Neto Auxiliary Protein Interactions Regulate Kainate and NMDA Receptor Subunit Localization at Mossy Fiber–CA3 Pyramidal Cell Synapses
Bibliographic record
Abstract
Neto1 and Neto2 auxiliary subunits coassemble with NMDA receptors (NMDARs) and kainate receptors (KARs) to modulate their function. In the hippocampus, Neto1 enhances the amplitude and prolongs the kinetics of KAR-mediated currents at mossy fiber (MF)-CA3 pyramidal cell synapses. However, whether Neto1 trafficks KARs to synapses or simply alters channel properties is unresolved. Therefore, postembedding electron microscopy was performed to investigate the localization of GluK2/3 subunits at MF-CA3 synapses in Neto-null mice. Postsynaptic GluK2/3 Immunogold labeling was substantially reduced in Neto-null mice compared with wild types. Moreover, spontaneous KAR-mediated synaptic currents and metabotropic KAR signaling were absent in CA3 pyramidal cells of Neto-null mice. A similar loss of ionotropic and metabotropic KAR function was observed in Neto1, but not Neto2, single knock-out mice, specifically implicating Neto1 in regulating CA3 pyramidal cell KAR localization and function. Additional controversy pertains to the role of Neto proteins in modulating synaptic NMDARs. While Immunogold labeling for GluN2A at MF-CA3 synapses was comparable between wild-type and Neto-null mice, labeling for postsynaptic GluN2B was robustly increased in Neto-null mice. Accordingly, NMDAR-mediated currents at MF-CA3 synapses exhibited increased sensitivity to a GluN2B-selective antagonist in Neto1 knockouts relative to wild types. Thus, despite preservation of the overall MF-CA3 synaptic NMDAR-mediated current, loss of Neto1 alters NMDAR subunit composition. These results confirm that Neto protein interactions regulate synaptic localization of KAR and NMDAR subunits at MF-CA3 synapses, with implications for both ionotropic and metabotropic glutamatergic recruitment of the CA3 network.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".