Prenatal maternal stress exposure and immune function in the offspring
Bibliographic record
Abstract
The intra-uterine environment provides the first regulatory connection for the developing fetus and shapes its physiological responses in preparation for postnatal life. Psychological stress acts as a programming determinant by setting functional parameters to abnormal levels, thus inducing postnatal maladaptation. The effects of prenatal maternal stress (PNMS) on the developing immune system have been documented mostly through animal studies, but inconsistent results and methodological differences have hampered the complete understanding of these findings. As the immune system follows a similar ontogenic pattern in all mammals, a translational framework based on the developmental windows of vulnerability proposed by immunotoxicology studies was created to integrate these findings. The objective of this review is to examine the available literature on PNMS and immune function in the offspring through the above framework and gain a better understanding of these results by elucidating the moderating influence of the stressor type, timing and duration, and the offspring species, sex and age at assessment. The evaluation of the literature through this framework showed that the effects of PNMS are parameter specific: the moderating effects of timing in gestation were relevant for lymphocyte population numbers, Natural Killer cell function and mitogen-induced proliferation. The presence of an important and directional sexual dimorphism was evident and the influence of the type or duration of PNMS paralleled that of stress in non-pregnant animals. In conclusion, PNMS is a relevant factor in the programming of immune function. Its consequences may be related to disorders with an important immune component such as allergies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".