Effects of chloro-s-triazine herbicides and metabolites on aromatase activity in various human cell lines and on vitellogenin production in male carp hepatocytes.
Bibliographic record
Abstract
We investigated a potential mechanism for the estrogenic properties of three chloro-s-triazine herbicides and six metabolites in vitro in several cell systems. We determined effects on human aromatase (CYP19), the enzyme that converts androgens to estrogens, in H295R (adrenocortical carcinoma), JEG-3 (placental choriocarcinoma), and MCF-7 (breast cancer) cells; we determined effects on estrogen receptor-mediated induction of vitellogenin in primary hepatocyte cultures of adult male carp (Cyprinus carpio). In addition to atrazine, simazine, and propazine, two metabolites--atrazine-desethyl and atrazine-desisopropyl--induced aromatase activity in H295R cells concentration-dependently (0.3-30 microM) and with potencies similar to those of the parent triazines. After a 24-hr exposure to 30 microM of the triazines, an apparent maximum induction of about 2- to 2.5-fold was achieved. The induction responses were confirmed by similar increases in CYP19 mRNA levels, determined by reverse-transcriptase polymerase chain reaction. In JEG-3 cells, where basal aromatase expression is about 15-fold greater than in H295R cells, the induction responses were similar but less pronounced; aromatase expression in MCF-7 cells was neither detectable nor inducible under our culture conditions. The fully dealkylated metabolite atrazine-desethyl-desisopropyl and the three hydroxylated metabolites (2-OH-atrazine-desethyl, -desisopropyl, and -desethyl-desisopropyl) did not induce aromatase activity. None of the triazine herbicides nor their metabolites induced vitellogenin production in male carp hepatocytes; nor did they antagonize the induction of vitellogenin by 100 nM (EC(50) 17beta-estradiol. These findings together with other reports indicate that the estrogenic effects associated with the triazine herbicides in vivo are not estrogen receptor-mediated, but may be explained partly by their ability to induce aromatase in vitro.
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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) | 0.000 | 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) | 0.001 | 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".