Biodistribution, plasma kinetics and quantification of single-pass pulmonary clearance of adrenomedullin
Bibliographic record
Abstract
The biodistribution, pharmacokinetics and multi-organ clearance of the vasodilator peptide AM (adrenomedullin) were evaluated in rats and its single-pass pulmonary clearance was measured in dogs by the indicator-dilution technique. Intravenously administered 125I-rAM(1-50) [rat AM(1-50)] was rapidly cleared following a two-compartment model with a very rapid distribution half-life of 2.0 min [95% CI (confidence interval), 1.98-2.01] and an elimination half-life of 15.9 min (95% CI, 15.0-16.9). The lungs retained most of the injected activity with evidence of single-pass clearance, since retention was lower after intra-arterial (13.5+/-0.6%) compared with intravenous (30.4+/-1.5%; P < 0.001) injection. Lung tissue levels of total endogenous AM were 20-fold higher than in other organs with no difference in plasma levels across the pulmonary circulation. In dogs, there was 36.4+/-2.1% first-pass unidirectional extraction of 125I-rAM(1-50) by the lungs that was reduced to 21.9+/-2.4% after the administration of unlabelled rAM(1-50) (P < 0.01). Extraction was not affected by calcitonin-gene-related peptide administration (40.6+/-2.9%), but was slightly reduced by the C-terminal fragment of human AM(22-52) (31.4+/-3.3%; P < 0.01). These data demonstrate that the lungs are a primary site for AM clearance in vivo with approx. 36% first-pass extraction through specific receptors. This suggests that the lungs not only modulate circulating levels of this peptide, but also represent its primary target.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".