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Record W2024215142 · doi:10.1126/sageke.2005.5.re1

Lipofuscin and Aging: A Matter of Toxic Waste

2005· review· en· W2024215142 on OpenAlexaff
Douglas A. Gray, John Woulfe

Bibliographic record

VenueScience of Aging Knowledge Environment · 2005
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsLipofuscinCell biologyLysosomeProgrammed cell deathCellMitochondrionChemistryBiologyNeuroscienceBiochemistryApoptosis

Abstract

fetched live from OpenAlex

Lipofuscin is membrane-bound cellular waste that can be neither degraded nor ejected from the cell but can only be diluted through cell division and subsequent growth. The fate of postmitotic cells is to accumulate lipofuscin, which as an "aging pigment" has been considered a reliable biomarker for the age of cells such as neurons and, by extension, their hosts. In the aging human brain, deposits of lipofuscin are not uniformly distributed but are concentrated in specific regions of functional interest. The prevailing thought is that the major source of lipofuscin is incomplete lysosomal degradation of damaged mitochondria. Accumulating evidence suggests that lipofuscin is not benign but can impair the functioning of seemingly unrelated cellular systems, including the ubiquitin/proteasome pathway. A damaging feedback loop of lysosomal and proteasomal inhibition may occur as lipofuscin accumulates, leading to what has been appropriately named a "garbage catastrophe." Reversing this catastrophe presents a formidable challenge.

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 score0.003
Threshold uncertainty score0.011

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 studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.002
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 head0.027
GPT teacher head0.328
Teacher spread0.301 · 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

Citations286
Published2005
Admission routes1
Has abstractyes

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