Updated Understanding of Platelets in Thrombosis and Hemostasis: The Roles of Integrin PSI Domains and their Potential as Therapeutic Targets
Bibliographic record
Abstract
Platelets are small blood cells known primarily for their ability to adhere and aggregate at injured vessels to arrest bleeding. However, when triggered under pathological conditions, the same adaptive mechanism of platelet adhesion and aggregation may cause thrombosis, a primary cause of heart attack and stroke. Over recent decades, research has made considerable progress in uncovering the intricate and dynamic interactions that regulate these processes. Integrins are heterodimeric cell surface receptors expressed on all metazoan cells that facilitate cell adhesion, movement, and signaling, to drive biological and pathological processes such as thrombosis and hemostasis. Recently, our group discovered that the plexin-semaphorin-integrin (PSI) domains of the integrin β subunits exert endogenous thiol isomerase activity derived from their two highly conserved CXXC active site motifs. Given the importance of redox reactions in integrin activation and its location in the knee region, this PSI domain activity may be critically involved in facilitating the interconversions between integrin conformations. Our monoclonal antibodies against the β3 PSI domain inhibited its thiol isomerase activity and proportionally attenuated fibrinogen binding and platelet aggregation. Notably, these antibodies inhibited thrombosis without significantly impairing hemostasis or causing platelet clearance. In this review, we will update mechanisms of thrombosis and hemostasis, including platelet versatilities and immune-mediated thrombocytopenia, discuss critical contributions of the newly discovered PSI domain thiol isomerase activity, and its potential as a novel target for anti-thrombotic therapies and beyond.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".