Effects of Developmental Exposure to Mixtures of Environmental Contaminants on the Hepatic Metabolism of Estradiol-17β in Immature Female Sprague Dawley Rats
Bibliographic record
Abstract
Exposure to environmental contaminants induces the activation of cytochrome P450s (CYP) which lead to the hydroxylation of contaminants and endogenous hormones such as estrogens. The hydroxylation of estrogens forms catecholestrogens (CEs), one of them being the mutagenic 4-hydroxyestradiol-17β (4-OH-E2). Catecholestrogens are transformed by catechol-o-methyltransferases (COMTs) into nonreactive methoxyestrogens. To investigate the hepatic metabolism of estradiol-17β in female offspring at postnatal day (PND) 21, pregnant rats were dosed daily from gestation day 1 until PND 21 with 2 dose levels of organochlorine pesticides (OCPs; 0.019 or 1.9 mg/kg per d), methylmercury (MeHg; 0.02 or 2 mg/kg per d), polychlorinated biphenyls (PCBs; 0.011 or 1.1 mg/kg per d), or a mixture (M; 0.05 or 5 mg/kg per d) including all 3 groups of chemicals. Concentrations of organochlorines in the mixture M were based on their proportions in serum of the Canadian Arctic population. The messenger RNA (mRNA) expressions of CYP and COMT were analyzed by quantitative reverse transcriptase-polymerase chain reaction (qRT-PCR). High-performance thin layer chromatography and phosphor imaging were used to measure the transformation of (14)C substrates into estrogen metabolites. The low-dose treatments or the MeHg groups had no effect. The high-dose OCP, PCB, and M group increased the production of 2-OH-E2 and 6α-OH-E2, while only the PCB and M groups increased the 2-OH-CE/methoxyestrogen ratio. In all groups, the cytosolic COMT activity exceeded the microsomal production rate of 4-OH-E2. Although the M treatment included the PCB and OCP mixtures, it did not modify the estrogen metabolism more than did the PCB mixture alone. This endocrine disruption information contributes to our understanding of chemical interactions in the toxicology of chemical mixtures.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".