A Mixture of Ammonium Perchlorate and Sodium Chlorate Enhances Alterations of the Pitutary-Thyroid Axis Caused by the Individual Chemicals in Adult Male F344 Rats
Bibliographic record
Abstract
Ammonium perchlorate (AP) and sodium chlorate (SC) have been detected in public drinking water supplies in many parts of the United States. These chemicals cause perturbations in pituitary-thyroid homeostasis in animals by competitively inhibiting iodide uptake, thus hindering the synthesis of thyroglobulin and reducing circulating T(4) (thyroxine). Little is known about the short-term exposure effects of mixtures of perchlorate and chlorate. The present study investigated the potential for the response to a mixture of these chemicals on the pituitary-thyroid axis in rats to be greater than that induced by the individual chemicals. Adult male F-344 rats were exposed, via their drinking water, to the nominal concentrations of 0.1, 1.0, 10 mg/L AP or 10, 100, 1000 mg/L SC and their mixtures for 7 days. Serum T(4) levels were significantly (p < 0.05) reduced in rats following exposure to the mixtures, but not after exposure to the individual chemicals. Serum T(3) (triiodothyronine) was not altered by treatment and TSH (thyroid stimulating hormone) was only increased after the high-dose chlorate treatment. Histological examination of the thyroid gland showed colloid depletion and hypertrophy of follicular epithelial cells in high-dose single chemical and all mixture-treated rats, while hyperplasia was observed only in some of the rats treated with mixtures (AP 10 + SC 100, AP 0.1 + SC 1000, and AP 10 + SC 1000 mg/L). These data suggest that short-term exposure to the mixture of AP and SC enhances the effect of either chemical alone on the pituitary-thyroid axis in rats.
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 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".