Maternal Smoking in Pregnancy: Do the Effects on Innate (Toll-Like Receptor) Function Have Implications for Subsequent Allergic Disease?
Bibliographic record
Abstract
: Subtle increases in immaturity of immune function in early infancy have been implicated in the rising susceptibility to allergic disease, particularly relative impairment of type 1 interferon (IFN)-gamma responses in the neonatal period. Although genetic predisposition is a clear risk factor, the escalating rates of allergic disease in infancy suggest that environmental factors are also implicated. We previously showed that maternal smoking in pregnancy may impair neonatal IFN-gamma responses. Our more recent studies now indicate that this common avoidable toxic exposure is also associated with attenuation of innate immune function, with attenuated Toll-like receptor (TLR)-mediated microbial responses (including TLR-2, -3, -4, and -9 responses). Most notably, the effects were more marked if the mothers were also allergic. In this review, we discuss the significance of these observations in the context of the emerging hypothesis that variations in TLR function in early life may be implicated in allergic propensity. There is now growing evidence that many of the key pathways involved in subsequent T-cell programming and regulation (namely, antigen-presenting cells and regulatory T cells) rely heavily on microbe-driven TLR activation for maturation and function. Factors that influence the function and activity of these innate pathways in early life may contribute to the increasing predisposition for allergic disease. Although "cleaner" environments have been implicated, here we explore the possibility that other common environmental exposures (such as maternal smoking) could also play a role.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".