Preconditioning induces tolerance by suppressing glutamate release in neuron culture ischemia models
Bibliographic record
Abstract
This study determined how preconditioned neurons responded to oxygen-glucose deprivation (OGD) to result in neuroprotection instead of neurotoxicity. Neurons preconditioned using chronically elevated synaptic activity displayed suppressed elevations in extracellular glutamate ([glutamateex ]) and intracellular Ca(2+) (Ca(2+) in ) during OGD. The glutamate uptake inhibitor TBOA induced neurotoxicity, but at a longer OGD duration for preconditioned cultures, suggestive of delayed up-regulation of transporter activity relative to non-preconditioned cultures. This delay was attributed to a critically attenuated release of glutamate, based on tolerance observed against insults mimicking key neurotoxic signaling during OGD (OGD-mimetics). Specifically, in the presence of TBOA, preconditioned neurons displayed potent protection to the OGD-mimetics: ouabain (a Na(+) /K(+) ATPase inhibitor), high 55 mM KCl extracellular buffer (plasma membrane depolarization), veratridine (a Na(+) ionophore), and paraquat (intracellular superoxide producer), which correlated with suppressed [glutamateex ] elevations in the former two insults. Tolerance by preconditioning was reversed by manipulations that increased [glutamateex ], such as by exposure to TBOA or GABAA receptor agonists during OGD, or by exposure to exogenous NMDA or glutamate. Pre-synaptic suppression of neuronal glutamate release by preconditioning, possibly via suppressed exocytic release, represents a key convergence point in neuroprotection during exposure to OGD and OGD-mimetics.
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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) | 0.001 | 0.001 |
| 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".