Dietary supplementation with <i>Bifidobacterium lactis</i> NCC2818 from weaning reduces local immunoglobulin production in lymphoid-associated tissues but increases systemic antibodies in healthy neonates
Bibliographic record
Abstract
Weaning is associated with a major shift in the microbial community of the intestine, and this instability may make it more acquiescent than the adult microbiota to long-term changes. Modulation achieved through dietary interventions may have potentially beneficial effects on the developing immune system, which is driven primarily by the microbiota. The specific aim of the present study was to determine whether immune development could be modified by dietary supplementation with the human probiotic Bifidobacterium lactis NCC2818 in a tractable model of weaning in infants. Piglets were reared by their mothers before being weaned onto a solid diet supplemented with B. lactis NCC2818, while sibling controls did not receive supplementation. Probiotic supplementation resulted in a reduction in IgA (P<0·0005) and IgM (P<0·009) production by mucosal tissues but had no effect on IgG production (P>0·05). Probiotic-supplemented pigs had more mast cells than unsupplemented littermates (P<0·0001), although numbers in both groups were low. In addition, the supplemented piglets made stronger serum IgG responses to fed and injected antigens (P<0·05). The present findings are consistent with B. lactis NCC2818 reducing intestinal permeability induced by weaning, and suggest that the piglet is a valuable intermediate between rodent models and human infants. The results also strongly suggest that measures of the effect of probiotic supplementation on the immune system need to be interpreted carefully as proxy measures of health benefit. However, they are useful in developing an understanding of the mechanism of action of probiotic strains, an important factor in predicting favourable health outcomes of nutritional intervention.
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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".