Sorting Nexin 27 regulates basal and activity-dependent trafficking of AMPARs
Bibliographic record
Abstract
Activity-dependent changes in synaptic strength have long been postulated as cellular correlates of learning and memory. Long-term potentiation (LTP), a well characterized form of synaptic plasticity, is often expressed as an increase in the number of postsynaptic AMPA-type glutamate receptors (AMPARs). Although the precise molecular mechanisms governing LTP remain elusive, this study identifies one member of the sorting nexin family, Sorting Nexin 27 (SNX27), as a critical component in this process. The ability of sorting nexins to bind specific phospholipids as well as their propensity to form protein-protein complexes, points to a role for these proteins in membrane trafficking and protein sorting. Here, we demonstrate that SNX27 binds to AMPARs, and that this interaction is regulated in an activity-dependent manner. Furthermore, we provide evidence that SNX27 is synaptically enriched and its level of expression regulates targeting of AMPARs to the neuronal surface. Loss of SNX27 abolishes recruitment of surface AMPARs during chemical LTP. Collectively, our data suggest a role for SNX27 in modulating synaptic plasticity through regulated interaction with AMPARs.
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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".