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Record W3094189501 · doi:10.1530/jme-20-0196

Aging, senescence and mitochondria: the PGC-1/ERR axis

2020· review· en· W3094189501 on OpenAlexafffund
Mathieu Vernier, Vincent Giguère

Bibliographic record

VenueJournal of Molecular Endocrinology · 2020
Typereview
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsMcGill University
FundersTerry Fox Research InstituteCanadian Institutes of Health ResearchFondation du cancer du sein du Québec
KeywordsMitochondrionSenescenceContext (archaeology)Cell biologyBiologyRegulatorReceptorNuclear receptorNeuroscienceBioinformaticsGeneticsTranscription factorGene

Abstract

fetched live from OpenAlex

Aging is a degenerative process that results from the accumulation of cellular and tissue lesions, leading progressively to organ dysfunction and death. Although the biological basis of human aging remains unclear, a large amount of data points to deregulated mitochondrial function as a central regulator of this process. Mounting years of research on aging support the notion that the engendered age-related decline of mitochondria is associated with alterations in key pathways that regulate mitochondrial biology. Particularly, several studies in the last decade have emphasized the importance of the estrogen-related receptor (ERR) family of nuclear receptors, master regulators of mitochondrial function, and their transcriptional coactivators PGC-1s in this context. In this review, we summarize key discoveries implicating the PGC-1/ERR axis in age-associated mitochondrial deregulation and tissue dysfunction. Also, we highlight the pharmacological potential of targeting the PGC-1/ERR axis to alleviate the onset of aging and its adverse effects.

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 score0.004
Threshold uncertainty score0.013

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 integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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

Citations48
Published2020
Admission routes2
Has abstractyes

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