Differential immunomodulatory effect of vitamin D (1,25 (OH)2 D3) on the innate immune response in different types of cells infected in vitro with infectious bursal disease virus
Bibliographic record
Abstract
It has been demonstrated that vitamin D (Vit D) included in diets offers a beneficial effect by improving innate immune responses in chickens. However, its mechanisms of action and the effect on immunosuppressive pathogens, such as infectious bursal disease virus, are not yet known. In the present study, we have studied the immunomodulatory effect of Vit D on the innate immune response in 3 cell lines: fibroblast cells (DF-1), macrophages (HD11), and B cells (DT-40) infected with IBDV (intermediate vaccine) at 2 multiplicity of infections (MOI) (1 and 0.1). Genes associated with innate immune responses (TLR-3, TLR-21, MDA-5, MyD88, TRIF, IRF-7, INF-α, INF-β, PKR, OAS, viperin, IL-1β, IL-6, and IL-12) were evaluated at different time points (3, 6, 12, 24, and 36 h after infection, h.p.i). Virus production reached a maximum at 24 h.p.i., which was significantly (P < 0.05) higher in DF-1 cells, followed by HD-11 and DT-40 cells. Mainly in HD-11 cells, there was a significant (P < 0.05) effect of Vit D supplementation on receptors TLR-3, TLR-21, and MDA-5 after 12 h.p.i, independent of MOI. DT-40 cells showed the highest antiviral activity, with a significant (P < 0.05) effect on IRF-7, IFN-β, OAS, and PKR gene expression, where expression of IRF-7 and IFN-β correlated positively with Vit D supplementation, while OAS and PKR were independent of Vit D. Proinflammatory cytokines were significantly (P < 0.05) upregulated and found to be Vit D and MOI dependent. In conclusion, this study demonstrated the capacity of IBDV to trigger a strong innate immune response in chicken cells and contributes to the understanding of the activation pathways of innate immunity induced by IBDV and further shows the benefitial effect of Vit D supplementation as an immunomodulator.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".