<scp>E</scp>pstein–<scp>B</scp>arr virus‐encoded <scp>LMP</scp>1 triggers regulation of the <scp>ERK</scp>‐mediated <scp>O</scp>p18/stathmin signaling pathway in association with cell cycle
Bibliographic record
Abstract
The MAPKs are activated by a variety of cellular stimuli to participate in a series of signaling cascades and mediate diverse intracellular responses. One potential target of the MAPKs is Op18/stathmin, a molecule that acts as an integrator of diverse cell signaling pathways and regulates the dynamics of microtubules, which are involved in modulating a variety of cellular processes, including cell cycle progression and cell growth. Our study focused on the regulation of the MAPK-mediated Op18/stathmin signaling pathway, which is triggered by the Epstein-Barr virus-encoded latent membrane protein 1 ( LMP1) oncogene in nasopharyngeal carcinoma cells. The results showed that the activity of MAPK, which was induced by LMP1, varied with cell cycle progression; LMP1 upregulated phosphorylation of ERK during the G(1)/S phase, but negatively regulated phosphorylation of ERK during the G(2)/M phase. We found that the regulation of Op18/stathmin signaling by LMP1 was mainly mediated through ERK. The inhibition of LMP1 expression attenuated the interaction of ERK with Op18/stathmin and promoted microtubule depolymerization. These findings indicate the existence of a new cell cycle-associated signaling pathway in which LMP1 regulates ERK-mediated Op18/stathmin signaling.
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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) | 0.001 | 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".