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Peroxisome Metabolism and Cellular Aging

2010· review· en· W1981972734 on OpenAlexafffund
Vladimir I. Titorenko, Stanley R. Terlecky

Bibliographic record

VenueTraffic · 2010
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsConcordia University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCanadian Institutes of Health ResearchNational Institutes of HealthConcordia University
KeywordsPeroxisomeBiologyOrganelleBiogenesisCell biologyCellular compartmentMetabolismFunction (biology)Reactive oxygen speciesOrganelle biogenesisFlux (metallurgy)Cell metabolismMitochondrionBiochemistryCellReceptorChemistryGene

Abstract

fetched live from OpenAlex

The essential role of peroxisomes in fatty acid oxidation, anaplerotic metabolism, and hydrogen peroxide turnover is well established. Recent findings suggest that these and other related biochemical processes governed by the organelle may also play a critical role in regulating cellular aging. The goal of this review is to summarize and integrate into a model the evidence that peroxisome metabolism actually helps define the replicative and chronological age of a eukaryotic cell. In this model, peroxisomal reactive oxygen species (ROS) are seen as altering organelle biogenesis and function, and eliciting changes in the dynamic communication networks that exist between peroxisomes and other cellular compartments. At low levels, peroxisomal ROS activate an anti-aging program in the cell; at concentrations beyond a specific threshold, a pro-aging course is triggered.

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
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.277
Teacher spread0.260 · 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

Citations160
Published2010
Admission routes2
Has abstractyes

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