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Free Radicals, Antioxidants, and Neurologic Injury: Possible Relationship to Cerebral Protection by Anesthetics

2002· review· en· W2082372926 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Neurosurgical Anesthesiology · 2002
Typereview
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineReactive oxygen speciesOxidative stressGlutamate receptorRadicalPharmacologyLipid peroxidationAntioxidantGlutamatergicFree-radical theory of agingAnesthesiaOxidative phosphorylationBiochemistryReceptorChemistryInternal medicine

Abstract

fetched live from OpenAlex

Oxygen-centered free radicals cause brain injury associated with trauma and stroke. These reactive oxygen species may be detoxified by endogenous antioxidants, but cell death occurs after antioxidants become depleted. General anesthetics penetrate into brain parenchyma, where they may abrogate oxidative injury to neurons by several mechanisms that prevent the initiation of free radical chain reactions or terminate the propagation of highly reactive radicals. First, general anesthetics may inhibit free radical generation because these drugs slow cerebral utilization of oxygen and glucose, inhibit oxidative metabolism in neutrophils, and prevent redox changes in hemoglobin. Second, antioxidant anesthetics, such as thiopental and propofol, directly scavenge reactive oxygen species and inhibit lipid peroxidation. Finally, anesthetics may prevent the elevation of extracellular glutamate concentration and inhibit the activation of excitatory glutamatergic receptors that augment oxidative stress after ischemia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.923
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.118
GPT teacher head0.338
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it