Trkb receptor activation alleviates early seizure-induced dysfunction of hippocampal fast-spiking interneurons
Bibliographic record
Abstract
Early life seizures (ELS) are often refractory to conventional anticonvulsant treatments, and can result in later life epilepsy and severe cognitive deficits. Our recent study demonstrated that ELS acutely reduced the excitatory synaptic inputs onto hippocampal fast-spiking (FS) interneurons through affecting presynaptic neurotransmitter release, which plays a crucial role in ELS pathophysiology. Thus, enhancing excitatory synaptic afferents onto FS interneurons will represent a logical approach to normalize the function of FS interneurons in ELS. BDNF regulates excitatory circuit development in FS interneurons through TrkB receptors. Therefore, we hypothesize that activation of TrkB receptors will alleviate ELS-induced dysfunction of excitatory afferents onto hippocampal FS interneurons. ELS were induced in P10-12 mice. We found that activation of TrkB receptors using a partial TrkB receptor agonist, LM22A-4, significantly increased the frequency of AMPA receptor mediated sEPSCs, but not sEPSC amplitude in CA1 FS interneurons in slices from 1 hour post-ELS mice, through increasing the probability of neurotransmitter release as evidenced by increased paired pulse ratio of evoked AMPAR EPSCs. Furthermore, LM22A-4's effects were abolished by co-administration of the TrkB receptor antagonist, ANA-12. These data strongly support a critical role of TrkB receptors in mediating ELS-induced dysregulation of hippocampal fast-spiking interneurons, and provide a potential therapeutic option for early life epilepsy.
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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) | 0.001 | 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) | 0.003 | 0.001 |
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".