Platelet generation from circulating megakaryocytes is triggered in the lung vasculature
Bibliographic record
Abstract
Abstract Platelets are small anucleate blood cells1,2 with critical roles in haemostasis, thrombosis, inflammation, vascularization, innate immunity and tissue regeneration3,4. In vitro-derived platelets, as an alternative to native platelets, are attractive for fundamental research because of their rapid genetic tractability, as vectors for drug and genetic component delivery5 and in clinical platelet transfusion. At present, however, their very low production rate, and poor agonist responsiveness, are major obstacles. Platelets are formed by fragmentation from mature polyploid megakaryocytes (MKs), their precursor cells6, although the process of their generation remains incompletely understood7,8. Bone marrow is proposed to be the main site of platelet production, however indirect evidence since the 1930s9,10 and recent direct observation11 has shown that the lung can also be a primary site of platelet biogenesis. Here we established an ex vivo mouse heart-lung model (Fig. 1a) through which we were able to perfuse murine MKs. Remarkably, we could show for the first time that MKs, despite their large size, can pass multiple times through the lung vasculature, and that this leads to the generation of very large numbers of fully functional platelets (up to 3,000 per megakaryocyte7,12). Using this system and a novel in vitro microfluidic chamber we show roles for ventilation, oxygenation and healthy pulmonary endothelial cells in platelet generation. We show that MKs undergo enucleation upon repeated passage through pulmonary vasculature before fragmentation to generate platelets, with this final process dependent on the actin regulator TPM4. This advances our understanding of platelet formation in the body and establishes a novel approach to generate large numbers of them outside the body.
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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 | 0.001 |
| 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".