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Record W2135732283 · doi:10.1139/h07-098

Role of nuclear factor κB and mitogen-activated protein kinase signaling in exercise-induced antioxidant enzyme adaptation

2007· review· en· W2135732283 on OpenAlexvenueno aff
Li Li Ji, Mari Carmen Gómez‐Cabrera, José Viña

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2007
Typereview
Languageen
FieldMedicine
TopicExercise and Physiological Responses
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)Cell biologyProtein kinase AEnzymeAntioxidantKinaseSignal transductionMitogen-activated protein kinaseChemistryBiologyBiochemistryNeuroscience

Abstract

fetched live from OpenAlex

Activation of nuclear factor (NF) kappaB and mitogen-activated protein kinase (MAPK) pathways in skeletal muscle has been shown to enhance the gene expression of several enzymes that play an important role in maintaining oxidant-antioxidant homeostasis, such as mitochondrial superoxide dismutase (MnSOD) and inducible nitric oxide synthase (iNOS). While an acute bout of exercise activates NF kappaB and MAPK signaling and upregulates MnSOD and iNOS, administration of chemical agents that suppress reactive oxygen species (ROS) production can cause attenuation of exercise-induced MnSOD and iNOS expression. Thus, ROS generation during exercise may have duel effects: the infliction of oxidative stress and damage, and the stimulation of adaptive responses favoring long-term protection. This scenario explains why animals and humans involved in exercise training have demonstrated increased resistance to oxidative damage under a wide range of physiological and pathological stresses.

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 score0.011

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.004

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 head0.051
GPT teacher head0.314
Teacher spread0.263 · 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

Citations71
Published2007
Admission routes1
Has abstractyes

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