Pharmacokinetic study in pigs and<i>in vitro</i>metabolic characterization in pig- and human-liver microsomes reveal marked differences in disposition and metabolism of tiletamine and zolazepam (Telazol)
Bibliographic record
Abstract
1. An equal-dose combination of tiletamine and zolazepam (Telazol®) is used as a veterinary anesthetic. There also have been reports of human abuse of Telazol®. The pharmacokinetics and metabolic fate of tiletamine and zolazepam and the rationale for their administration as an equal-dose combination are unclear. 2. The single-dose pharmacokinetics of intramuscular tiletamine and zolazepam (3 mg/kg each) in 16 Yorkshire-crossbred pigs were determined. The metabolites of tiletamine and zolazepam in pig plasma and urine were identified by mass spectrometry. The metabolic stability of tiletamine and zolazepam and the kinetics of formation of their metabolites by pig- and human-liver microsomes were determined. 3. Higher concentrations of zolazepam were observed in pig plasma and it was cleared more slowly compared to tiletamine (apparent clearance: 11 versus 134 l/h; half-life: 2.76 versus 1.97 h). Three metabolites of zolazepam and one metabolite of tiletamine were identified in pig urine, plasma and in microsomal incubations. In vitro formation of each of these metabolites in microsomes was biphasic involving a high-affinity/low-capacity and a low-affinity/high-capacity enzyme. The in vitro metabolic stability of tiletamine was considerably lower compared to zolazepam. 4. These results collectively point to major pharmacokinetic and metabolic differences between the two components of this fixed-dose anesthetic combination.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".