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Record W2600396554 · doi:10.1038/cdd.2017.37

Evolution of caspase-mediated cell death and differentiation: twins separated at birth

2017· review· en· W2600396554 on OpenAlexafffund
Ryan A. V. Bell, Lynn A. Megeney

Bibliographic record

VenueCell Death and Differentiation · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchMuscular Dystrophy AssociationHeart and Stroke Foundation of Canada
KeywordsCaspaseProgrammed cell deathBiologyProteostasisCell biologyCaspase 2ApoptosisCellular differentiationGeneticsGene

Abstract

fetched live from OpenAlex

The phenotypic and biochemical similarities between caspase-mediated apoptosis and cellular differentiation are striking. They include such diverse phenomenon as mitochondrial membrane perturbations, cytoskeletal rearrangements and DNA fragmentation. The parallels between the two disparate processes suggest some common ancestry and highlight the paradoxical nature of the death-centric view of caspases. That is, what is the driving selective pressure that sustains death-inducing proteins throughout eukaryotic evolution? Plausibly, caspase function may be rooted in a primordial non-death function, such as cell differentiation, and was co-opted for its role in programmed cell death. This review will delve into the links between caspase-mediated apoptosis and cell differentiation and examine the distinguishing features of these events. More critically, we chronicle the evolutionary origins of caspases and propose that caspases may have held an ancient role in mediating the fidelity of cell division/differentiation through its effects on proteostasis and protein quality control.

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
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.273
Teacher spread0.245 · 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

Citations139
Published2017
Admission routes2
Has abstractyes

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