Kainate receptor-mediated synaptic transmissions in the adult rodent insular cortex
Bibliographic record
Abstract
Kainate (KA) receptors are expressed widely in the central nervous system and regulate both excitatory and inhibitory synaptic transmission. KA receptors play important roles in fear memory, anxiety, and pain. However, little is known about their function in synaptic transmission in the insular cortex (IC), a critical region for taste, memory, and pain. Using whole cell patch-clamp recordings, we have shown that KA receptors contribute to fast synaptic transmission in neurons in all layers of the IC. In the presence of the GABA(A) receptor antagonist picrotoxin, the NMDA receptor antagonist AP-5, and the selective AMPA receptor antagonist GYKI 53655, KA receptor-mediated excitatory postsynaptic currents (KA EPSCs) were revealed. We found that KA EPSCs are ~5-10% of AMPA/KA EPSCs in all layers of the adult mouse IC. Similar results were found in adult rat IC. KA EPSCs had a significantly slower rise time course and decay time constant compared with AMPA receptor-mediated EPSCs. High-frequency repetitive stimulations at 200 Hz significantly facilitated the summation of KA EPSCs. In addition, genetic deletion of GluK1 or GluK2 subunit partially reduced postsynaptic KA EPSCs, and exposure of GluK2 knockout mice to the selective GluK1 antagonist UBP 302 could significantly reduce the KA EPSCs. These data suggest that both GluK1 and GluK2 play functional roles in the IC. Our study may provide the synaptic basis for the physiology and pathology of KA receptors in the IC-related functions.
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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 | 0.001 |
| 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".