Bibliographic record
Abstract
PURPOSE OF REVIEW: To identify and discuss recent studies relating prenatal and early-life environmental exposures to the development of asthma and allergic disease. RECENT FINDINGS: New studies show that prenatal and early-life stress can alter infant immune profiles, increasing risk for asthma and allergy. Mounting evidence implicates indoor and outdoor air pollution in the origins of allergic disease, while Vitamin D intake and a Mediterranean diet may be protective. The role of early-life fever and infection remain controversial, with recent studies yielding conflicting results and new evidence indicating that previous studies may have been confounded. New studies are increasingly focused on environmental 'imprinting' of the infant gut microbiota, which is a critical determinant of immune system development. Early exposures impacting the intestinal microbiota include mode of delivery, infant diet, and use of antibiotics - factors that are also associated with childhood asthma and allergic disease. SUMMARY: This overview highlights environmental exposures during the in-utero and ex-utero time periods that are potential stimuli for the early programming of asthma and allergy. Special consideration is given for the potential role of intestinal microbiota. Future studies in this field promise to inform health policy and intervention strategies for the prevention of asthma and allergic disease.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".