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Record W2040962503 · doi:10.1097/mol.0b013e328352dd03

Connecting mTORC1 signaling to SREBP-1 activation

2012· review· en· W2040962503 on OpenAlexaff
Inan Bakan, Mathieu Laplante

Bibliographic record

VenueCurrent Opinion in Lipidology · 2012
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsInstitut Universitaire de Cardiologie et de Pneumologie de QuébecUniversité Laval
Fundersnot available
KeywordsmTORC1LipogenesisSterol regulatory element-binding proteinPI3K/AKT/mTOR pathwayTranscription factorBiologyCell biologySignal transductionCancer researchBiochemistryLipid metabolismGene

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The implication of the mammalian target of rapamycin (mTOR) complex 1 (mTORC1) in promoting protein synthesis has been well described. Over the past years, several studies revealed that mTORC1 also plays a crucial role in promoting lipid biosynthesis and that such connection could be linked to diseases including obesity, nonalcoholic fatty liver disease (NAFLD), and cancer. Here, we review the mechanisms by which mTORC1 regulates lipid synthesis by focusing on the key signaling events that trigger hepatic de-novo lipogenesis in response to nutrients and insulin. RECENT FINDINGS: mTORC1 promotes lipid synthesis by activating the transcription factor sterol regulatory element binding protein 1 (SREBP-1). Recent studies indicate that mTORC1 regulates SREBP-1 activation at multiple levels. Although mTORC1 was originally shown to be necessary and sufficient to activate SREBP-1 in vitro, new studies indicate that hyperactivation of mTORC1 is insufficient to trigger SREBP-1 activation and lipid biogenesis in vivo. These findings reveal that the molecular connection between mTORC1 and SREBP-1 is more complex than originally envisioned. SUMMARY: The discovery of a connection between mTORC1 and SREBP-1 opens a new chapter in our understanding of the molecular mechanisms regulating de-novo lipogenesis. A better comprehension of these mechanisms is key for the development of new tools to treat NAFLD and its complications.

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)
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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.182
GPT teacher head0.432
Teacher spread0.251 · 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

Citations281
Published2012
Admission routes1
Has abstractyes

Explore more

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