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Record W2090253955 · doi:10.1016/j.cub.2009.12.032

Cell-Nonautonomous Regulation of C. elegans Germ Cell Death by kri-1

2010· article· en· W2090253955 on OpenAlexafffund
Shu Ito, Sebastian Greiss, Anton Gartner, W. Brent Derry

Bibliographic record

VenueCurrent Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health ResearchCancer Research UKWellcome Trust
KeywordsBiologyProgrammed cell deathCell biologyApoptosisCellDNA damageCell fate determinationCaspaseGerm cellGeneticsCell growthGeneDNATranscription factor

Abstract

fetched live from OpenAlex

Programmed cell death (or apoptosis) is an evolutionarily conserved, genetically controlled suicide mechanism for cells that, when deregulated, can lead to developmental defects, cancers, and degenerative diseases. In C. elegans, DNA damage induces germ cell death by signaling through cep-1/p53, ultimately leading to the activation of CED-3/caspase. It has been hypothesized that the major regulatory events controlling cell death occur by cell-autonomous mechanisms, that is, within the dying cell. In support of this, genetic studies in C. elegans have shown that the core apoptosis pathway genes ced-4/APAF-1 and ced-3/caspase are required in cells fated to die. However, it is not known whether the upstream signals that activate apoptosis function in a cell-autonomous manner. Here we show that kri-1, an ortholog of KRIT1/CCM1, which is mutated in the human neurovascular disease cerebral cavernous malformation, is required to activate DNA damage-dependent cell death independently of cep-1/p53. Interestingly, we find that kri-1 regulates cell death in a cell-nonautonomous manner, revealing a novel regulatory role for nondying cells in eliciting cell death in response to DNA damage.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.246
Teacher spread0.238 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations54
Published2010
Admission routes2
Has abstractyes

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