Involvement of MEK, ERK, PKC and GSK3B in Maintaining the Mitotic Spindle
Bibliographic record
Abstract
The MAPK pathway has been implicated in various functions related to cell cycle regulation. MAPKK (MEK) is part of this pathway and the extracellular regulated kinase (ERK) is its known downstream target. Glycogen synthase kinase 3B (GSK3B) and protein kinase C (PKC) also have been implicated in cell cycle regulation due to their association with the centrosomes along with MEK and ERK. In the current study, we tested the effects of inhibiting MEK on the activities of ERK, GSK3B, PKC, and ?-tubulin. Two types of MEK inhibitors were used, a siRNA inhibitor and U0126. The effects of MEK inhibition were tested by immunocytochemistry and confocal analysis, western blotting, RT-PCR analysis and study of cell numbers in M-phase stages. Results from this study indicate that inhibition of MEKdid not inhibit GSK3B and PKC enrichment at the centrosomes. However, the mitotic spindle showed a reduction in the pixel intensity of microtubules and also a reduction in the number of cells in each of the M-phase stages. A peptide activation inhibitor of ERK was used next. Our results indicated a further decrease in mitotic spindle microtubules than what was seen with the MEK inhibitors and an absence of cells in most of the M-phase stages. GSK3B and PKC enrichment were however not inhibited at the centrosomes. Taken together, the kinases GSK3B and PKC may not function as a part of the MAPK pathway to regulate the mitotic spindle.
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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".