Bibliographic record
Abstract
Structurally, aquaporins (AQPs) are small channel proteins with monomers of ~ 30 kDa that are assembled as tetramers to form pores on cell membranes. Aquaporins mediate the conduction of water but at times also small solutes including glycerol across cell membranes and along osmotic gradients. Thirteen isoforms of AQPs have been reported in mammalian cells, and several of these are likely expressed in platelets. Osmotic swelling mediated by AQP1 sustains the calcium entry required for platelet phosphatidylserine exposure and microvesiculation, through calcium permeable stretch-activated or mechanosensitive cation channels. Notably, deletion of AQP1 diminishes platelet procoagulant membrane dynamics in vitro and arterial thrombosis in vivo, independent of platelet granule secretion and without affecting hemostasis. Water entry into platelets promotes procoagulant activity, and AQPs may also be critical for the initiation and progression of venous thrombosis. Platelet AQPs may therefore represent valuable targets for future development of a new class of antithrombotics, namely, anti-procoagulant antithrombotics, that are mechanistically distinct from current antithrombotics. However, the structure of AQPs does not make for easy targeting of these channels, hence they remain elusive drug targets. Nevertheless, thrombosis data in animal models provide compelling reasons to continue the pursuit of AQP-targeted antithrombotics. In this review, we discuss the role of aquaporins in platelet secretion, aggregation and procoagulation, the challenge of drugging AQPs, and the prospects of targeting AQPs for arterial and venous antithrombosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".