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Record W2159351939 · doi:10.1155/2011/689524

Activation of Nrf2-Regulated Glutathione Pathway Genes by Ischemic Preconditioning

2011· article· en· W2159351939 on OpenAlexfundno aff
Karen Bell, Jill H. Fowler, Bashayer Al‐Mubarak, Karen Horsburgh, Giles E. Hardingham

Bibliographic record

VenueOxidative Medicine and Cellular Longevity · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilCanadian Institutes of Health ResearchTenovusMedical Research ScotlandAlzheimer's SocietyWellcome Trust
KeywordsNeuroprotectionGlutathioneEndogenyOxidative stressIn vivoTranscription factorPharmacologyMediatorCell biologyIschemiaIschemic preconditioningBiologyChemistryGeneBiochemistryMedicineEnzymeGeneticsInternal medicine

Abstract

fetched live from OpenAlex

Prophylactic pharmacological activation of astrocytic gene expression driven by the transcription factor Nrf2 boosts antioxidant defences and protects against neuronal loss in ischemia and other disease models. However, the role of Nrf2 in mediating endogenous neuroprotective responses is less clear. We recently showed that Nrf2 is activated by mild oxidative stress in both rodent and human astrocytes. Moreover, brief exposure to ischemic conditions was found to activate Nrf2 both in vivo and in vitro, and this was found to contribute to neuroprotective ischemic preconditioning. Here we show that transient ischemic conditions in vitro and in vivo cause an increase in the expression of Nrf2 target genes associated with the glutathione pathway, including those involved in glutathione biosynthesis and cystine uptake. Taken together, these studies indicate that astrocytic Nrf2 may represent an important mediator of endogenous neuroprotective preconditioning pathways.

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 score0.005

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)0.0020.000

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 head0.021
GPT teacher head0.228
Teacher spread0.207 · 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

Citations81
Published2011
Admission routes1
Has abstractyes

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