Survey of hormone activities in municipal biosolids and animal manures
Bibliographic record
Abstract
The potential exists for natural or synthetic hormonal chemicals present in agricultural fertilizers to be transferred to adjacent aquatic environments in order to alter endocrine function in exposed wildlife. Recombinant yeast and mammalian cell line (BG1Luc4E2) assays were used to screen crude organic extracts of municipal biosolids and animal manures for estrogen-, androgen-, and progesterone receptor gene transcription activities. Of the biosolid extracts, those samples that had undergone aerobic digestion had no or minimal estrogen- and no androgen receptor gene transcription activities. In contrast, those biosolid samples that had undergone anaerobic digestion had much higher estrogen- and, for all but one site, androgen receptor gene transcription activities. Extracts prepared from animal manure samples had variable levels of androgen- and estrogen receptor gene transcription activities, which may be related to the type, sex, age, and reproductive status of the animals. The diet and treatment of animals with hormone implants also appeared to be factors influencing hormone activity in animal manure. Progesterone receptor gene transcription activity was observed for only one chicken litter sample. Overall, results of this study suggest that in vitro bioassays can be used to survey and detect hormone activity in municipal biosolids and animal manures. Furthermore, results of these assays can be used to develop practices that will minimize the potential environmental endocrine-disrupting effects of these substances.
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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 | 0.001 | 0.001 |
| 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 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".