Unchanged triclabendazole kinetics after co-administration with ivermectin and methimazole: failure of its therapeutic activity against triclabendazole-resistant liver flukes
Bibliographic record
Abstract
BACKGROUND: The reduced drug accumulation based on enhanced drug efflux and metabolic capacity, identified in triclabendazole (TCBZ)-resistant Fasciola hepatica may contribute to the development of resistance to TCBZ. The aim of this work was to evaluate the pharmacokinetics and clinical efficacy of TCBZ administered alone or co-administered with ivermectin (IVM, efflux modulator) and methimazole (MTZ, metabolic inhibitor) in TCBZ-resistant F. hepatica-parasitized sheep. Sheep infected with TCBZ-resistant F. hepatica (Sligo isolate) were divided into three groups (n = 4): untreated control, TCBZ-treated (i.r. at 10 mg/kg) and TCBZ+IVM+MTZ treated sheep (10 i.r., 0.2 s.c. and 1.5 i.m. mg/kg, respectively). Plasma samples were collected and analysed by HPLC. In the clinical efficacy study, the animals were sacrificed at 15 days post-treatment to evaluate the comparative efficacy against TCBZ-resistant F. hepatica. RESULTS: The presence of IVM and MTZ did not affect the plasma disposition kinetics of TCBZ metabolites after the i.r. administration of TCBZ. The AUC value of TCBZ.SO obtained after TCBZ administration (653.9 +/- 140.6 microgxh/ml) was similar to that obtained after TCBZ co-administered with IVM and MTZ (650.7 +/- 122.8 microgxh/ml). Efficacy values of 56 and 38% were observed for TCBZ alone and for the combined treatment, respectively. No statistical differences (P > 0.05) were observed in fluke counts between treated groups and untreated control, which confirm the resistant status of the Sligo isolate. CONCLUSIONS: The presence of IVM and MTZ did not affect the disposition kinetics of TCBZ and its metabolites. Thus, the combined drug treatment did not reverse the poor efficacy of TCBZ against TCBZ-resistant F. hepatica.
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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 | 0.000 | 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 | 0.000 |
| 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".