Phenanthrene and its halogenated derivative inhibit adipogenesis and decrease peroxisome proliferator-activated receptor gamma (PPARγ) expression independently of aryl hydrocarbon receptor (AhR) activation
Bibliographic record
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are natural by-products of incomplete combustion of fossil fuels, wood, incinerator waste, and are also used in man-made dyes, plastics, and pesticides. Humans are mostly exposed to PAHs through air (ex. smoke inhalation), drinking water, and foods. Phenanthrene (Phe) is the most abundant PAH found in the environment, however there are very few studies that have examined either its systemic health effects or its effects on metabolism and adipogenesis. Halogenated-polycyclic aromatic hydrocarbons (HPAHs) are a class of PAHs that have a halogen bound to an aromatic ring of a PAH, leading to increased potency compared to their PAH derivatives and yet are studied even less so than PAHs. Extensive research on another PAH, and a strong AhR activator, Benzo[a]pyrene (BaP) showed that BaP inhibited adipogenesis in vitro amongst other effects. In this study, we proceeded to investigate the effects of Phe and its halogenated counterpart, 9-chloro-phenanthrene (9P), on adipogenesis in the 3 T3-L1 cell line. Our results show that Phe and 9P inhibited adipogenesis independently of AhR upregulation or activation, indicated by their inability to increase the expression of the AhR and its downstream target gene CYP1A1. We also show that both Phe and 9P decreased PPARγ mRNA, and more pronouncedly protein expression. Further, effects on expression of proteins in the insulin signaling pathway, and adipokines were also observed, suggesting a global effect on adipocyte function.
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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".