Maternal Urinary Organophosphate Esters and Alterations in Maternal and Neonatal Thyroid Hormones
Bibliographic record
Abstract
Production of organophosphate esters (OPEs), which represent a major flame-retardant class present in consumer goods, has increased over the past 2 decades. Experimental studies suggest that OPEs may be associated with thyroid hormone disruption, but few human studies have examined this association. We quantified OPE metabolites in the urine of 298 pregnant women from Cincinnati, Ohio, in the Health Outcomes and Measures of the Environment Study (enrolled 2003-2006) at 3 time points (16 and 26 weeks' gestation, and at delivery), and thyroid hormones in 16-week maternal and newborn cord sera. Urinary bis(1,3-dichloro-2-propyl)-phosphate concentrations were generally associated with decreased triiodothyronine and thyroxine levels and increased thyroid-stimulating hormone levels in maternal and newborn thyroid hormones in quartile dose-response analyses and multiple informant models. There was weaker evidence for thyroid hormone alterations in association with diphenyl-phosphate and di-n-butyl-phosphate. Bis-2-chloroethyl-phosphate was not associated with alterations in thyroid hormones in any analyses. We did not observe any evidence of effect modification by infant sex. These results suggest that gestational exposure to some OPEs may influence maternal and neonatal thyroid function, although replication in other cohorts is needed.
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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 | 0.001 | 0.002 |
| 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".