A rich meconium metabolome in human infants is associated with early-life gut microbiota composition and reduced allergic sensitization
Bibliographic record
Abstract
Microbiota maturation and immune development occur in parallel with, and are implicated in, allergic diseases, and research has begun to demonstrate the importance of prenatal influencers on both. Here, we investigate the meconium metabolome, a critical link between prenatal exposures and both early microbiota and immune development, to identify components of the neonatal gut niche that contribute to allergic sensitization. Our analysis reveals that newborns who develop immunoglobulin E (IgE)-mediated allergic sensitization (atopy) by 1 year of age have a less-diverse gut metabolome at birth, and specific metabolic clusters are associated with both protection against atopy and the abundance of key taxa driving microbiota maturation. These metabolic signatures, when coupled with early-life microbiota and clinical factors, increase our ability to accurately predict whether or not infants will develop atopy. Thus, the trajectory of both microbiota colonization and immune development are significantly affected by metabolites present in the neonatal gut at birth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".