Correction: Transcriptional and Post-Transcriptional Mechanisms for Oncogenic Overexpression of Ether À Go-Go K<sup>+</sup>Channel
Bibliographic record
Abstract
The human ether-a `-go-go-1 (h-eag1) K + channel is expressed in a variety of cell lines derived from human malignant tumors and in clinical samples of several different cancers, but is otherwise absent in normal tissues.It was found to be necessary for cell cycle progression and tumorigenesis.Specific inhibition of h-eag1 expression leads to inhibition of tumor cell proliferation.We report here that h-eag1 expression is controlled by the p532miR-342E2F1 pathway through a negative feed-forward mechanism.We first established E2F1 as a transactivator of h-eag1 gene through characterizing its promoter region.We then revealed that miR-34, a known transcriptional target of p53, is an important negative regulator of h-eag1 through dual mechanisms by directly repressing h-eag1 at the post-transcriptional level and indirectly silencing h-eag1 at the transcriptional level via repressing E2F1.There is a strong inverse relationship between the expression levels of miR-34 and h-eag1 protein.H-eag1antisense antagonized the growth-stimulating effects and the upregulation of h-eag1 expression in SHSY5Y cells, induced by knockdown of miR-34, E2F1 overexpression, or inhibition of p53 activity.Therefore, p53 negatively regulates h-eag1 expression by a negative feed-forward mechanism through the p532miR-342E2F1 pathway.Inactivation of p53 activity, as is the case in many cancers, can thus cause oncogenic overexpression of h-eag1 by relieving the negative feed-forward regulation.These findings not only help us understand the molecular mechanisms for oncogenic overexpression of h-eag1 in tumorigenesis but also uncover the cell-cycle regulation through the p532miR-342E2F12h-eag1 pathway.Moreover, these findings place h-eag1 in the p532miR-342E2F12h-eag1 pathway with h-eag as a terminal effecter component and with miR-34 (and E2F1) as a linker between p53 and h-eag1.Our study therefore fills the gap between p53 pathway and its cellular function mediated by h-eag1.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.081 | 0.030 |
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".