Maternal endotoxin exposure attenuates allergic airway disease in infant rats
Bibliographic record
Abstract
Prenatal exposures to immunogenic stimuli, such as bacterial LPS, have shown to influence the neonatal immune system and lung function. However, no detailed analysis of the immunomodulatory effects of LPS on postnatal T helper cell differentiation has been performed. Using a rat model, we investigated the effect of prenatal LPS exposure on postnatal T cell differentiation and experimental allergic airway disease. Pregnant rats were injected with LPS on day 20 and 21 (term = 22 days). Some of the offspring were sensitized and challenged with ovalbumin. Positive control animals were placebo exposed to saline instead of LPS, whereas negative controls were sensitized with saline. Expression of T cell-related transcription factors and cytokines was quantified in the lung, and airway hyperresponsiveness was measured. Prenatal LPS exposure induced a T helper 1 (T(H)1) immune milieu in the offspring of rats [i.e., increased T-bet and T(H)1 cytokine expression while expression of T(H)2-associated transcription factors (GATA3 and STAT6) and cytokines was decreased]. Prenatal LPS exposure did not trigger T(H)17 cell differentiation in the offspring. Furthermore, prenatal LPS exposure reduced ovalbumin-induced (T(H)2-mediated) airway inflammation, eosinophilia, and airway responsiveness. Thus, in utero exposure to endotoxin promotes a T(H)1 immune environment, which suppresses the development of allergic airway disease later in life.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".