Evaluation of the Influence of Chloroacetic Acids on the Pharmacokinetics of Trihalomethanes in the Rat
Bibliographic record
Abstract
Chloroacetic acids (monochloroacetic acid [MCA], dichloroacetic acid [DCA], and trichloroacetic acid [TCA]) and trihalomethanes (THMs: chloroform [CHCl(3)], bromodichloromethane [BDCM], dibromochloromethane [DBCM], and bromoform [TBM]) are common by-products of the chlorination of drinking water. The purpose of this study was to evaluate the influence of chloroacetic acids on the pharmacokinetics of trihalomethanes in the male Sprague-Dawley rat. In the first series of studies, groups of 5 animals were given, by intravenous injections, a single dose of 0.125 mmol/kg of one of the four THMs. Additional groups received a binary mixture containing 0.125 mmol/kg of a THM plus 0.125 mmol/kg of a chloroacetic acid. The venous blood concentrations of unchanged THMs were measured by headspace gas chromatography from 5 min to 6 h postadministration. The areas under the blood concentration versus time curves (AUCs) of CHCl(3), BDCM, and DBCM were increased by a factor of 3.5, 1.6, and 2, respectively, by coadministration of TCA. DCA coadministration resulted in an increase in the AUC of DBCM (x2.5) and TBM (x1.3), whereas MCA modified the Cmax (x1.5) and AUC (x1.8) of BDCM and the AUC of DBCM (x2.5). In the second series of experiments, animals received either a single dose of 0.03125 mmol/kg of one of the four THMs, a mixture containing 0.03125 mmol/kg of each of the four THMs (total dose = 0.125 mmol/kg), or a mixture containing 0.03125 mmol/kg of each of the four THMs plus 0.125 mmol/kg of either TCA or DCA. Results indicated that the AUCs of CHCl(3), BDCM, DBCM, and TBM were increased during coadministration compared to single administrations (+2.5-fold). Combined administration of the four THMs with TCA, and not DCA, resulted in an increase of the AUCs of THMs (CHCl(3): x11.7; BDCM, DBCM, and TBM: x3.9) and an increase in the Cmax of CHCl(3) (x1.9). Overall, these results indicate that, at the dose levels tested in this study, TCA alters the blood concentration profiles of THMs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".