Estrogenic Endocrine Disruptors and their Possible Deleterious Effects on Marine Organisms: Use of a Novel Monitoring Bioassay
Bibliographic record
Abstract
Abstract: Estrogens are both natural and synthetic substances that mimic the effect of the female estrogenic hormone in the body and impart estrogenic activity. Human wastes, birth control pills and chemicals like detergents are a major source of estrogens in the environment. In waste water treatment plants, a major part of these estrogens are not removed after treatment and are released in the marine environment. They are suspected to interfere with the exposed aquatic species’ endocrine systems. In fact, they mimic the effect of the endogenous hormone and therefore can disrupt the endocrine systems of exposed species and the reproductive systems of aquatic fauna. To understand their environmental fate, the estrogenic activity was studied by using the Yeast Estrogenic Screening (YES) bioassay. This bioassay has been validated in the detection of a wide range of estrogenic receptor agonists. A reverse phase HPLC method was used to identify the nature of estrogenic components.We focused on two marine bivalves Ruditapes decussatus and Cerastoderma glaucum recognised bioindicator organisms useful in biomonitoring. Our work is based on in situ and in vivo studies. Different compartments were used: the effluents of a wastewater treatment plant, the sea water, the sediment and the clam Ruditapes decussatus . Some observed histological effects showing hermaphroditic cases and parasites in the cockle Cerastoderma glaucum are also discussed in this paper.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".