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Redox Regulation of Nuclear Factor Kappa B: Therapeutic Potential for Attenuating Inflammatory Responses

2000· review· en· W2085612389 on OpenAlexaff
John W. Christman, Timothy S. Blackwell, B. H. J. Juurlink

Bibliographic record

VenueBrain Pathology · 2000
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsUniversity of Saskatchewan
FundersNational Heart, Lung, and Blood Institute
KeywordsTranscription factorReactive oxygen speciesOxidative stressNFKB1Lipid peroxidationNF-κBEndogenyCell biologyChemistryEnzymeKEAP1Signal transductionInflammationBiochemistryBiologyImmunologyGene

Abstract

fetched live from OpenAlex

Nuclear factor kappa B (NF-kappaB) is a protein transcription factor that is required for maximal transcription of a wide array of pro-inflammatory mediators that are involved in the pathogenesis of stroke. The purpose of this review article is to describe what is known about the molecular biology of NF NF-kappaB and to review current understanding of the interaction between reactive oxygen species (ROS) in NF-kappaB. ROS seem to play a duel role by participating in the NF-kappaB activation cascade and by directly modulating DNA binding affinity. Exogenous and endogenous antioxidants are effective in blocking activation of NF-kappaB and preventing the consequences of pro-inflammatory gene expression. Phase II enzymes either directly or indirectly play a major in vivo role in minimizing oxidative stress by scavenging peroxides, peroxide breakdown products and dicarbonyls and in regeneration of lipid peroxidation chain-breaker, vitamin E. Dietary phase II enzyme inducers have been demonstrated to increase phase II enzyme activities in a variety of tissues. These data, together, suggest that phase II enzyme inducers could have therapeutic value for ameliorating inflammatory conditions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.027
GPT teacher head0.309
Teacher spread0.281 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations147
Published2000
Admission routes1
Has abstractyes

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