Review: Postnatal development of the mucosal immune system and consequences on health in adulthood
Bibliographic record
Abstract
The intestinal microbiota is a dynamic multifaceted ecosystem which has evolved a complex and mutually beneficial relationship with the mammalian host. The contribution to host fitness is evident, but in recent years it has become apparent that these commensal microorganisms may exert far more influence over health and disease than previously thought. The gut microbiota are implicated in many aspects of biological function, such as metabolism, angiogenesis and immune development: disruption, especially during the neonatal period, which may impose life-long penalty. Elimination of the microbiota appears difficult, but manipulation of the ratios and dominance of composite populations can be achieved by alterations in diet, rearing environment, antibiotics and/or probiotics. Components of the intestinal microbiota are frequently documented to affect normal function of the mucosal immune system in experimental animals and in domesticated, agricultural species. However, it is not always clear that the effects described are sufficiently well understood to provide a sound basis for commercial intervention. Some microbial interventions may be beneficial to the host under particular circumstances, while detrimental during others. It is essential that we further our understanding of the complex and intricate host-commensal relationship to avoid causing more long-term damage than advantage.Key words: Postnatal immune development, microbiota manipulation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".