Modulation of Neonatal Microbial Recognition: TLR-Mediated Innate Immune Responses Are Specifically and Differentially Modulated by Human Milk
Bibliographic record
Abstract
The mechanisms controlling innate microbial recognition in the neonatal gut are still to be fully understood. We have sought specific regulatory mechanisms operating in human breast milk relating to TLR-mediated microbial recognition. In this study, we report a specific and differential modulatory effect of early samples (days 1-5) of breast milk on ligand-induced cell stimulation via TLRs. Although a negative modulation was exerted on TLR2 and TLR3-mediated responses, those via TLR4 and TLR5 were enhanced. This effect was observed in human adult and fetal intestinal epithelial cell lines, monocytes, dendritic cells, and PBMC as well as neonatal blood. In the latter case, milk compensated for the low capacity of neonatal plasma to support responses to LPS. Cell stimulation via the IL-1R or TNFR was not modulated by milk. This, together with the differential effect on TLR activation, suggested that the primary effect of milk is exerted upstream of signaling proximal to TLR ligand recognition. The analysis of TLR4-mediated gene expression, used as a model system, showed that milk modulated TLR-related genes differently, including those coding for signal intermediates and regulators. A proteinaceous milk component of > or =80 kDa was found to be responsible for the effect on TLR4. Notably, infant milk formulations did not reproduce the modulatory activity of breast milk. Together, these findings reveal an unrecognized function of human milk, namely, its capacity to influence neonatal microbial recognition by modulating TLR-mediated responses specifically and differentially. This in turn suggests the existence of novel mechanisms regulating TLR activation.
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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 | 0.001 | 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 | 0.001 |
| 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".