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mTOR Signaling in Angiogenesis

2009· book-chapter· en· W13541650 on OpenAlexaff
Henry Mead, Mirjana Zeremski, Markus Guba

Bibliographic record

VenueHumana Press eBooks · 2009
Typebook-chapter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversity of TorontoToronto General Hospital
Fundersnot available
KeywordsPI3K/AKT/mTOR pathwayAngiogenesisProtein kinase BCancer researchRPTORBiologyVascular endothelial growth factorCell biologySignal transduction

Abstract

fetched live from OpenAlex

An important feature of tumor blood vessels is that they are in a state of constant new tumor blood vessel growth. In endothelial cells, the PI3K/Akt pathway has been shown to play an important role in mediating cell survival, proliferation, and migration. The serine/threonine kinase, mammalian target of rapamycin (mTOR), an important downstream target of PI3K/Akt and mTOR signaling, has been shown to be involved in the control of cell growth and proliferation. To grow beyond a certain size primary tumor and metastases are dependent on the formation of new blood vessels or angiogenesis. In angiogenesis mTOR serves as a central regulator. There is growing evidence in support of the hypothesis that mTOR acts as a critical switch for endothelial cellular catabolism and anabolism, thus determining whether these cells grow and proliferate. This is especially critical in cancer cells bearing disturbances in the TOR pathway. There are several human cancers whereby the PI3K/Akt pathway is dysregulated. Gain or loss mutations of this pathway lead to neoplastic transformation. mTOR inhibitors downregulate hypoxia-inducible factor 1α (HIF1α)-mediated production of pro-angiogenic cytokine, vascular endothelial growth factor (VEGF), by tumor cells and the resulting activation of vascular endothelial growth factor receptors (VEGF-Rs) on endothelial and lymphatic precursor cells inhibiting survival and growth-promoting signals that support tumor vascularization and tumorigenesis. The antiangiogenic and antilymphangiogenic effects of mTOR inhibition may well translate into a reduced incidence of clinically apparent malignancies through reduced tumor growth and lymphatic metastasis, respectively.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.850
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.043
GPT teacher head0.265
Teacher spread0.222 · 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
GenreOther

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

Citations8
Published2009
Admission routes1
Has abstractyes

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