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Record W3042220572 · doi:10.4049/jimmunol.1900902

Zebrafish <i>phd3</i> Negatively Regulates Antiviral Responses via Suppression of Irf7 Transactivity Independent of Its Prolyl Hydroxylase Activity

2020· article· en· W3042220572 on OpenAlexaff
Guangqing Yu, Xiong Li, Ziwen Zhou, Jinhua Tang, Jing Wang, Xing Liu, Sijia Fan, Gang Ouyang, Wuhan Xiao

Bibliographic record

VenueThe Journal of Immunology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsIRF7BiologyHydroxylationZebrafishTranscription factorCell biologyUbiquitinFunction (biology)GeneEnzymeBiochemistryHEK 293 cells

Abstract

fetched live from OpenAlex

Abstract Prolyl hydroxylase domain (PHD)–containing enzyme 3 belongs to the Caenorhabditis elegans gene egl-9 family of prolyl hydroxylases, which has initially been revealed to hydroxylate hypoxia-inducible factor α (HIF-α) and mediate HIF-α degradation. In addition to modulating its target function by hydroxylation, PHD3 has been also shown to influence its binding partners’ function independent of its prolyl hydroxylase activity. In this study, we report that overexpression of zebrafish phd3 suppresses cellular antiviral response. Moreover, disruption of phd3 in zebrafish increases the survival rate upon spring viremia of carp virus exposure. Further assays indicate that phd3 interacts with irf7 through the C-terminal IRF association domain of irf7 and diminishes K63-linked ubiquitination of irf7. However, the enzymatic activity of phd3 is not required for phd3 to inhibit irf7 transactivity. This study provides novel insights into phd3 function and sheds new light on the regulation of irf7 in retinoic acid–inducible gene I–like receptor signaling.

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 score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.240
Teacher spread0.228 · 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

Citations20
Published2020
Admission routes1
Has abstractyes

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