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Record W3200599534 · doi:10.3390/v13091829

The Innate Immune DNA Sensing cGAS-STING Signaling Pathway Mediates Anti-PRRSV Function

2021· article· en· W3200599534 on OpenAlexaff
Yulin Xu, Youwen Zhang, Shaohua Sun, Jia Luo, Sen Jiang, Jiajia Zhang, Xueliang Liu, Qi Shao, Qi Cao, Wanglong Zheng, Nanhua Chen, François Meurens, Jianzhong Zhu

Bibliographic record

VenueViruses · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of Saskatchewan
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsYangzhou UniversityGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsInnate immune systemStingPorcine reproductive and respiratory syndrome virusBiologyGene knockdownVirologyRIG-IImmunityImmune systemVirusDNA virusImmunologyGeneGeneticsGenome

Abstract

fetched live from OpenAlex

Porcine reproductive and respiratory syndrome virus (PRRSV) modulates host innate immunity which plays a key role against PRRSV infection. As a RNA virus, PRRSV is mainly sensed by innate immune RNA receptors, whereas the role of innate immune DNA sensors in the PRRSV infection has not been elucidated. Here, we investigated the roles of DNA sensing cGAS-STING pathway in both PRRSV infected Marc-145 cells and porcine macrophages. The results show that in Marc-145 cells, the stable expression of STING with or without stimulations exhibited anti-PRRSV activity, and STING knockout heightened PRRSV infection. In CD163-3D4/21 porcine macrophages, either expression of STING or stimulation of cGAS-STING signaling obviously suppressed PRRSV infection, whereas in STING knockdown macrophages, the PRRSV infection was upregulated. Our results clearly demonstrate that the host cGAS-STING signal exerts an important antiviral role in PRRSV infection.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.039
GPT teacher head0.233
Teacher spread0.194 · 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

Citations32
Published2021
Admission routes1
Has abstractyes

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