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Record W2011817914 · doi:10.1093/mutage/geu045

The expanding role of mTOR in cancer cell growth and proliferation

2015· review· en· W2011817914 on OpenAlex
Marie Cargnello, Joseph Tcherkezian, Philippe P. Roux

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMutagenesis · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversité de MontréalMcGill UniversityInstitute for Research in Immunology and Cancer
FundersCanadian Institutes of Health Research
KeywordsPI3K/AKT/mTOR pathwaymTORC1RPTORMechanistic target of rapamycinP70-S6 Kinase 1mTORC2Cell growthCell biologyBiologyRHEBKinaseProtein kinase BRibosomal s6 kinaseRibosomal protein s6Signal transductionBiochemistry

Abstract

fetched live from OpenAlex

The mechanistic/mammalian target of rapamycin (mTOR) is a conserved protein kinase that controls several anabolic processes required for cell growth and proliferation. As such, mTOR has been implicated in an increasing number of pathological conditions, including cancer, obesity, type 2 diabetes and neurodegeneration. As part of the mTOR complex 1 (mTORC1), mTOR regulates cell growth by promoting the biosynthesis of proteins, lipids and nucleic acids. Several mTORC1 substrates have been shown to regulate protein synthesis, including the eukaryotic initiation factor 4E (eIF4E)-binding proteins (4E-BPs) and the ribosomal S6 kinases (S6Ks) 1 and 2. In this work, we focus on the signalling pathways that lie both upstream and downstream of mTORC1, as well as their relevance to human pathologies. We further discuss pharmacological approaches that target mTOR and their applications for the treatment of cancer.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score0.618

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 head0.030
GPT teacher head0.329
Teacher spread0.299 · 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