Does 2,2′,4,4′‐tetrabromodiphenyl ether interact directly with thyroid receptor?
Bibliographic record
Abstract
2,2',4,4'-Tetrabromodiphenyl ether (BDE-47) is a flame-retardant chemical appearing at increasing concentrations and frequency in the environment and human samples. A number of health effects of exposure to BDE-47 have been observed, thyroid disruption being the most sensitive. Our objective was to examine BDE-47 interaction with thyroid receptor beta (TRβ). We used a variety of approaches, including in vitro binding assays, luciferase reporter-gene transcriptional assays, and analysis of expression of thyroid responsive genes in rat offspring exposed perinatally to BDE-47. We found that BDE-47 alone or in mixture with 2,2',4,4',5-pentabromodiphenyl ether (BDE-99), 2,2',4,4',6-pentabromodiphenyl ether (BDE-100), and 2,2',4,4',5,5'-hexabromodiphenyl ether (BDE-153) does not compete with [(125)I]T(3) for TRβ-binding even at 4000 fold higher concentrations. Also, BDE-47 does not affect thyroid responsive genes through TRβ in in vitro studies of transcription regulation. A subset of thyroid responsive genes were significantly differentially expressed in liver and frontal lobe brain samples of exposed pups, however, the action of BDE-47 was neither agonistic or antagonistic to that of thyroid hormone. We conclude that BDE-47 does not interact directly with TRβ1 nor does it influence its transcriptional activity. Developmental exposure of rats to BDE-47 leads to differential expression of thyroid responsive genes in liver and brain due to unknown mechanism.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".