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Record W1992268707 · doi:10.4161/cc.23046

Transgenerational cell fate profiling

2012· article· en· W1992268707 on OpenAlexfundno aff
Mohamed Jèmaà, Lorenzo Galluzzi, Oliver Kepp, Maria Castedo, Santiago Rello‐Varona, Ilio Vitale, Guido Kroemer

Bibliographic record

VenueCell Cycle · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrotubule and mitosis dynamics
Canadian institutionsnot available
FundersInstitute of Cancer ResearchNational Institutes of HealthInstitut National Du Cancer
KeywordsBiologyCell fate determinationMitosisAneuploidyCarcinogenesisCell divisionCell cycleCell biologyCellPopulationGenome instabilityGeneticsCancer researchDNA damageGeneTranscription factorDNAChromosome

Abstract

fetched live from OpenAlex

The illicit generation of tetraploid cells constitutes a prominent driver of oncogenesis, as it often precedes the development of aneuploidy and genomic instability. In addition, tetraploid (pre-)malignant cells display an elevated resistance against radio- and chemotherapy. Here, we report a strategy to preferentially kill tetraploid tumor cells based on the broad-spectrum kinase inhibitor SP600125. Live videomicroscopy revealed that SP600125 affects the execution of mitosis, impedes proper cell division and/or activates apoptosis in near-to-tetraploid, though less so in parental, cancer cells. We propose a novel graphical model to quantify the differential response of diploid and tetraploid cells to mitotic perturbators, including SP600125, which we baptized "transgenerational cell fate profiling." We speculate that this representation constitutes a valid alternative to classical "single-cell fate" and "genealogical" profiling and, hence, may facilitate the analysis of cell fate within a heterogeneous population as well as the visual examination of cell cycle alterations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.352

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.220
Teacher spread0.212 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations8
Published2012
Admission routes1
Has abstractyes

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