Known and emerging factors modulating estrogenic effects of endocrine-disrupting chemicals
Bibliographic record
Abstract
A variety of endocrine-disrupting chemicals (EDCs) have estrogenic effects and are termed xenoestrogens (XEs). The genomic pathway mediated by estrogen receptors (ERs) has been considered the major explanation for the estrogenic effects elicited by XEs. Presently, nongenomic pathways have achieved considerably more attention because the genomic pathways cannot fully elucidate many biological and physiological responses. Genomic and nongenomic pathways act either separately or cooperatively. XEs activate a variety of signaling pathways and downstream kinases, which in turn alter the posttranslational modification and activation of ERs. Classical ERs and their splice variants reside at the membrane and mediate rapid effects cooperatively with G protein-coupled estrogen receptor 1 (GPER), G protein, and many other signaling molecules. GPER seems more effective in mediating the synthetic chemical-induced effects. There are also feedback and feedforward mechanisms between both pathways. Numerous factors may affect both pathways. Recently, some new layers of regulation on the estrogenic effects were identified. In this review, we summarize these multiple regulation layers and discuss the newly identified factors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".