FAdV-4 induces more severe inflammatory responses compared to FAdV-8b
Bibliographic record
Abstract
Multiple infections, either single or mixed, involving pathogens such as serotype 4 fowl adenovirus (FAdV-4) and serotype 8b fowl adenovirus (FAdV-8b), have been observed in numerous laying hens in China, leading to severe liver damage. Thus, fowl adenovirus (FAdVs) is speculated to cause and inflammatory response. In this study, single infections with FAdV-4 and FAdV-8b were confirmed through RT-PCR and Enzyme-linked Immunosorbent Assay (ELISA) in specific pathogen-free (SPF) chickens exhibiting severe liver damage. Following this, the two reference strains, FAdV-4 and FAdV-8b, were inoculated into cardiomyocytes (CM) and cardiac fibroblasts (CF) to assess their immune responses. Additionally, the replication dynamics of FAdV-4 and FAdV-8b, as well as the expression levels of immune-related cytokines, were evaluated. The results demonstrated that FAdV-4 significantly enhanced viral replication in the heart, CM, and CF cells. The transcriptional levels of IL-1β, TNFα, IL-6, and IL-8 were markedly increased in cells infected with either FAdV-4 or FAdV-8b. These findings confirmed the in vitro and in vivo infection of FAdV-4 and FAdV-8b, elucidating their pathogenic mechanisms and providing new insights into the viral interactions and immune responses.
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 | 0.001 |
| 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".