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Record W2082241903 · doi:10.1158/0008-5472.can-07-0082

Targeting Multiple Arms of the Apoptotic Regulatory Machinery

2007· review· en· W2082241903 on OpenAlexaff
Yun Dai, Steven Grant

Bibliographic record

VenueCancer Research · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsImmunovaccine (Canada)
FundersNational Cancer Institute
KeywordsApoptosisCancer researchLethalitySynthetic lethalityCancerLong-term potentiationBiologyDNA repairGeneGenetics

Abstract

fetched live from OpenAlex

ABT-737 targets Bcl-2/Bcl-xL but not Mcl-1, which confers resistance to this novel agent. Here, we summarize recent findings indicating that Mcl-1 represents a critical determinant of ABT-737 sensitivity and resistance, and that Mcl-1 down-regulation by various pharmacologic agents or genetic approaches dramatically increases ABT-737 lethality in diverse malignant cell types. These findings also show that the multidomain proapoptotic proteins Bax and Bak play important functional roles in ABT-737-mediated apoptosis, and that Bak activation is essential in potentiation of ABT-737 lethality by agents that down-regulate Mcl-1. Collectively, these findings suggest a novel therapeutic strategy targeting multiple arms of the apoptotic machinery.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.100
GPT teacher head0.423
Teacher spread0.323 · 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 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

Citations110
Published2007
Admission routes1
Has abstractyes

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