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Record W4236022293 · doi:10.22215/etd/2014-10433

Less is MTOR: Regulation of Protein Synthesis via the Insulin Signaling Pathway in the Anoxia-Tolerant Red-Eared Slider Trachemys Scripta Elegans

2014· dissertation· en· W4236022293 on OpenAlexaff
Kama E. Szereszewski

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsCarleton University
Fundersnot available
KeywordsPI3K/AKT/mTOR pathwayBiologymTORC1Anoxic watersP70-S6 Kinase 1Protein kinase BTSC2Cell biologyInsulinEffectorHypoxia (environmental)Internal medicineInsulin receptorEndocrinologySignal transductionChemistryEcologyInsulin resistanceOxygenMedicine

Abstract

fetched live from OpenAlex

The red-eared slider turtle, Trachemys scripta elegans, can survive 3-4 months of anoxic submergence in cold water during the winter.The effect of hypoxia/anoxia on protein synthesis in red-eared sliders was investigated with a focus on the insulin-signaling pathway and analysis of the mammalian target of rapamycin (mTOR) and its upstream and downstream effectors in liver and white muscle.Expression of mTORC1 did not change in muscle but increased significantly in liver after 5 and 20 hours of anoxic submergence.Upstream effectors, AKT and RAPTOR, were also elevated in liver but suppressed in muscle.PRAS40 and TSC2 inhibitors of mTOR were differentially regulated in both tissues but generally suppressed.Downstream targets of mTOR signaling (eIF4E, 4E-BP1, P70S6K, S6) as well as the poly(A) binding protein also showed differential responses to anoxia.Overall, the data indicate that the early response to anoxia by turtles is maintenance of protein synthesis in liver but suppression in white muscle.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.231
Teacher spread0.218 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2014
Admission routes1
Has abstractyes

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