High-content imaging and transcriptomic analyses of the effects of bisphenol S and alternative color developers on KGN granulosa cells
Bibliographic record
Abstract
Concerns about the adverse effects of bisphenol A (BPA), a chemical used for the production of polycarbonate plastics, epoxy resins, and as a color developer in thermal papers, have led to an increase in the use of 4,4-sulfonyldiphenol (bisphenol S; BPS), bis(3-allyl-4-hydroxyphenyl) sulfone (TGSA), 4-hydroxyphenyl 4-isoprooxyphenylsulfone (D-8), [3-[(4-methylphenyl)sulfonylcarbamoylamino]phenyl] 4-methylbenzenesulfonate (Pergafast-201; PF-201), and 2,4-bis(phenylsulfonyl)phenol (DBSP) as alternative color developers. Data on these chemicals are scarce, and little is known about their potential toxicity. We determined the effects of BPS, TGSA, D-8, PF-201, and DBSP on the phenotype, function, and transcriptome of KGN human granulosa cells. Using high-content imaging, we observed that TGSA was the most cytotoxic compound tested, followed by D-8, DBSP, PF-201, and BPS. Although the effects of these compounds on lysosomes, mitochondria, and oxidative stress were minimal, TGSA, D-8, and PF-201 drastically increased the number and total area of lipid droplets compared with the control. RNA sequencing analyses revealed that TGSA and D-8 exposure differentially regulated 2,414 and 2,563 genes, respectively. PF-201 was the least transcriptionally active chemical, significantly affecting only 6 transcripts. The predominant effect of TGSA was the activation of pathways related to the extracellular matrix, whereas both TGSA and D-8 inhibited pathways involved in cell cycle regulation, DNA replication, and DNA repair. Such mechanisms may be underlying the cytotoxicity and lipid droplet accumulation observed in KGN cells. These data suggest that alternative color developers such as TGSA, D-8, and PF-201 act by different mechanisms and may not be responsible replacements for BPA and BPS in thermal papers.
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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 | 0.001 |
| 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".