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Record W2012077513 · doi:10.4161/psb.27577

Regulation of ABI5 turnover by reversible post-translational modifications

2014· article· en· W2012077513 on OpenAlexaff
Hongxia Liu, Sophia L. Stone

Bibliographic record

VenuePlant Signaling & Behavior · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCalcium signaling and nucleotide metabolism
Canadian institutionsDalhousie University
Fundersnot available
KeywordsSUMO proteinUbiquitinProteasomeBiologyCell biologyPhosphorylationAbscisic acidTranscription factorUbiquitin ligaseBiochemistryGene

Abstract

fetched live from OpenAlex

Post-translational modifications (PTMs) such as phosphorylation, ubiquitination, and sumoylation play significant roles in regulating abscisic acid (ABA) signaling. The targets for PTM are usually transcriptional regulators such as Abscisic acid Insensitive 5 (ABI5). PTM regulate ABI5 stability as well as activity. The abundance of ABI5 is tightly controlled by the ubiquitination-26S proteasome system. E3 ubiquitin ligases such as KEG negatively regulate ABA signaling by promoting ABI5 ubiquitination and subsequent degradation by the 26S proteasome. In our recent study we demonstrated that, in the absence of ABA, KEG-mediated turnover of ABI5 occurs within the cytoplasm. Whereas ubiquitination promotes ABI5 degradation, sumoylation prohibits degradation of the transcription factor. While phosphorylation has been shown to regulate ABI5 activity, our studies and others suggest that the phosphorylation status of ABI5 does not play a significant role in modulating ABI5 turnover.

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations41
Published2014
Admission routes1
Has abstractyes

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