Biodistribution of covalent antithrombin-heparin complexes
Bibliographic record
Abstract
We have developed a covalent antithrombin-heparin (ATH) complex with advantages compared to non-covalent antithrombin:heparin (AT:H) mixtures. In addition to increased activity, ATH has a longer intravenous half-life that is partly due to reduced plasma protein binding. Given ATH's altered clearance, we investigated biodistribution of ATH in vivo. ATH made from either human plasma-derived AT (pATH) or recombinant human (produced in goats) AT (rhATH) was studied. 125I-ATH + unlabeled carrier was injected into rabbits at different doses. 131I-labeled albumin was administered just before sacrifice as a marker for trapped blood in tissues. Immediately after sacrifice, animal components were removed, weighed, and subsamples were counted for gamma-radioactivity. Percent recoveries of ATH in various organs/compartments at different time points were calculated, and kinetic distribution plots generated. At saturating doses, early disappearance of rhATH from the circulation was much faster than pATH. Co-incident with clearance, 26 +/- 3% of dose for rhATH was liver-associated compared to only 3.7 +/- 0.5% for pATH by 20 min. Also, at early time periods, >60% of all extravascular ATH was liver-associated. Analysis of the vena cava and aorta suggested that vessel wall binding might also account for initial plasma loss of rhATH. By 24 h, most of pATH and rhATH were present as urinary degradation products (51 +/- 3% and 63 +/- 8%, respectively). In summary, systemic elimination of ATH is greatly influenced by the form of AT in the complex, with liver uptake and degradation playing a major role.
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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".