Cytokine gene transcription in the trachea, Harderian gland, and trigeminal ganglia of chickens inoculated with virulent infectious laryngotracheitis virus (ILTV) strain
Bibliographic record
Abstract
The objective of this study was to determine how cytokine transcription profiles correlate with patterns of infectious laryngotracheitis virus (ILTV) replication in the trachea, Harderian gland, and trigeminal ganglia during the early and late stages of infection after intratracheal inoculation. Viral genomes and transcripts were detected in the trachea and Harderian gland but not in trigeminal ganglia. The onset of viral replication in the trachea was detected at day one post-infection and peaked by day three post-infection. The peak of pro-inflammatory (CXCLi2, IL-1β, IFN-γ) and anti-inflammatory (IL-13, IL-10) cytokine gene transcription, 5 days post-infection, coincided with the increased recruitment of inflammatory cells, extensive tissue damage, and limiting of virus replication in the trachea. In contrast, transcription of the IFN-β gene in the trachea remained unaffected suggesting that ILTV infection blocks type I interferon responses. In the Harderian gland, the most evident transcription change was the early and transient upregulation of the IFN-γ gene at 1 day post-infection, which suggests that the Harderian gland is prepared to rapidly respond to ILTV infection. Overall, results from this study suggest that regulation of Th1 effector cells and macrophage activity by Th1/2 cytokines was pertinent to maintain a balanced immune response capable of providing an adequate Th1-mediated protective immunity, while sustaining some immune homeostasis in preparation for the regeneration of the tracheal mucosa.
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".