Organophosphate Esters Disrupt Steroidogenesis in KGN Human Ovarian Granulosa Cells
Bibliographic record
Abstract
Organophosphate esters (OPEs) are used extensively as flame retardants and plasticizers and are found ubiquitously in the environment and human matrices. Previous studies suggested that exposure to some of these chemicals may disrupt the homeostasis of female sex hormones and have detrimental effects on female fertility. Here, we determined the effects of OPEs on the function of KGN ovarian granulosa cells. We hypothesized that OPEs alter the steroidogenic ability of these cells by dysregulating the expression of transcripts involved in steroid and cholesterol biosynthesis. KGN cells were exposed for 48 hours to 1 of 5 OPEs (1-50μM): triphenyl phosphate (TPHP), tris(methylphenyl) phosphate (TMPP), isopropylated triphenyl phosphate (IPPP), tert-butylphenyl diphenyl phosphate (BPDP), and tributoxyethyl phosphate (TBOEP), or to a polybrominated diphenyl ether flame retardant, 2,2',4,4' tetrabromodiphenyl ether (BDE-47), in the presence or absence of Bu2cAMP. OPEs increased the basal production of progesterone (P4) and 17β-estradiol (E2) and had either no effect or inhibited Bu2cAMP-stimulated P4 and E2 synthesis; exposure to BDE-47 had no effect. Quantitative real-time polymerase chain reaction (qRT-PCR) analyses revealed that OPEs (≥5μM) increased the basal expression of critical genes (STAR, CYP11A1, CYP19A1, HSD3B2, and NR5A1) involved in steroidogenesis; upon stimulation, the expression of all genes tested was downregulated. An overall inhibition in cholesterol biosynthesis was induced by OPEs, characterized by a downregulation in HMGCR and SREBF2 expression. TBOEP consistently showed the least effect. Therefore, OPEs perturbed steroidogenesis in KGN granulosa cells by targeting the expression of steroidogenic enzymes and cholesterol transporters; these effects may have an adverse impact on female reproduction.
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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 | 0.000 |
| 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) | 0.001 | 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".