Phthalates and alternative plasticizers differentially affect phenotypic parameters in gonadal somatic and germ cell lines
Bibliographic record
Abstract
The developmental and reproductive toxicity associated with exposure to phthalates has motivated a search for alternatives. However, there is limited knowledge regarding the adverse effects of some of these chemicals. We used high-content imaging to compare the effects of mono (2-ethylhexyl) phthalate (MEHP) with six alternative plasticizers: di-2-ethylhexyl terephthalate (DEHTP); diisononyl-phthalate (DINP); di-isononylcyclohexane-1,2-dicarboxylate (DINCH); 2-ethylhexyl adipate (DEHA); 2,2,4-trimethyl 1,3-pentanediol diisobutyrate (TXIB) and di-iso-decyl-adipate (DIDA). A male germ spermatogonial cell line (C18-4), a Sertoli cell line (TM4) and two steroidogenic cell lines (MA-10 Leydig and KGN granulosa) were exposed for 48 h to each chemical (0.001-100 μM). Cell images were analyzed to assess cytotoxicity and effects on phenotypic endpoints. Only MEHP (100 μM) was cytotoxic and only in C18-4 cells. However, several plasticizers had distinct phenotypic effects in all four cell lines. DINP increased Calcein intensity in C18-4 cells, whereas DIDA induced oxidative stress. In TM4 cells, MEHP, and DINCH affected lipid droplet numbers, while DEHTP and DINCH increased oxidative stress. In MA-10 cells, MEHP increased lipid droplet areas and oxidative stress; DINP decreased the number of lysosomes, while DINP, DEHA, and DIDA altered mitochondrial activity. In KGN cells, MEHP, DINP and DINCH increased the number of lipid droplets, whereas DINP decreased the number of lysosomes, increased oxidative stress and affected mitochondria. The Toxicological Priority Index (ToxPi) provided a visual illustration of the cell line specificity of the effects on phenotypic parameters. The lowest administered equivalent doses were observed for MEHP. We propose that this approach may assist in screening alternative plasticizers.
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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".