RGMa and Neogenin control dendritic spine morphogenesis via WAVE Regulatory Complex-mediated actin remodeling
Bibliographic record
Abstract
Structural plasticity, the ability of dendritic spines to change their volume in response to synaptic stimulation, is an essential determinant of synaptic strength and long-term potentiation (LTP), the proposed cellular substrate for learning and memory. Branched actin polymerization is a major force driving spine enlargement and sustains structural plasticity. The WAVE Regulatory Complex (WRC), a pivotal branched actin regulator, controls spine morphology and therefore structural plasticity. However, the molecular mechanisms that govern WRC activation during spine enlargement are largely unknown. Here we identify a critical role for Neogenin and its ligand RGMa (Repulsive Guidance Molecule a) in promoting spine enlargement through the activation of WRC-mediated branched actin remodeling. We demonstrate that Neogenin regulates WRC activity by binding to the highly conserved Cyfip/Abi binding pocket within the WRC. We find that after Neogenin or RGMa depletion, the proportions of filopodia and immature thin spines are dramatically increased, and the number of mature mushroom spines concomitantly decreased. Wildtype Neogenin, but not Neogenin bearing mutations in the Cyfip/Abi binding motif, is able to rescue the spine enlargement defect. Furthermore, Neogenin depletion inhibits actin polymerization in the spine head, an effect that is not restored by the mutant. We conclude that RGMa and Neogenin are critical modulators of WRC-mediated branched actin polymerization promoting spine enlargement. This study also provides mechanistic insight into Neogenin's emerging role in LTP induction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".