Peroxisome Proliferator-Activated Receptor γ is a Sensitive Target for Oil Sands Process-Affected Water: Effects on Adipogenesis and Identification of Ligands
Bibliographic record
Abstract
Identification of toxic components of complex mixtures is a challenge. Here, oil sands process-affected water (OSPW) was used as a case study to identify those toxic components with a known protein target. Organic chemicals in OSPW exhibited dose-dependent activation of peroxisome proliferator-activated receptor γ (PPARγ) at concentrations less than those currently in the environment (0.025× equivalent of full-strength OSPW), by use of a luciferase reporter gene assay. Activation of PPARγ-mediated adipogenesis by OSPW was confirmed in 3T3L1 preadipocytes, as evidenced by accumulation of lipids and up-regulation of AP2, LPL, and PPARγ gene expression after exposure to polar fractions of OSPW. Unexpectedly, the nonpolar fractions of OSPW inhibited differentiation of preadipocytes via activation of the Wnt signaling pathway. Organic chemicals in OSPW that were ligands of PPARγ were identified by use of a pull-down system combined with untargeted chemical analysis (PUCA), with a recombinant PPARγ protein. Thirty ligands of PPARγ were identified by use of the PUCA assay. High resolution MS(1) and MS(2) spectra were combined to predict the formulas or structures of a subset of ligands, and polyoxygenated or heteroatomic chemicals, especially hydroxylated carboxylic/sulfonic acids, were the major ligands of PPARγ.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".