P.089 AMPA receptor modulation as a therapeutic strategy to enhance survival of spinal cord neural stem cells
Bibliographic record
Abstract
Background: Transplantation of neural stem/progenitor cells (NSPCs) following spinal cord injury (SCI) is a promising strategy to enhance regeneration but is limited by poor survival of grafted cells. Recently, we demonstrated for the first time that the excitatory neurotransmitter glutamate, which is released after SCI, promotes survival/proliferation of spinal cord NSPCs via the AMPA subtype of glutamate receptors. Here, we examine the therapeutic potential of selective AMPA receptor modulation on NSPC survival using allosteric AMPA receptor modulators known as ampakines. Methods: NSPCs from the periventricular region of the adult rat spinal cord were treated with ampakines CX614 and CX546 for 72h either alone or in the presence of low-dose glutamate (50uM). Results: Treatment with CX-546 or CX-614 in the presence of glutamate led to a significant increase in live cell numbers. This was due to both a reduction in cell death and increase in cellular proliferation. Ampakine/glutamate treatment led to a significant increase in cell survival compared to controls in the setting of oxidative stress. Conclusions: We present the first examination of the effect of allosteric AMPA receptor modulators on adult spinal cord--derived NSPCs. Positive modulation of AMPA receptors may be a promising therapeutic strategy in the subacute/chronic phases after SCI to increase survival of endogenous or transplanted NSPCs.
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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) | 0.007 | 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".