Attenuation of porcine deltacoronavirus disease severity by porcine reproductive and respiratory syndrome virus coinfection in a weaning pig model
Bibliographic record
Abstract
Porcine deltacoronavirus (PDCoV) is a potentially emerging zoonotic pathogen that causes severe diarrhea in young pigs, with a risk of fatal dehydration. Its pathogenicity on neonatal piglet has been previously reported, however, it is less known if the coinfection with immunosuppressive pathogens can influence PDCoV disease manifestation. Here, a coinfection model of PDCoV and porcine reproductive and respiratory syndrome virus (PRRSV), a global-spread immunosuppressive virus, was set to study their interaction. Weaning pigs in the coinfection group were intranasally inoculated with PRRSV NADC30-like virus and latterly orally inoculated with PDCoV at three day-post-inoculation (DPI). Unexpectedly, compared with pigs in the PDCoV single-infected group, the coinfected pigs did not show any obvious diarrhea, as PDCoV fecal shedding, average daily weight gain (ADWG), gross and microscopic lesions and PDCoV IHC scores consistently indicated that PRRSV coinfection lessened PDCoV caused diarrhea. Additionally, three proinflammatory cytokines TNF-α, IL-1 and IL-6, which can be secreted by PRRSV infected macrophages, were detected to be highly expressed at the intestine from both PRRSV infected groups. By adding to PDCoV-infected cells, these three cytokines were further confirmed to be able to inhibit the PDCoV replication post its cellular entry. Meanwhile, the inhibition effect of the supernatant from PRRSV-infected PAMs could be obviously blocked by the antagonist of these three cytokines. In conclusion, PRRSV coinfection increased TNF-α, IL-1, and IL-6 in the microenvironment of intestines, which inhibits the PDCoV proliferation, leading to lessened severity of diarrhea. The findings provide some new insight into the pathogenesis and replication regulation of PDCoV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".