Effect of Covalent Serpin–Heparinoid Complexes on Plasma Thrombin Generation on Fetal Distal Lung Epithelium
Bibliographic record
Abstract
Extravascular coagulation within the lung airspace is a hallmark of respiratory distress syndrome (RDS) in premature infants. We previously showed that covalent antithrombin-heparin complex (ATH) is superior to noncovalent antithrombin (AT) + heparin (H) mixtures at inhibiting plasma thrombin generation on rat fetal distal lung epithelium (FDLE) in vitro. However, heparin cofactor II (HC) has been shown to selectively inhibit thrombin, which may be advantageous if other enzyme activities are present in the airspace. We compared the abilities of ATH, covalent HC-heparin complex (HCH), and covalent HC-dermatan sulfate (HCD) to inhibit thrombin generation on FDLE in plasmas from either adults or newborns. In the presence of ATH, peak free thrombin generation in adult plasma on the cell surface was reduced by 92% compared with controls (no anticoagulant). However, whereas HCH reduced peak free thrombin generation in adult plasma by 81%, HCD was only able to reduce activity by 33%. All covalent complexes caused a greater decrease in thrombin activity compared with that with the corresponding noncovalent serpin + heparinoid mixtures. Experiments in plasma from newborns resulted in peak free thrombin that was less than or equal to that in adult plasma when covalent conjugates were added. Relative peak free thrombin was proportional to rate of prothrombin consumption and amount of thrombin-inhibitor complexes formed. In vivo, experiments in newborn rats showed that a greater percentage of intratracheally instilled ATH and HCH could be recovered in lung lavage fluid compared withwith that for HCD. In summary, ATH, HCH, and HCD are inhibitors of thrombin generation on FDLE superior to the corresponding noncovalent mixtures, with ATH and HCH being more potent than HCD. Covalent conjugates of AT or HC with H may be preferred in treatment of extravascular coagulation.
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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".