Nonylphenol Isomers Differ in Estrogenic Activity
Bibliographic record
Abstract
Nonylphenol belongs to the most investigated xenohormones acting at the estrogen receptor. Technical nonylphenol contains approximately 20 para-substituted isomers. Because of limitations in testing and quantifying all 20 isomers in the mixture, the linear form, 4n-NP, is often used as a reference substance, even though it is not present in the technical mixture. Here, we report on the synthesis and estrogenic potency of six nonylphenol isomers that occur at different proportions in technical nonylphenol mixtures. The relative potency of each isomer was determined by use of the MVLN transcriptional activation cell assay. As well, a subset of isomers was tested in the E-screen assay. One isomer, p353-NP, exhibited the same relative potency as the nonylphenol mixture, whereas the other isomers were found to be less potent. Two isomers, p22-NP and p262 NP, and the linear 4n-NP were found to be weak ER agonists with responses near the detection limit in the MVLN assay. Two isomers, p262-NP and 4n-NP, exhibited measurable activity in the E-screen. Our results demonstrate that defined p-NP isomers are most suitable for reflecting the estrogenic potency of technical NP mixtures. Among other applications, they should be used in the future to explain differences in estrogenic potency due to NPs as detected by various in vitro assays.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".