Inferior Vena Cava Ligation Rapidly Induces Tissue Factor Expression and Venous Thrombosis in Rats
Bibliographic record
Abstract
OBJECTIVE: Although stasis is important in the pathogenesis of deep vein thrombosis (DVT), how it contributes to thrombogenesis is largely unknown. To gain mechanistic insight, we used a rat model of inferior vena cava (IVC) ligation. METHODS AND RESULTS: Rats were subjected to IVC ligation for 15 to 60 minutes. Ligation resulted in rapid IVC dilatation and by 60 minutes, thrombi were detected in all rats. Small thrombi were detected in the IVC of most rats after 15 minutes of ligation. Thrombi were rich in fibrin, contained aggregated platelets as well as trapped leukocytes and red cells, and most originated at sites of localized endothelial denudation. Immunohistochemical analysis revealed tissue factor (TF)-expressing leukocytes within the thrombi and adherent to the vessel wall. Despite a largely intact vessel wall, endothelial cells also stained for TF. The expression of TF colocalized with that of protein disulfide isomerase (PDI), an enzyme implicated in TF decryption. CONCLUSIONS: These findings suggest that the rapid development of DVT after IVC ligation reflects a combination of stasis-induced vein wall injury and enhanced TF expression in endothelial cells and leukocytes. Because TF expression occurs so soon after ligation, new synthesis is unlikely. Instead, stasis-induced venous dilatation with or without exposure of subendothelial TF, may be responsible for vessel wall TF expression. Colocalization of TF and PDI raises the possibility that PDI-mediated TF decryption plays a role in the pathogenesis of DVT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".