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Record W3159369840 · doi:10.3390/biom11050681

mTOR Signaling in Metabolic Stress Adaptation

2021· review· en· W3159369840 on OpenAlex

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.

Bibliographic record

VenueBiomolecules · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsCarleton UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsPI3K/AKT/mTOR pathwayBiologyCellular adaptationRegulatormTORC2Signal transductionMechanistic target of rapamycinTOR signalingAdaptation (eye)Cell biologyNeurosciencemTORC1GeneticsGene

Abstract

fetched live from OpenAlex

The mechanistic target of rapamycin (mTOR) is a central regulator of cellular homeostasis that integrates environmental and nutrient signals to control cell growth and survival. Over the past two decades, extensive studies of mTOR have implicated the importance of this protein complex in regulating a broad range of metabolic functions, as well as its role in the progression of various human diseases. Recently, mTOR has emerged as a key signaling molecule in regulating animal entry into a hypometabolic state as a survival strategy in response to environmental stress. Here, we review current knowledge of the role that mTOR plays in contributing to natural hypometabolic states such as hibernation, estivation, hypoxia/anoxia tolerance, and dauer diapause. Studies across a diverse range of animal species reveal that mTOR exhibits unique regulatory patterns in an environmental stressor-dependent manner. We discuss how key signaling proteins within the mTOR signaling pathways are regulated in different animal models of stress, and describe how each of these regulations uniquely contribute to promoting animal survival in a hypometabolic state.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.683

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.302
Teacher spread0.242 · 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