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Record W2804899347 · doi:10.1139/bcb-2018-0004

mTOR signalling: jack-of-all-trades

2018· review· en· W2804899347 on OpenAlexafffundvenue
Yassine El Hiani, Emmanuel E. Egom, Xian‐Ping Dong

Bibliographic record

VenueBiochemistry and Cell Biology · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsJewish General HospitalDalhousie University
FundersUniversity of TorontoDalhousie University
KeywordsPI3K/AKT/mTOR pathwayBiologyMechanistic target of rapamycinRPTORmTORC2SignallingKinaseCell biologyAutophagySignal transductionmTORC1ApoptosisGenetics

Abstract

fetched live from OpenAlex

The mechanistic target of rapamycin (mTOR) is an evolutionarily conserved serine/threonine kinase that senses and integrates environmental information into cellular regulation and homeostasis. Accumulating evidence has suggested a master role of mTOR signalling in many fundamental aspects of cell biology and organismal development. mTOR deregulation is implicated in a broad range of pathological conditions, including diabetes, cancer, neurodegenerative diseases, myopathies, inflammatory, infectious, and autoimmune conditions. Here, we review recent advances in our knowledge of mTOR signalling in mammalian physiology. We also discuss the impact of mTOR alteration in human diseases and how targeting mTOR function can treat human diseases.

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.004

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 head0.035
GPT teacher head0.313
Teacher spread0.278 · 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

Citations30
Published2018
Admission routes3
Has abstractyes

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