MétaCan
Menu
Back to cohort
Record W2161879858 · doi:10.1186/2045-9912-1-2

Moderately delayed post-insult treatment with normobaric hyperoxia reduces excitotoxin-induced neuronal degeneration but increases ischemia-induced brain damage

2011· article· en· W2161879858 on OpenAlexaff
Benoît Haelewyn, Laurent Chazalviel, Olivier Nicole, Myriam Lecocq, Jean‐Jacques Risso, Jacques H. Abraini

Bibliographic record

VenueMedical Gas Research · 2011
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversité Laval
FundersCentre National de la Recherche Scientifique
KeywordsIschemiaMedicineNeuroprotectionStroke (engine)In vivoNMDA receptorBrain damageNeuroscienceDegeneration (medical)NeurodegenerationBrain ischemiaHyperoxiaExcitotoxicityAnesthesiaCardiologyPathologyPharmacologyInternal medicineBiologyDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The use and benefits of normobaric oxygen (NBO) in patients suffering acute ischemic stroke is still controversial. RESULTS: Here we show for the first time to the best of our knowledge that NBO reduces both NMDA-induced calcium influxes in vitro and NMDA-induced neuronal degeneration in vivo, but increases oxygen and glucose deprivation-induced cell injury in vitro and ischemia-induced brain damage produced by middle cerebral artery occlusion in vivo. CONCLUSIONS: Taken together, these results indicate that NBO reduces excitotoxin-induced calcium influx and subsequent neuronal degeneration but favors ischemia-induced brain damage and neuronal death. These findings highlight the complexity of the mechanisms involved by the use of NBO in patients suffering acute ischemic stroke.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.178
GPT teacher head0.346
Teacher spread0.168 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations22
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueMedical Gas ResearchSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207