Disrupting GluA2-GAPDH Interaction Affects Axon and Dendrite Development
Bibliographic record
Abstract
GluA2-containing AMPA receptors (AMPARs) play a critical role in various aspects of neurodevelopment. However, the molecular mechanisms underlying these processes are largely unknown. We report here that the interaction between GluA2 and glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is necessary for neuron and cortical development. Using an interfering peptide (GluA2-G-Gpep) that specifically disrupts this interaction, we found that primary neuron cultures with peptide treatment displayed growth cone development deficits, impairment of axon formation, less dendritic arborization and lower spine protrusion density. Consistently, in vivo data with mouse brains from pregnant dams injected with GluA2-G-Gpep daily during embryonic day 8 to 19 revealed a reduction of cortical tract axon integrity and neuronal density in post-natal day 1 offspring. Disruption of GluA2-GAPDH interaction also impairs the GluA2-Plexin A4 interaction and reduces p53 acetylation in mice, both of which are possible mechanisms leading to the observed neurodevelopmental abnormalities. Furthermore, electrophysiological experiments indicate altered long-term potentiation (LTP) in hippocampal slices of offspring mice. Our results provide novel evidence that AMPARs, specifically the GluA2 subunit via its interaction with GAPDH, play a critical role in cortical neurodevelopment.
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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".