Exploring the interaction environment of blood cells : proteomic analysis of platelet releasate and platelet-monocyte interaction
Bibliographic record
Abstract
Platelet-monocyte aggregates circulating in the blood are found to play an important role in cardiovascular disease, the most common cause of death in Canada, and are now an established early marker of acute events. Upon stimulation, monocytes transmigrate across the endothelial layer into the intima where they take up oxidized low density lipoproteins (LDL) and differentiate into macrophages, and are then incorporated into atherosclerotic plaques. Upon plaque rupture, which accounts for the majority of fatal cardiovascular incidents, platelets are exposed to a variety of agonists such as collagen and mildly oxidized LDL. We used dimethyl labeling quantitative proteomics approach to determine the relative abundance of platelet releasate (Rel) proteins from platelets activated with thrombin, collagen or Lysophosphatidic acid (LPA; the most potent platelet activator found in mildly oxidized LDL). Using the different agonists led to releasates with unique protein compositions. In addition, we analyzed the relative abundance of protein in releasate free of microparticles (Rel-MP) when using the different agonists. Flow cytometry and proteomics studies showed that thrombin, collagen or LPA activated platelets not only produce different number of platelet microparticles (MP), but that these MP have different proteome profiles. We studied the effects of combining agonists by activating platelets with thrombin plus collagen or a subthreshold concentration of collagen plus LPA. Through biologic functional studies we saw that the Rel, Rel-MP or MP from the platelets activated with the different agonists lead to different degree of THP-1 cell migration. We added the contents released from thrombin activated platelets to a human monocytic cell line THP-1, in order to find the proteins which are responsible for THP-1 cell stimulation. Based on the increased expression of proteins such as integrin β1, we found that, adding platelet releasate induces a pro-inflammatory state in THP-1 cells and prime them for transmigration. Therefore, we have taken considerable strides towards uncovering the effect of platelet activation on monocyte protein expression. The findings may aid in discovery of drug targets for prevention of inappropriate platelet activation and platelet-monocyte aggregate formation, in order to dampen the effects of these events in contributing to cardiovascular disease.
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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".