Host Immune Response Modulation in Avian Coronavirus Infection: Tracheal Transcriptome Profiling In Vitro and In Vivo
Bibliographic record
Abstract
causing moderate to severe respiratory infection in chickens. Understanding the initial antiviral response in the respiratory mucosa is crucial for controlling viral spread. We aimed to characterize the impact of IBV Delmarva (DMV)/1639 and IBV Massachusetts (Mass) 41 at the primary site of infection, namely, in chicken tracheal epithelial cells (cTECs) in vitro and the trachea in vivo. We hypothesized that some elements of the induced antiviral responses are distinct in both infection models. We inoculated cTECs and infected young specific pathogen-free (SPF) chickens with IBV DMV/1639 or IBV Mass41, along with mock-inoculated controls, and studied the transcriptome using RNA-sequencing (RNA-seq) at 3 and 18 h post-infection (hpi) for cTECs and at 4 and 11 days post-infection (dpi) in the trachea. We showed that IBV DMV/1639 and IBV Mass41 replicate in cTECs in vitro and the trachea in vivo, inducing host mRNA expression profiles that are strain- and time-dependent. We demonstrated the different gene expression patterns between in vitro and in vivo tracheal IBV infection. Ultimately, characterizing host-pathogen interactions with various IBV strains reveals potential mechanisms for inducing and modulating the immune response during IBV infection in the chicken trachea.
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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) | 0.000 | 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) | 0.000 | 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".