Depot-Specific Analysis of Human Adipose Cells and Their Responses to Bisphenol S
Bibliographic record
Abstract
Exposure to endocrine-disrupting chemicals (EDCs) is associated with adverse health outcomes including obesity and diabetes. Obesity, and more specifically visceral obesity, is correlated with metabolic disease. The adipose tissue is an endocrine organ and a potential target for many environmental pollutants including bisphenols. The subcutaneous (Sc) and the omental (Om, visceral) depots are composed of mature adipocytes and residing progenitors, which may be different between the depots and may be EDCs targets. Bisphenol A (BPA) is a suspected metabolic disruptor, and is being replaced with structurally similar compounds such as bisphenol S (BPS). Like BPA, BPS induces adipogenesis in murine and primary human Sc preadipocytes. However, the effect of BPS on Om preadipocytes is not known. In this study, we show that human primary progenitors from Om depots have a distinct transcriptomic signature as compared to progenitors derived from donor-matched Sc depots. Furthermore, we show that BPS increases adipogenesis both of Om and Sc preadipocytes and can mimic the action of glucocorticoids or peroxisome proliferator-activated receptor γ (PPARγ) agonists. We also show that BPS treatment, at 0.1 µM and 25 µM, modifies the adipokine profiles both of Om- and Sc-derived adipocytes in a depot-specific manner. Taken together our data show distinct gene expression profiles in the Om vs Sc progenitors and similar responses to the BPA analogue, BPS.
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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 | 0.001 |
| 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".