Use of Freund's Complete Adjuvant (FCA) in inflammatory pain models: Consequences on the metabolism and pharmacokinetics of the non-peptidic delta receptor agonist SNC80 in the rat
Bibliographic record
Abstract
This study was initiated to characterize the metabolism and pharmacokinetics of SNC80 in rats and to evaluate the impact of Freund's complete adjuvant (FCA)-induced inflammation on its body disposition. In vitro, the disappearance and intrinsic clearance (CL(int)) of SNC80 were measured following incubations in recombinant rat CYPs and in phenotyped liver microsomes from naive and 24-h FCA-treated rats. The unbound fraction (f(u)) was assessed by ultrafiltration. Based on the Clint values, in vivo blood clearance of 3.35 and 2.48 L/h/kg were predicted in naive and FCA-treated rats. In vivo, SNC80 was administered to naive and 24-h FCA-treated rats at 10 micromol/kg i.v. and 50 micromol/kg p.o. The naive animals showed high plasma clearance (3.1 L/h/kg), low renal clearance (<0.02 L/h/kg) and poor bioavailability (<4%). Following i.v. administration, plasma clearance was lower (22%) in FCA-treated vs. untreated rats. Despite the decreases in f(u) (approximately 30%) and CL(int) (approximately 40%) in vitro, in vivo the apparent bioavailability and oral clearance were not significantly different between FCA-treated and naive rats. Hepatic and possibly intestinal losses contribute to the low bioavailability of SNC80. Non-hepatic mechanisms may compensate for the decrease in plasma clearance found in FCA-treated rats, preventing an increase in the oral bioavailability of SNC80.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".