KCC2 antagonism increases neuronal network excitability but disrupts ictogenesis in vitro
Bibliographic record
Abstract
The potassium-chloride cotransporter 2 (KCC2) plays a role in epileptiform synchronization, but it remains unclear how it influences such a process. Here, we used tetrode recordings in the in vitro rat entorhinal cortex (EC) to analyze the effects of the KCC2 antagonist VU0463271 on 4-aminopyridine (4AP)-induced ictal and interictal activity. During 4AP application, ictal events were associated with significant increases in interneurons and principal cells activities. VU0463271 application transformed ictal discharges to shorter ictal-like events that were not accompanied by significant increases in interneuron or principal cell firing. Interictal events persisted during VU0463271 application at an accelerated frequency of occurrence with significant increases in interneuron and principal cell activity. Further analysis revealed that interneuron and principal cell firing rate during 4AP-induced interictal events were increased after VU0463271 application without changes in synchronicity. Overall, our results demonstrate that in the EC, KCC2 antagonism enhances both interneuron and principal cell excitability, while paradoxically decreasing the ability of neuronal networks to generate structured ictal events. NEW & NOTEWORTHY We are the first to use tetrode recordings in the entorhinal cortex to demonstrate that antagonizing potassium-chloride cotransporter 2 (KCC2) function abolishes ictal discharges and the associated, dynamic changes in single-unit firing in the in vitro 4-aminopyrine model of epileptiform synchronization. Interictal discharges were, however, shorter and more frequent during KCC2 antagonism, while the associated single-unit activity increased, suggesting augmented neuronal excitability. Our findings highlight the complex role of KCC2 in disease pathology.
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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) | 0.001 | 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".