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Different dynamic patterns of extracellular glutamate release in rat hippocampus after permanent or 30‐min transient cerebral ischemia and histological correlation

2001· article· en· W2020943683 on OpenAlexaff
Yi Yang, Li Qiu, Hero Miyashita, Tao Yang, Ashfaq Shuaib

Bibliographic record

VenueNeuropathology · 2001
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsRoyal University HospitalUniversity of Alberta
Fundersnot available
KeywordsGlutamate receptorMicrodialysisIschemiaExcitotoxicityHippocampusMedicineAnesthesiaExtracellularPharmacologyNeuroscienceInternal medicineBiologyCentral nervous systemBiochemistry

Abstract

fetched live from OpenAlex

The extent and severity of neuronal damage is different in ischemia with reperfusion compared to ischemia and no reperfusion. To investigate the role of glutamate in cerebral ischemia-reperfusion injury, in vivo microdialysis was performed to examine the dynamic profile of glutamate in the hippocampus in a transient (30 min) or permanent middle cerebral artery occlusion (MCAo) in Wistar rats. The extracellular concentration of glutamate in the cornu ammonis (CA)1 sector of the ipsilateral hippocampus showed a significant but transient elevation of glutamate for both groups immediately following ischemic insult. The initial high peak in glutamate levels in the transient MCAo group was followed by two secondary elevations in glutamate at 50 min and 90 min after initialization of reperfusion. The histopathological outcome was also different in the two groups. The observation that glutamate releases occurred in the early reperfusion phase provided an evidence of additional excitotoxicity of glutamate and thereby a therapeutic base for extended use of glutamate antagonist in the ischemia-reperfusion injury.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.025
GPT teacher head0.291
Teacher spread0.266 · 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 designObservational
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

Citations44
Published2001
Admission routes1
Has abstractyes

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