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Record W3019610200 · doi:10.4049/jimmunol.1900309

Zebrafish NF-κB/p65 Is Required for Antiviral Responses

2020· article· en· W3019610200 on OpenAlexaff
Gang Ouyang, Qian Liao, Dawei Zhang, Fangjing Rong, Xiaolian Cai, Sijia Fan, Junji Zhu, Jing Wang, Xing Liu, Xueqin Liu, Wuhan Xiao

Bibliographic record

VenueThe Journal of Immunology · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsMinistry of Agriculture
FundersNational Natural Science Foundation of China
KeywordsZebrafishBiologyProinflammatory cytokineViremiaInnate immune systemNF-κBImmune systemCell biologyGeneImmunologyVirusVirologyInflammationSignal transductionGenetics

Abstract

fetched live from OpenAlex

Transcriptional programs regulated by the NF-κB family are essential for the inflammatory response as well as for innate and adaptive immunity. NF-κB activation occurs via two major signaling pathways: the canonical and the noncanonical. The canonical NF-κB pathway responds to diverse immune stimulations and leads to rapid but transient activation. As a member of the canonical NF-κB family, p65 is thought to be a key regulator of viral infection. Because of the embryonic lethality of p65-null mice, the physiological role of p65 in the antiviral immune response is still unclear. In this study, we generated p65-null zebrafish, which were viable and indistinguishable from their wildtype (WT) siblings under normal conditions. However, p65-null zebrafish were more sensitive to spring viremia of carp virus infection than their WT siblings. Further assays indicated that proinflammatory and antiviral genes, including IFN, were downregulated in p65-null zebrafish after spring viremia of carp virus infection compared with their WT siblings. Our results thus suggested that p65 is required for the antiviral response, activating not only proinflammatory genes but also antiviral genes (including IFN).

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.212
Threshold uncertainty score0.589

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.275
Teacher spread0.244 · 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 teacher head, 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

Citations34
Published2020
Admission routes1
Has abstractyes

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