Comparative innate responses induced by Toll-like receptor (TLR)7 and 21 ligands against infectious bronchitis virus infection
Bibliographic record
Abstract
Toll-like receptor (TLR)7 and 21 ligands, resiquimod and cytosine-guanosine (CpG) oligonucleotides (ODNs) respectively have been used in ovo (pre-hatch) to enhance or prime an early immune response in chickens to provide protection against microbial pathogens. Yet, their protective efficacy against an infectious bronchitis virus (IBV) infection encountered post-hatch has not been evaluated. Thus, our objectives were to investigate the efficacy of resiquimod and CpG ODNs against a post-hatch IBV infection by delivering the ligands in ovo at embryo day (ED)18 and then, to determine possible mechanisms of protection. We found upregulation of interleukin (IL)-1β and interferon (IFN)-γ mRNA levels and considerable expansions of macrophage and cluster of differentiation (CD)8α+ T cell populations in lungs of chicken as early as day one post-hatch, following pre-hatch delivery of resiquimod. When the resiquimod pre-treated day-old chickens were infected with IBV, reduction in viral shedding via oral and fecal routes was observed at 3 days post-infection (dpi). Similarly, in CpG ODN pre-treated birds at 3 dpi, we found increased recruitment of macrophages, CD8α+ and CD4+ T lymphocytes in addition to up-regulation of IFN-γ and IL-1β mRNA concentrations in chicken lungs. However, only in ovo delivered CpG ODNs significantly reduced the morbidity and mortality associated with IBV infection. Overall, these studies bring us closer to understanding mechanisms behind CpG ODNs and resiquimod induced immune responses in chickens when used as stand-alone prophylactic agents in ovo.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".