Deletion of the NMDA Receptor GluN2A Subunit Significantly Decreases Dendritic Growth in Maturing Dentate Granule Neurons
Bibliographic record
Abstract
It is known that NMDA receptors can modulate adult hippocampal neurogenesis, but the contribution of specific regulatory GluN2 subunits has been difficult to determine. Here we demonstrate that mice lacking GluN2A (formerly NR2A) do not show altered cell proliferation or neuronal differentiation, but present significant changes in neuronal morphology in dentate granule cells. Specifically, GluN2A deletion significantly decreased total dendritic length and dendritic complexity in DG neurons located in the inner granular zone. Furthermore, the absence of GluN2A also resulted in a localized increase in spine density in the middle molecular layer, a region innervated by the medial perforant path. Interestingly, alterations in dendritic morphology and spine density were never seen in dentate granule cells located in the outer granular zone, a region that has been hypothesized to contain older, more mature, neurons. These results indicate that although the GluN2A subunit is not critical for the cell proliferation and differentiation stages of the neurogenic process, it does appear to play a role in establishing synaptic and dendritic morphology in maturing dentate granule cells localized in the inner granular zone.
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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) | 0.001 | 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".