Detection of Polybrominated Diphenyl Ethers in Herring Gull <i>(Larus argentatus</i>) brains: Effects on mRNA Expression in Cultured Neuronal Cells
Bibliographic record
Abstract
In recent years, polybrominated diphenyl ethers (PBDEs) have been detected at increasing levels in the environment due to their widespread use as flame retardants. PBDEs can affect thyroid hormone homeostasis and the cholinergic neurotransmitter system. In this study, several PBDE congeners were detected in whole brain samples and neuronal cells of herring gulls (Larus argentatus). A herring gull neuronal cell culture method was used to determine the effects of PBDEs on cytotoxicity and mRNA expression. Real-time RT-PCR assays were developed for genes associated with the thyroid hormone pathway (thyroid hormone receptors [TR alpha and beta], transthyretin [TTR]), and the cholinergic system (neuronal nicotinic acetylcholine receptor alpha-7 [nAChR alpha-7]). Administration of T3 resulted in a significant up-regulation of the two TRs and a significant down-regulation of TTR. TTR was also down-regulated by the commercial penta-BDE mixture, DE-71. In contrast, neither DE-71, nor BDE-47, -99, or -100 altered the mRNA levels of the TRs or nAChR alpha-7. The in vitro approach was a relevant model system for assessing the effects of PBDEs on cytotoxicity and mRNA expression. Herring gull neuronal cells were responsive to both T3 and PBDEs although, receptors associated with two predicted mechanisms of PBDE action were not effective molecular biomarkers of exposure.
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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".