Dioxin-like Activity in Pregnant Women and Indices of Fetal Growth: The ACCEPT Birth Cohort
Bibliographic record
Abstract
Exposure to lipophilic persistent organic pollutants (lipPOPs) elicits a number of species- and tissue-specific toxic responses, many of which involve the aryl hydrocarbon receptor (AhR). This study aims to measure the combined serum dioxin-like activity of lipPOPs in Greenlandic Inuit pregnant women and the associations with fetal growth indices. The combined dioxin-like activity of serum lipPOPs extracts was determined using the AhR reporter gene bioassay and expressed as pico-gram (pg) TCDD equivalent (TEQ) per gram serum lipid [AhR-TEQ (pg/g lipid)]. Significant AhR-TEQ was found in >87% of serum samples with the median level of 86.2 pg TEQ/g lipid. The AhR-TEQ level positively correlated with the marine food intake biomarker n-3/n-6 polyunsaturated fatty acids ratio, while negatively correlated with body mass index and parity. Women giving birth to infants with low birth weight (<2500 g) and length (<50 cm) had higher AhR-TEQ level compared to those with normal weight and length infants. For previous smokers, we found significant inverse associations between maternal AhR-TEQ level and fetal growth indices. In conclusion, exposure of Greenlandic Inuit pregnant women to dioxin-like compounds through traditional marine food can adversely influence the fetal growth via induced AhR activity. Smoking might have modifying effects.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".