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Record W2760281524 · doi:10.1080/15476286.2017.1379645

Visualizing tRNA-dependent mistranslation in human cells

2017· article· en· W2760281524 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRNA Biology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsWestern University
FundersCanadian Cancer Society Research InstituteUniversity of AdelaideCanada Research ChairsGovernment of Canada
KeywordsBiologyTransfer RNAComputational biologyGeneticsCell biologyRNAEvolutionary biologyGene

Abstract

fetched live from OpenAlex

(G3:U70) mutant that is not aminoacylated with proline, but is an efficient alanine acceptor. In live human cells, we visualized mistranslation using a green fluorescent protein reporter that fluoresces in response to mistranslation at proline codons. In agreement with measurements in yeast, quantitation based on the GFP reporter suggested a mistranslation rate of up to 2-5% in HEK 293 cells. Our findings suggest a stress-dependent phenomenon where mistranslation levels increased during nutrient starvation. Human cells did not mount a detectable heat-shock response and tolerated this level of mistranslation without apparent impact on cell viability. Because humans encode ∼600 tRNA genes and the natural population has greater tRNA sequence diversity than previously appreciated, our data also demonstrate a cell-based screen with the potential to elucidate mutations in tRNAs that may contribute to or alleviate disease.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.028
GPT teacher head0.349
Teacher spread0.321 · 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