Evidence for Non-Linear Pharmacokinetics of Oxytocin in Anesthetizetized Rat
Bibliographic record
Abstract
PURPOSE: Because oxytocin (OT) is potentially useful in cardiovascular therapy but has hormonal roles on the cardiovascular and renal systems, we characterized its pharmacokinetic (PK) properties as a function of dose. METHODS: A single intravenous bolus of OT was given at doses of 200, 300, 500, 1000, 3000, 5000 and 10000 ng/kg to anesthetized male rats (n >= 4 per dose). Blood samples (6) were taken over 72 min to 150 min, depending on dose. The individual time-courses of plasma OT concentrations were analyzed with a one- or an open two-compartment PK model. Kruskal-Wallis tests (alpha=0.05) were used to compare the PK parameters among groups. RESULTS: At doses up to 500 ng/kg, OT showed a higher median systemic clearance (CLT = 0.0624 L/(min*kg); 0.0622 +/- 0.0228 as mean +/- SD value), a higher median central compartment volume of distribution (VC = 0.7906 L/kg; 0.6961 +/- 0.1754), and a lower median elimination half life (t(1/2)(lambdaz) 7.94 min; 9.08 +/- 4.3) with respect to the higher doses (CLT = 0.0266 L/(min*kg); 0.0284 +/- 0.0098, VC = 0.2213 L/kg; 0.2227 +/- 0.1142, and t(1/2)(lambdaz) 21.09 min; 28.36 +/- 21.8), all differences being significant (p 0.0008). Minimal differences were found for the estimates of these PK parameters among the 4 higher OT doses. CONCLUSION: The PK properties and persistence of exogenous OT are not proportional to dose, therefore this must be accounted for in dosing regimen design for potential cardiovascular therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".