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Record W3081751925 · doi:10.7554/elife.57132

CD163 and pAPN double-knockout pigs are resistant to PRRSV and TGEV and exhibit decreased susceptibility to PDCoV while maintaining normal production performance

2020· article· en· W3081751925 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueeLife · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of Guelph
FundersShenzhen Technical ProjectChinese Academy of Agricultural SciencesNational Natural Science Foundation of China
KeywordsPorcine reproductive and respiratory syndrome virusBiologyVirologyKnockout mouseGeneGenotypeCD163ReceptorVirusGeneticsPhenotype

Abstract

fetched live from OpenAlex

Porcine reproductive and respiratory syndrome virus (PRRSV) and transmissible gastroenteritis virus (TGEV) are two highly infectious and lethal viruses causing major economic losses to pig production. Here, we report generation of double-gene-knockout (DKO) pigs harboring edited knockout alleles for known receptor proteins CD163 and pAPN and show that DKO pigs are completely resistant to genotype 2 PRRSV and TGEV. We found no differences in meat-production or reproductive-performance traits between wild-type and DKO pigs, but detected increased iron in DKO muscle. Additional infection challenge experiments showed that DKO pigs exhibited decreased susceptibility to porcine deltacoronavirus (PDCoV), thus offering unprecedented in vivo evidence of pAPN as one of PDCoV receptors. Beyond showing that multiple gene edits can be combined in a livestock animal to achieve simultaneous resistance to two major viruses, our study introduces a valuable model for investigating infection mechanisms of porcine pathogenic viruses that exploit pAPN or CD163 for entry.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.410

Codex and Gemma teacher scores by category

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

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 head0.044
GPT teacher head0.231
Teacher spread0.188 · 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