Oral Treatment of Chickens with Lactobacilli Influences Elicitation of Immune Responses
Bibliographic record
Abstract
Commensal microbes in the intestine are in constant interaction with host cells and play a role in shaping the immune system. Lactobacillus acidophilus, Lactobacillus reuteri, and Lactobacillus salivarius are members of the chicken intestinal microbiota and have been shown to induce different cytokine profiles in mononuclear cells in vitro. The objective of the present study was to examine the effects of these bacteria individually or in combination on the induction of antibody- and cell-mediated immune responses in vivo. The birds received lactobacilli weekly via oral gavage starting on day of hatch and subsequently, at 14 and 21 days, were immunized with sheep red blood cells (SRBC), keyhole limpet hemocyanin (KLH), Newcastle disease virus vaccine, and infectious bursal disease virus vaccine. Antibody responses in serum were measured weekly for 4 weeks beginning on the day of primary immunization. The cell-mediated immune response was evaluated at 21 days postimmunization by measurement of gamma interferon (IFN-γ) production in splenocytes stimulated with inactivated vaccine antigens. L. salivarius-treated birds had significantly more serum antibody to SRBC and KLH than birds that were not treated with probiotics. L. salivarius-treated birds also had decreased cell-mediated immune responses to recall antigen stimulation. L. reuteri treatment did not significantly affect the systemic immune response, while L. acidophilus treatment increased the antibody response to KLH. These results indicate that systemic antibody- and cell-mediated immune responses can be modulated by oral treatment with lactobacilli but that these bacteria may vary in their ability to modulate the immune response.
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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) | 0.001 | 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".