Staufen 2 regulates mGluR long-term depression and Map1b mRNA distribution in hippocampal neurons
Bibliographic record
Abstract
The two members of the Staufen family of RNA-binding proteins, Stau1 and Stau2, are present in distinct ribonucleoprotein complexes and associate with different mRNAs. Stau1 is required for protein synthesis-dependent long-term potentiation (L-LTP) in hippocampal pyramidal cells. However, the role of Stau2 in synaptic plasticity remains unexplored. We found that unlike Stau1, Stau2 is not required for L-LTP. In contrast, Stau2, but not Stau1, is necessary for DHPG-induced protein synthesis-dependent long-term depression (mGluR-LTD). While Stau2 is involved in early development of spines, its down-regulation does not alter spine morphology or spontaneous miniature synaptic activity in older cultures where LTD occurs. In addition, Stau2, but not Stau1, knockdown reduces the dendritic localization of Map1b mRNA, a specific transcript involved in mGluR-LTD. Moreover, mGluR stimulation with DHPG induces Map1b, but not Map2, mRNA dissociation from mRNA granules containing Stau2 and the ribosomal protein P0. This dissociation was not observed in cells in which Stau2 was depleted. Finally, Stau2 knockdown reduces basal Map1b protein expression in dendrites and prevents DHPG-induced increases in dendritic Map1b protein level. We suggest a role for Stau2 in the generation and regulation of Map1b mRNA containing granules that are required for mGluR-LTD.
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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".