Rho kinase inhibition drives megakaryocyte polyploidization and proplatelet formation through <i><scp>MYC</scp></i> and <i><scp>NFE</scp>2</i> downregulation
Bibliographic record
Abstract
The processes of megakaryocyte polyploidization and demarcation membrane system (DMS) formation are crucial for platelet production, but the mechanisms controlling these processes are not fully determined. Inhibition of Rho kinase (ROCK) signalling leads to increased polyploidization in umbilical cord blood-derived megakaryocytes. To extend these findings we determined the effect of ROCK inhibition on development of the DMS and on proplatelet formation. The underlying mechanisms were explored by analysing the effect of ROCK inhibition on the expression of MYC and NFE2, which encode two transcription factors critical for megakaryocyte development. ROCK inhibition promoted DMS formation, and increased proplatelet formation and platelet release. Rho kinase inhibition also downregulated MYC and NFE2 expression in mature megakaryocytes, and this down-regulation correlated with increased proplatelet formation. Our findings suggest a model whereby ROCK inhibition drives polyploidization, DMS growth and proplatelet formation late in megakaryocyte maturation through downregulation of MYC and NFE2 expression.
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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) | 0.002 | 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".