GSG1L suppresses AMPA receptor-mediated synaptic transmission and uniquely modulates AMPA receptor kinetics in hippocampal neurons
Bibliographic record
Abstract
Regulation of AMPA receptor (AMPAR)-mediated synaptic transmission is a key mechanism for synaptic plasticity. In the brain, AMPARs assemble with a number of auxiliary subunits, including TARPs, CNIHs and CKAMP44, which are important for AMPAR forward trafficking to synapses. Here we report that the membrane protein GSG1L negatively regulates AMPAR-mediated synaptic transmission. Overexpression of GSG1L strongly suppresses, and GSG1L knockout (KO) enhances, AMPAR-mediated synaptic transmission. GSG1L-dependent regulation of AMPAR synaptic transmission relies on the first extracellular loop domain and its carboxyl-terminus. GSG1L also speeds up AMPAR deactivation and desensitization in hippocampal CA1 neurons, in contrast to the effects of TARPs and CNIHs. Furthermore, GSG1L association with AMPARs inhibits CNIH2-induced slowing of the receptors in heterologous cells. Finally, GSG1L KO rats have deficits in LTP and show behavioural abnormalities in object recognition tests. These data demonstrate that GSG1L represents a new class of auxiliary subunit with distinct functional properties for AMPARs.
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 | 0.001 |
| 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".