Bisphenol A and Bisphenol S Induce Distinct Transcriptional Profiles in Differentiating Human Primary Preadipocytes
Bibliographic record
Abstract
Bisphenol S (BPS) is increasingly used as a replacement plasticizer for bisphenol A (BPA) but its effects on human health have not been thoroughly examined. Recent evidence indicates that both BPA and BPS induce adipogenesis, although the mechanisms leading to this effect are unclear. In an effort to identify common and distinct mechanisms of action in inducing adipogenesis, transcriptional profiles of differentiating human preadipocytes exposed to BPA or BPS were compared. Human subcutaneous primary preadipocytes were differentiated in the presence of either 25 μM BPA or BPS for 2 and 4 days. Poly-A RNA-sequencing was used to identify differentially expressed genes (DEGs). Functional analysis of DEGs was undertaken in Ingenuity Pathway Analysis. BPA-treatment resulted in 472 and 176 DEGs on days 2 and 4, respectively, affecting pathways such as liver X receptor (LXR)/retinoid X receptor (RXR) activation, hepatic fibrosis and cholestasis. BPS-treatment resulted in 195 and 51 DEGs on days 2 and 4, respectively, revealing enrichment of genes associated with adipogenesis and lipid metabolism including the adipogenesis pathway and cholesterol biosynthesis. Interestingly, the transcription repressor N-CoR was identified as a negative upstream regulator in both BPA- and BPS-treated cells. This study presents the first comparison of BPA- and BPS-induced transcriptional profiles in human differentiating preadipocytes. While we previously showed that BPA and BPS both induce adipogenesis, the results from this study show that BPS affects adipose specific transcriptional changes earlier than BPA, and alters the expression of genes specifically related to adipogenesis and lipid metabolism. The findings provide insight into potential BPS and BPA-mediated mechanisms of action in inducing adipogenesis in human primary preadipocytes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.002 | 0.001 |
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".