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Record W1989656471 · doi:10.1074/jbc.m511831200

FRET Analysis of in Vivo Dimerization by RNA-editing Enzymes

2006· article· en· W1989656471 on OpenAlex
Kaari Chilibeck, Tao Wu, Chao Liang, Matthew J. Schellenberg, Emily M. Gesner, Jeffrey M. Lynch, Andrew M. MacMillan

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

VenueJournal of Biological Chemistry · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsADARRNA editingAdenosine deaminaseRNABiochemistryRNase PBiologyTransfectionEnzymeCell biologyMolecular biologyChemistryGene

Abstract

fetched live from OpenAlex

Members of the ADAR (adenosine deaminase that acts on RNA) enzyme family catalyze the hydrolytic deamination of adenosine to inosine within double-stranded RNAs, a poorly understood process that is critical to mammalian development. We have performed fluorescence resonance energy transfer experiments in mammalian cells transfected with fluorophore-bearing ADAR1 and ADAR2 fusion proteins to investigate the relationship between these proteins. These studies conclusively demonstrate the homodimerization of ADAR1 and ADAR2 and also show that ADAR1 and ADAR2 form heterodimers in human cells. RNase treatment of cells expressing these fusion proteins changes their localization but does not affect dimerization. Taken together these results suggest that homo- and heterodimerization are important for the activity of ADAR family members in vivo and that these associations are RNA independent.

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 score0.065
Threshold uncertainty score0.252

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 head0.008
GPT teacher head0.237
Teacher spread0.230 · 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