Exposure to<i>tert</i>-Butylphenyl Diphenyl Phosphate, an Organophosphate Ester Flame Retardant and Plasticizer, Alters Hedgehog Signaling in Murine Limb Bud Cultures
Bibliographic record
Abstract
Organophosphate esters have become widely used as flame retardants since the phase out of polybrominated diphenyl ethers. Previously, we demonstrated that some organophosphate esters, such as tert-butylphenyl diphenyl phosphate (BPDP), were more detrimental to endochondral ossification in murine limb bud cultures than one of the major polybrominated diphenyl ethers that they replaced, 2,2',4,4'-tetrabromodiphenyl ether. Here, we used a transcriptomic approach to elucidate the mechanism of action of BPDP in the developing limb. Limb buds collected from gestation day 13 CD1 mouse embryos were cultured for 3 or 24 h in the presence of vehicle, 1 μM, or 10 μM BPDP. RNA sequencing analyses revealed that exposure to 1 µM BPDP for 24 h increased the expression of 5 transcripts, including Ihh, and decreased 14 others, including Gli1, Ptch1, Ptch2, and other targets of Hedgehog (Hh) signaling. Pathway analysis predicted the inhibition of Hh signaling. Attenuation of Hh signaling activity began earlier and reached a greater magnitude after exposure to 10 µM BPDP. Because this pathway is part of the regulatory network governing endochondral ossification, we used a known Hh agonist, purmorphamine, to determine the contribution of Hh signaling inhibition to the negative impact of BPDP on endochondral ossification. Cotreatment of limbs with purmorphamine rescued the detrimental morphological changes in the cartilage template induced by BPDP exposure though it did not restore the expression of key transcription factors, Runx2 and Sp7, to control levels. These data highlight Hh signaling as a developmentally important pathway vulnerable to environmental chemical exposures.
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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 | 0.001 |
| 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".