NEW CLINICAL AND INVESTIGATIVE TOOLS FOR EVALUATING THROMBOSIS AND HAEMOSTASIS
Bibliographic record
Abstract
Haemostasis is maintained by a dynamic balance between pro- and anti-thrombotic mediators. Its dysregulation can lead to bleeding or thrombosis, and is a major cause of morbidity and mortality. Thus, elucidation of the mechanisms involved in maintaining or disrupting this balance have important implications in health and disease. Investigative tools enable characterization of the haemostatic system, but are often associated with limitations. For instance, haemostasis in animal models is often investigated by assessing bleeding responses in one particular vessel or tissue without a complete understanding of how the results translate to the regulation of haemostasis in other vascular beds. As a second example, microparticles (MPs) are a heterogeneous population of submicron-sized vesicles that may be important in thrombosis. With the exception of a few subtypes, MPs cannot be reliably characterized using widely accessible techniques. Finally, the thrombin generation assay (TGA), which measures ex vivo activation and inhibition of thrombin, is a promising tool for clinical assessment of thrombosis and haemostasis. However, characterization of thrombin generation in the general population, and the development of point of care testing are in their infancies. As a result, the TGA remains largely a research tool. The works described in this thesis specifically seek to address these three limitations in thrombosis and haemostasis research. The first isolated murine arterial bleeding model is presented and its characterization with respect to bleeding in other vascular tissues is described. In addition, a solid-phase capture assay for evaluating procoagulant, P-selectin-binding MPs, which are postulated to be mediators of thrombosis, was developed in order to determine whether these MPs associate with risk of recurrent venous thromboembolism. Lastly, a 25 x 20 mm chip that performs four individual thrombin generation assays using ~10 µl of capillary blood was developed as a proof of concept for point of care thrombin generation testing.
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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 | 0.011 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.005 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".