Neuroprotective effects of xenon: a therapeutic window of opportunity in rats subjected to transient cerebral ischemia
Bibliographic record
Abstract
Brain insults are a major cause of acute mortality and chronic morbidity. Given the largely ineffective current therapeutic strategies, the development of new and efficient therapeutic interventions is clearly needed. A series of previous investigations has shown that the noble and anesthetic gas xenon, which has low-affinity antagonistic properties at the N-methyl-D-aspartate (NMDA) receptor, also exhibits potentially neuroprotective properties with no proven adverse side effects. Surprisingly and in contrast with most drugs that are being developed as therapeutic agents, the dose-response neuroprotective effect of xenon has been poorly studied, although this effect could be of major critical importance for its clinical development as a neuroprotectant. Here we show, using ex vivo and in vivo models of excitotoxic insults and transient brain ischemia, that xenon, administered at subanesthetic doses, offers global neuroprotection from reduction of neurotransmitter release induced by ischemia, a critical event known to be involved in excitotoxicity, to reduction of subsequent cell injury and neuronal death. Maximal neuroprotection was obtained with xenon at 50 vol%, a concentration at which xenon further exhibited significant neuroprotective effects in vivo even when administered up to 4 h after intrastriatal NMDA injection and up to at least 2 h after induction of transient brain ischemia.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".