NETO1 Regulates Postsynaptic Kainate Receptors in CA3 Interneurons During Circuit Maturation
Bibliographic record
Abstract
Kainate type ionotropic glutamate receptors (KARs) are expressed in hippocampal interneurons and regulate interneuron excitability and GABAergic transmission. Neuropilin tolloid-like proteins (NETO1 and NETO2) act as KAR auxiliary subunits; however, their significance for various functions of KARs in GABAergic interneurons is not fully understood. Here we show that NETO1, but not NETO2, is necessary for dendritic delivery of KAR subunits and, consequently, for formation of KAR-containing synapses in cultured GABAergic neurons. Accordingly, electrophysiological analysis of neonatal CA3 stratum radiatum interneurons revealed impaired postsynaptic and metabotropic KAR signaling in Neto1 knockouts, while a subpopulation of ionotropic KARs in the somatodendritic compartment remained functional. Loss of NETO1/KAR signaling had no significant effect on development of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-D-aspartate (NMDA)-receptor-mediated glutamatergic transmission in CA3 interneurons, contrasting the synaptogenic role proposed for KARs in principal cells. Furthermore, loss of NETO1 had no effect on excitability and characteristic spontaneous network bursts in the immature CA3 circuitry. However, we find that NETO1 is critical for kainate-dependent modulation of network bursts and GABAergic transmission in the hippocampus already during the first week of life. Our results provide the first description of NETO1-dependent subcellular targeting of KAR subunits in GABAergic neurons and indicate that endogenous NETO1 is required for formation of KAR-containing synapses in interneurons. Since aberrant KAR-mediated excitability is implicated in certain forms of epilepsy, NETO1 represents a potential therapeutic target for treatment of both adult and early life seizures.
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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".