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Record W2029411138 · doi:10.4161/cc.10.10.15520

Multiple pathways counteract cell death induced by RB1 loss: Implications for cancer

2011· article· en· W2029411138 on OpenAlexafffund
Giovanni Ciavarra, Eldad Zacksenhaus

Bibliographic record

VenueCell Cycle · 2011
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsBiologyAutophagyMyogenesisProgrammed cell deathCell biologyCancer cellApoptosisSuppressorCancer researchNeoplastic transformationCancerMyocyteGeneticsCarcinogenesis

Abstract

fetched live from OpenAlex

Inactivation of the tumor suppressor RB1 leads to cell proliferation, cell death and abortive differentiation in certain tissues and physiological contexts. Anti-apoptotic signals are thought to be the most important mechanism by which RB1-mutant cells escape cell death. Indeed, in the course of neoplastic transformation RB1 is often inactivated in conjunction with a mutation in the pro-apoptotic tumor suppressor p53. We have previously devised a biological framework to identify factors that maintain survival of differentiating Rb-deficient muscle fibers. We showed that differentiating Rb-deficient myoblasts fuse to form short myotubes that degenerate in a process associated with enhanced autophagy, and that degeneration was rescued by antagonists of apoptosis or autophagy, induction of mitochondrial-biogenesis or hypoxia-induced glycolytic shift, leading to long, twitching myotubes. Here, we also show that lithium slows the collapse of Rb-deficient myotubes and surprisingly, this is independent of autophagy, cyclin D3 and β-catenin. Thus, several distinct processes can suppress cell death induced by RB1 loss. We discuss these pathways and how they may cooperate with RB1 inactivation in the course of cancer initiation.

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 score0.035
Threshold uncertainty score0.501

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 head0.050
GPT teacher head0.297
Teacher spread0.247 · 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

Citations19
Published2011
Admission routes2
Has abstractyes

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