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Record W4394274122 · doi:10.6084/m9.figshare.7211603

Porcine transmissible gastroenteritis virus nonstructural protein 2 contributes to inflammation via NF-κB activation

2018· dataset· en· W4394274122 on OpenAlexaff
Li Wang, Xinyuan Qiao, Sijia Zhang, Yue Qin, Tiantian Guo, Li Sun, Xiaona Wang, Yanan Wang, Yanping Jiang, Lijie Tang, Yigang Xu, Yijing Li

Bibliographic record

VenueFigshare · 2018
Typedataset
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInflammationNF-κBVirologyVirusBiologyImmunology

Abstract

fetched live from OpenAlex

Transmissible gastroenteritis virus (TGEV) infection causes acute enteritis in swine of all ages, and especially in suckling piglets. Small intestinal inflammation is considered a central event in the pathogenesis of TGEV infections, and nuclear factor-kappa B (NF-κB) is a key transcription factor in the inflammatory response. However, it is unclear whether NF-κB is crucial for inducing inflammation during a TGEV infection. Our results show that NF-κB was activated in swine testicular (ST) cells and intestinal epithelial cell lines J2 (IPEC-J2) cells infected with TGEV, which is consistent with the up-regulation of pro-inflammatory cytokines. Treatment of TGEV-infected ST cells and IPEC-J2 cells with the NF-κB-specific inhibitor caused the down-regulation of pro-inflammatory cytokine expression, but did not significantly affect TGEV replication. Individual TGEV protein screening results demonstrated that Nsp2 exhibited a high potential for activating NF-κB and enhancing the expression of pro-inflammatory cytokines. Functional domain analyzes indicated that the first 120 amino acid residues of Nsp2 were essential for NF-κB activation. Taken together, these data suggested that NF-κB activation was a major contributor to TGEV infection-induced inflammation, and that Nsp2 was the key viral protein involved in the regulation of inflammation, with amino acids 1–120 playing a critical role in activating NF-κB. Abbreviations: TCID50: 50% tissue culture infectious dose; DMEM: Dulbecco’s Modified Eagle Medium; eNOS: Endothelial nitric oxide synthase; FBS: fetal bovine serum; IFA: Indirect immunofluorescence; IκB: inhibitor of nuclear factor kappa-B; IL: interleukin; IPEC-J2: intestinal epithelial cell lines J2; IKK: IκB kinase; Luc: luciferase reporter gene; mAbs: monoclonal antibodies; MOI: multiple of infection; Nsp: nonstructural protein; NF-κB: nuclear factor-kappa ; ORFs: open reading frames; PBS: phosphate-buffered saline; p65 p-p65: phosphorylated; RT-PCR: reverse transcription PC; SeV: Sendai virus; ST: swine testicular; TGEV: Transmissible gastroenteritis virus; TNF-α: tumor necrosis factor α; UV-TGEV: Ultraviolet light-inactivated TGEV; ZnF: zinc finger

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0030.001

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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations0
Published2018
Admission routes1
Has abstractyes

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