Development of an experimental model of pre-thrombosis in rats based on Wessler's principle using a calibrated venous stasis
Bibliographic record
Abstract
We have developed a model of a pre-thrombotic state in rats based on venous stasis induced by partial ligature of the inferior vena cava. The degree of stenosis was calibrated by using variations in upstream venous pressure. Different degrees of stasis were tested in order to obtain a pre-thrombotic state. Increasing doses of thromboplastin were infused. The thrombogenic potential of this model was evaluated by measuring thrombus weight and by the increase in levels of thrombin-antithrombin complexes. A pre-thrombotic state was induced by 2 h of exposure to a 40% stasis obtained by increasing by 40% the upstream venous pressure (mean thrombus weight, 0.2 +/- 0.6 mg). In these conditions of stasis, low doses of thromboplastin induced venous thrombosis (mean weight, 23 +/- 20 mg; P < 0.05). The increase in thrombus size was correlated to the rise in thrombin-antithrombin levels (r = 0.53, P < 0.001). In conclusion, we have developed the first animal model in which venous stasis can be calibrated by varying the degree of stenosis of the inferior vena cava. This model could be used to study the kinetics of biological markers of hypercoagulability, to study the pathogeny of thrombosis or to evaluate the therapeutic efficacy of new drugs in pre-clinical trials.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".