Occurrence of Thyroid Hormone Activities in Drinking Water from Eastern China: Contributions of Phthalate Esters
Bibliographic record
Abstract
Thyroid hormone is essential for the development of humans. However, some synthetic chemicals with thyroid disrupting potentials are detectable in drinking water. This study investigated the presence of thyroid active chemicals and their toxicity potential in drinking water from five cities in eastern China by use of an in vitro CV-1 cell-based reporter gene assay. Waters were examined from several phases of drinking water processing, including source water, finished water from waterworks, tap water, and boiled tap water. To identify the responsible compounds, concentrations and toxic equivalents of a list of phthalate esters were quantitatively determined. None of the extracts exhibited thyroid receptor (TR) agonist activity. Most of the water samples exhibited TR antagonistic activities. None of the boiled water displayed the TR antagonistic activity. Dibutyl phthalate accounted for 84.0-98.1% of the antagonist equivalents in water sources, while diisobutyl phthalate, di-n-octyl phthalate and di-2-ethylhexyl phthalate also contributed. Approximately 90% of phthalate esters and TR antagonistic activities were removable by waterworks treatment processes, including filtration, coagulation, aerobic biodegradation, chlorination, and ozonation. Boiling water effectively removed phthalate esters from tap water. Thus, this process was recommended to local residents to reduce certain potential thyroid related risks through drinking water.
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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".