Probiotic Lactobacilli Enhance Immunogenicity of an Inactivated H9N2 Influenza Virus Vaccine in Chickens
Bibliographic record
Abstract
Avian influenza viruses (AIVs) infect a wide range of hosts, including humans and many avian species. Efforts have been made to control this pathogen in chickens using vaccination programs, but that has been met with varying degrees of success. Therefore, identification of more efficacious vaccination strategies is warranted. This study was undertaken to investigate the potential effects of probiotics on the immunogenicity of a beta-propiolactone-whole inactivated virus (WIV) vaccine of H9N2 subtype adjuvanted with the Toll-like receptor-21 ligand, CpG oligodeoxynucleotides 2007 (CpG). Eighty-four 1-day-old White Leghorn layers were allocated into six groups. Two out of six groups received a mixture of probiotic Lactobacillus spp. (PROB) biweekly from days 1 35 of age. Chickens were intramuscularly vaccinated with WIV either alone or adjuvanted with AddaVax™ (WIV+Add) or CpG (WIV+CpG), and one group received saline (phosphate-buffered saline). Primary and secondary vaccinations occurred at days 14 and 28 of age, respectively. The results revealed that the group that received probiotics and was vaccinated with CpG-adjuvanted WIV H9N2 vaccine had higher hemagglutination inhibition titers than the other treatment groups at days 14 and 21 postprimary vaccination. Probiotics did not induce higher IgM or IgY titers in chickens receiving the WIV vaccine only. Concerning their effect on cell-mediated immune responses, probiotics enhanced interferon-gamma (IFN-γ) gene expression and significantly increased secretion of IFN-γ protein by splenocytes in chickens vaccinated with CpG-adjuvanted WIV H9N2. Together, these findings suggest the use of probiotics to enhance the immunogenicity of CpG-adjuvanted WIV H9N2 vaccines. Additional studies are required to better understand the specific interactions between probiotics and the gut microbiota and different types of cells of the gastrointestinal tract to decipher the underlying mechanisms of how probiotics modulate immune responses to vaccines.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".