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Record W2112130045 · doi:10.1517/14728222.12.2.209

Mammalian target of rapamycin as a therapeutic target in oncology

2008· review· en· W2112130045 on OpenAlexaff
Robert T. Abraham, Christina H. Eng

Bibliographic record

VenueExpert Opinion on Therapeutic Targets · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsWomen's Health Research Institute
Fundersnot available
KeywordsPearlOncologyClinical OncologyInternal medicineMedicineGeographyCancerArchaeology

Abstract

fetched live from OpenAlex

BACKGROUND: The mammalian target of rapamycin (mTOR) has emerged as a validated therapeutic target in cancer and mTOR inhibitors alter tumor cell responses to mitogenic signals and microenvironmental stress. OBJECTIVES: The aims of this review are to describe the mTOR signaling pathway and the rationale for the use of rapamycin analogs and other mTOR inhibitors for oncology indications. METHODS: This review presents information from recent publications, as well as some more conjectural viewpoints stemming from the early clinical experience with mTOR inhibitors in cancer patients. RESULTS/CONCLUSIONS: A thorough understanding of the antitumor mechanisms of the existing mTOR inhibitors will drive the development of effective combination therapies to overcome tumor resistance to these agents. Furthermore, the development of second-generation inhibitors of this critical protein target may yield deeper and broader therapeutic activities in human cancers.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.382
Teacher spread0.327 · 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.

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

Citations92
Published2008
Admission routes1
Has abstractyes

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