Glutamate Increases In Vitro Survival and Proliferation and Attenuates Oxidative Stress-Induced Cell Death in Adult Spinal Cord-Derived Neural Stem/Progenitor Cells via Non-NMDA Ionotropic Glutamate Receptors
Bibliographic record
Abstract
Traumatic spinal cord injury (SCI) leads to a cascade of secondary chemical insults, including oxidative stress and glutamate excitotoxicity, which damage host neurons and glia. Transplantation of exogenous neural stem/progenitor cells (NSPCs) has shown promise in enhancing regeneration after SCI, although survival of transplanted cells remains poor. Understanding the response of NSPCs to the chemical mediators of secondary injury is essential in finding therapies to enhance survival. We examined the in vitro effects of glutamate and glutamate receptor agonists on adult rat spinal cord-derived NSPCs. NSPCs isolated from the periventricular region of the adult rat spinal cord were exposed to various concentrations of glutamate for 96 h. We found that glutamate treatment (500 μM) for 96 h significantly increased live cell numbers, reduced cell death, and increased proliferation, but did not significantly alter cell phenotype. Concurrent glutamate treatment (500 μM) in the setting of H2O2 exposure (500 μM) for 10 h increased NSPC survival compared to H2O2 exposure alone. The effects of glutamate on NSPCs were blocked by the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)/kainate receptor antagonist GYKI-52466, but not by the N-methyl-D-aspartic acid receptor antagonist MK-801 or DL-AP5, or the mGluR3 antagonist LY-341495. Furthermore, treatment of NSPCs with AMPA, kainic acid, or the kainate receptor-specific agonist (RS)-2-amino-3-(3-hydroxy-5-tert-butylisoxazol-4-yl)propanoic acid mimicked the responses seen with glutamate both alone and in the setting of oxidative stress. These findings offer important insights into potential mechanisms to enhance NSPC survival and implicate a potential role for glutamate in promoting NSPC survival and proliferation after traumatic SCI.
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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".