PLCβ1a and PLCβ1b Selective Regulation and Cyclin D3 Modulation Reduced by Kinamycin F During K562 Cell Differentiation
Bibliographic record
Abstract
Here we report that both PLCβ1a and PLCβ1b are relevant regulators of erythropoiesis in that kinamycin F, a potent inducer of γ-globin production in K562 cells, caused a selectively reduction of both PLCβ1 isozymes even though the results point out that the effect of the drug is mainly directed toward the expression of the PLCβ1a isoform. We have identified a different role for the two isozymes as regulators of K562 differentiation process induced by kinamycin F. The overexpression of PLCβ1b induced an increase in γ-globin expression even in the absence of kinamycin F. Moreover during K562 differentiation, cyclin D3 level is regulated by PLCβ1 signaling pathway. Namely the amplification of the expression of the PLCβ1a, but not of PLCβ1b, is able to maintain high levels of expression of cyclin D3 even after treatment with kinamycin F. This could be due to their different distribution in the cell compartments since the amount of PLCβ1b is mainly present in the nucleus in respect to PLCβ1a. Our data indicate that the amplification of PLCβ1a expression, following treatment with kinamycin F, confers a real advantage to K562 cells viability and protects cells themselves from apoptosis.
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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 | 0.000 |
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".