Contribution of Coagulation Pathways and Fibrinolysis in Generation of Kinins.
Bibliographic record
Abstract
Abstract BACKGROUND. Classically, there are two main pathways by which kinins are generated: the plasma and tissue kallikrein-kinin systems. Each of this complex multi-protein system includes tissue or plasma kallikrein, which generate kinins from high or low molecular weight kininogen. In addition to plasma and tissue kallikreins, other serine proteases may have a kinin-forming capacity. OBJECTIVES. The main purpose of this study was to characterize the kininogenase activity of plasma kallikrein, thrombin (factor IIa), factor Xa, and plasmin in a purified system. We also aimed at characterizing the kinetic profile of generation of kinins in a whole blood system where coagulation and fibrinolysis were monitored by thromboelastography. METHODS. Bradykinin (BK) released from both low and high molecular weight kininogens and quantified with a specific competitive enzyme immunoassay was used to calculate the kinetic parameters for the different kininogenase activities. Physicochemical and pharmacological characterization of immunoreactive kinins confirm their nature. The kinetic profile of kinin generation was studied during the process of coagulation which was initiated with kaolin or with tissue factor and monitored by thromboelastography. RESULTS. BK was released not only by plasma kallikrein; both plasmin and factor Xa hydrolyzed high molecular kininogen to produce BK. In the case of thrombin, the release of both BK and kallidin was detected from low and high molecular weight kininogen. When applied to whole blood, this analytical approach indicated that the kinin-forming capacity of the coagulation intrinsic pathway was higher than that of the extrinsic pathway. The triggering of fibrinolysis by tissue plasminogen activator dramatically potentiated the release of des-Arg9-BK. CONCLUSIONS. Although plasma kallikrein is considered as being the main kinin-forming enzyme, other serine proteases of the coagulation and the fibrinolysis pathways are able to generate kinins and could play a role in different pathologies where kinins are potentially involved.
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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".