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Record W1987613196 · doi:10.1089/ars.2010.3610

p53 Pro-Oxidant Activity in the Central Nervous System: Implication in Aging and Neurodegenerative Diseases

2010· review· en· W1987613196 on OpenAlexafffund
Wassim Chatoo, Mohamed Abdouh, Gilbert Bernier

Bibliographic record

VenueAntioxidants and Redox Signaling · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsDNA damageOxidative stressBiologySenescenceDNA repairContext (archaeology)NeuroscienceCell biologyNeurodegenerationApoptosisHomeostasisDNA Damage RepairCentral nervous systemProgrammed cell deathDNAGeneticsMedicineBiochemistryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

Recent advances in delineating the biological functions of p53 had shed the light on its key role in the multifacets of cellular homeostasis. After its activation, via DNA damage, oxidative stress, or aberrant expression of oncogenes, p53 transduces its classical effect through several mechanisms comprising activation of the DNA repair machinery, cell cycle arrest, and initiation of apoptosis or senescence. In the mammalian brain, p53 plays critical functions in normal development, tumor suppression, neurodegenerative diseases, and aging. Herein, we focus on the constitutive pro-oxidant activity of p53 in neurons and discuss the potential implication of this finding in the context of neurodegenerative diseases and normal brain aging.

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)0.001
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.020
GPT teacher head0.290
Teacher spread0.270 · 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

Citations42
Published2010
Admission routes2
Has abstractyes

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