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Implications of Protein Degradation in Aging

2001· review· en· W2076830701 on OpenAlexfundno aff
Sataro Goto, Ryoya Takahashi, Atsushi Kumiyama, Zsolt Radák, Toshiaki Hayashi, Masaki Takenouchi, Ryoichi Abe

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2001
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsnot available
FundersMagyar Tudományos AkadémiaJapan Foundation for Aging and HealthAGE-WELL
KeywordsProtein turnoverProteasomeProtein degradationOrganismTurnoverDegradation (telecommunications)AgeingCell biologyPhysiologyBiologyChemistryBiochemistryProtein biosynthesisGenetics

Abstract

fetched live from OpenAlex

Aging is characterized by accumulation of potentially harmful altered proteins that could lead to gradual deterioration of cellular functions and eventually result in increased probability of death. Metabolic turnover of proteins thus plays an essential role in maintaining the life of an organism. In this article we summarize our current knowledge on age-related changes in protein turnover with special reference to degradation. Increase in half-life of proteins with advancing age is well documented. Qualitative rather than quantitative changes of proteasomes appear to be responsible for this change. Dietary restriction and moderate long-term exercise seem to restore higher proteasome activity and turnover rate of proteins in aged animals.

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)0.001
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.143
GPT teacher head0.394
Teacher spread0.250 · 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

Citations83
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicMuscle metabolism and nutritionFrench-language works237,207