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Record W3199065741 · doi:10.3390/cells10102517

The Dual Role of Autophagy in Crizotinib-Treated ALK+ ALCL: From the Lymphoma Cells Drug Resistance to Their Demise

2021· review· en· W3199065741 on OpenAlexaff
Estelle Espinos, Raymond Lai, Sylvie Giuriato

Bibliographic record

VenueCells · 2021
Typereview
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsAutophagyCrizotinibContext (archaeology)Cancer researchProgrammed cell deathBiologyCell biologyChemistryMedicineLung cancerApoptosisOncologyBiochemistry

Abstract

fetched live from OpenAlex

Autophagy has been described as harboring a dual role in cancer development and therapy. Depending on the context, it can exert either pro-survival or pro-death functions. Here, we review what is known about autophagy in crizotinib-treated ALK+ ALCL. We first present our main findings on the role and regulation of autophagy in these cells. Then, we provide literature-driven hypotheses that could explain mechanistically the pro-survival properties of autophagy in crizotinib-treated bulk and stem-like ALK+ ALCL cells. Finally, we discuss how the potentiation of autophagy, which occurs with combined therapies (ALK and BCL2 or ALK and RAF1 co-inhibition), could convert it from a survival mechanism to a pro-death process.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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