Studies of α-granule proteins in cultured human megakaryocytes
Bibliographic record
Abstract
alpha-Granule protein storage is important for producing platelets with normal haemostatic function. The low to undetectable levels of several megakaryocyte-synthesized alpha-granule proteins in normal plasma suggest megakaryocytes are important to sequester these proteins in vivo. alpha-Granule protein storage in vitro has been studied using other cell types, with differences observed in how some proteins are processed compared to platelets. Human megakaryocytes, cultured from cord blood CD34(+) cells and grown in serum-free media containing thrombopoietin, were investigated to determine if they could be used as a model for studying normal alpha-granule protein processing and storage. ELISA indicated that cultured megakaryocytes contained the alpha-granule proteins multimerin, von Willebrand factor, thrombospondin-1, beta-thromboglobulin and platelet factor 4, but no detectable fibrinogen and factor V. A significant proportion of the alpha-granule protein in megakaryocyte cultures was contained within the cells (averages: 41-71 %), consistent with storage. Detailed analyses of multimerin and von Willebrand factor confirmed that alpha-granule proteins were processed to mature forms and were predominantly located in the alpha-granules of cultured megakaryocytes.Thrombopoietin-stimulated cultured megakaryocytes provide a useful model for studying alpha-granule protein processing and storage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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".