Gestational and Lactational Exposure to the Emergent Alternative Plasticizer 1,2-Cyclohexane Dicarboxylic Acid Diisononyl Ester (DINCH) Impairs Lipid Metabolism to a Greater Extent Than the Commonly Used Di(2-Ethylhexyl) Phthalate (DEHP) in the Adult Rat Mammary Gland
Bibliographic record
Abstract
Due to their endocrine disruption properties, phthalate plasticizers such as di(2-ethylhexyl) phthalate (DEHP) can affect the hormone-dependent development of the mammary gland. Over the past few years, DEHP has been partially replaced by 1,2-cyclohexane dicarboxylic acid diisononyl ester (DINCH) which also have potential endocrine disrupting properties. The goal of the present study is to understand the impact of a gestational and lactational exposure to DEHP and DINCH on mammary gland development using Sprague Dawley rats. Both plasticizers altered the adipocytes of the mammary gland fat pad of adult progeny, as demonstrated by a decrease in their size, folding of their membrane, and modulations of the lipid profiles. DEHP treatments decreased the expression of Rxrα and Scd1 at the low and high dose, respectively, but did not affect any of the other genes studied. DINCH modulation of lipid metabolism could be observed at puberty by a decreased expression of genes implicated in triglyceride synthesis, lipid transport, and lipolysis, but by an increased expression of genes of the β-oxidation pathway and of genes involved in lipid storage and fatty acid synthesis at adulthood, compared with control and DEHP-treated rats. A strong upregulation of different inflammatory markers was observed following DINCH exposure only. Together, our results indicate that a gestational and lactational exposure to DINCH has earlier and more significant effects on lipid homeostasis, adipogenesis, and the inflammatory state of the adult mammary gland than DEHP exposure. The long-term consequence of these effects on mammary gland health remained to be determined.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".