Ganglioside GM3 is required for caffeic acid phenethyl ester-induced megakaryocytic differentiation of human chronic myelogenous leukemia K562 cells
Bibliographic record
Abstract
The human chronic myelogenous cell line K562 has been used extensively as a model for the study of leukemia differentiation. We show here that treatment of K562 cells with caffeic acid phenethyl ester (CAPE) induced a majority of cells to differentiate towards the megakaryocytic lineage. Microscopy analysis showed that K562 cells treated with CAPE exhibited characteristic features of physiological megakaryocytic differentiation, including the presence of vacuoles and demarcation membranes. Differentiation of K562 cells treated with CAPE was also accompanied by a net increase in megakaryocytic markers. The transcriptional activity of lactosylceramide α-2,3-sialyltransferase (GM3 synthase) and synthesis of ganglioside GM3 were increased by CAPE treatment. The promoter analysis of GM3 synthase demonstrated that CAPE induced the expression of GM3 synthase mRNA via activation of the cAMP response element-binding protein (CREB), transcription factor in nucleus. Interestingly, the inhibition of ganglioside GM3 synthesis by D-threo-1-phenyl-2-decanoylamino-3-morpholino-1-propranol (D-PDMP) and GM3 synthase-siRNA blocked the CAPE-induced expression of the megakaryocytic markers and differentiation of K562 cells. Taken together, these results suggest that CAPE induces ganglioside GM3-mediated megakaryocytic differentiation of human chronic myelogenous cells.
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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 | 0.000 |
| 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".