In vivo, BrdU uptake in the proliferative ventricular zone was reduced in embryos following acute administration of ionotropic glutamate receptor antagonists. In keeping with in vitro observations, proliferation in cortical and striatal ventricular regions was reduced, respectively, by either AMPA/KA or NMDA receptor blockade. We also determined whether forebrain-derived progenitors expanded as neurospheres in the presence of growth factors show similar ionotropic glutamatergic responses. Cells in neither dorsal nor ventral telencephalon-derived neurospheres showed altered proliferation following exposure to either class of ionotropic glutamate receptor antagonist. Together, these findings suggest that glutamate influences the proliferation of forebrain neuronal progenitors, but not more primitive populations represented in multipotential progenitors expanded in vitro. The effects on neuroblast proliferation in different forebrain domains are heterogeneous and are mediated by distinct subclasses of ionotropic glutamate receptors.
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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".