Functions of Platelet Microparticles in Inflammatory Arthritis
Bibliographic record
Abstract
Abstract Abstract SCI-35 Besides their pivotal role in thrombosis and wound repair, platelets can participate in inflammatory responses via a broad arsenal that includes CD40L and CD40, cyclooxygenase-1 mediated prostaglandins, leukotrienes, IL-1, RANTES, serotonin, platelet factor 4, matrix metalloproteinases -2 and -9, P-selectin, adenosine diphosphate, and reactive oxygen species. Rheumatoid arthritis (RA) is amongst the most common autoimmune chronic inflammation that affects the joints. Interestingly, we found copious amounts of submicron particles that harbor platelet integrins in the synovial fluid of patients suffering from RA, pointing to evidence of platelet activation in this inflammatory autoimmune disease. Importantly, we identified the collagen receptor glycoprotein VI as a key trigger for platelet microparticle generation in arthritis pathophysiology. In addition to the transcellular collaboration between platelets and fibroblast-like synoviocytes in generation of pro-inflammatory prostacyclin (1), we found that platelets contribute to synovitis by production of IL-1-rich platelet microparticles (2). These recent advances in understanding of the platelet activities in inflammation notwithstanding, the mechanisms by which platelet microparticles invade the diseased joint in RA remain obscure. Using synovial biopsies from patients suffering from RA in addition to in vivo imaging strategies in a murine model of arthritis, our current work aspires to dissect the means of transportation of platelet microparticles during RA. Given their pro-inflammatory properties, to understand the process by which microparticles invade the synovial joint is of great clinical interest. Disclosures: No relevant conflicts of interest to declare.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".