Enhanced Vulnerability to NMDA Toxicity in Sublethal Traumatic Neuronal Injury <i>In Vitro</i>
Bibliographic record
Abstract
Traumatic brain injury causes neuronal disruption and triggers secondary events leading to additional neuronal death. To study injuries triggered by secondary events, we exposed cultured cortical neurons to sublethal mechanical stretch, thus eliminating confounding death from primary trauma. Sublethally stretched neurons maintained cell membrane integrity, viability, and electrophysiological function. However, stretching induced in the cells a heightened vulnerability to subsequent challenges with L-glutamate or NMDA. This heightened vulnerability was specifically mediated by NMDA receptors (NMDARs), as stretched neurons did not become more vulnerable to either kainate toxicity or to that induced by the Ca(2+) ionophore A23187. Stretch-enhanced vulnerability to NMDA occurred independently of endogenous glutamate release, but required Ca(2+) and Na(+) influx through NMDARs. Stretch did not affect the electrophysiological properties of NMDARs nor excitatory synaptic activity, indicating that specificity of enhanced vulnerability to NMDA involves postsynaptic mechanisms downstream from NMDARs. To test whether this specificity requires physical interactions between NMDARs and cytoskeletal elements, we perturbed actin filaments and microtubules, both of which are linked to NMDARs. This had no effect on the stretch-induced vulnerability to NMDA, suggesting that sublethal stretch does not affect cell survival through the cytoskeleton. Our data illustrate that sublethal in vitro stretch injury triggers distinct signaling pathways that lead to secondary injury, rather than causing a generalized increase in vulnerability to secondary insults.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".