<i>In Vitro</i> Effects of Bisphenol A <b>β</b> -D-Glucuronide (BPA-G) on Adipogenesis in Human and Murine Preadipocytes
Bibliographic record
Abstract
BACKGROUND: Exposure to common environmental substances, such as bisphenol A (BPA), has been associated with a number of negative health outcomes. In vivo, BPA is rapidly converted to its predominant metabolite, BPA-glucuronide (BPA-G), which has long been believed to be biologically inactive because it lacks estrogenic activity. However, the effects of BPA-G on cellular metabolism have not been characterized. In the present study we examined the effect of BPA-G on adipogenesis. METHODS: The effect of BPA-G on the differentiation of human and 3T3L1 murine preadipocytes was evaluated in vitro by quantifying lipid accumulation and the expression of adipogenic markers. RESULTS: Treatment of 3T3L1 preadipocytes with 10 μM BPA-G induced a significant increase in lipid accumulation, mRNA expression of the adipogenic markers sterol regulatory element binding factor 1 (SREBF1) and lipoprotein lipase (LPL), and protein levels of LPL, aP2, and adipsin. Treatment of primary human preadipocytes with BPA-G also induced adipogenesis as determined by aP2 levels. Co-treatment of cells with the estrogen receptor (ER) antagonist fulvestrant (ICI) significantly inhibited the BPA-G-induced increase in LPL and aP2 levels, whereas treatment with ICI alone had no effect. Moreover, BPA-G did not display any significant estrogenic activity. CONCLUSIONS: To our knowledge, this study is the first to report that BPA-G induces adipocyte differentiation and is not simply an inactive metabolite. The fact that BPA-G induced adipogenesis and was inhibited by an ER antagonist yet showed no estrogenic activity suggests that it has no classical ER transcriptional activation function and acts through a pathway that remains to be determined.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".