Interaction between miR-572 and PPP2R2C, and their effects on the proliferation, migration, and invasion of nasopharyngeal carcinoma (NPC) cells
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
We investigated the how miR-572 regulates PPP2R2C, and studied the effects of miR-572 and PPP2R2C on proliferation and migration as well as invasion of nasopharyngeal carcinoma (NPC) cells. NPC tissues and normal tissues were collected, and the expressions of miR-572 and PPP2R2C were detected by real-time PCR. Western blot was applied to detect the expression of PPP2R2C protein. The target relationship between miR-572 and PPP2R2C was confirmed by dual luciferase reporter gene assay. MTT assay and flow cytometry were applied to investigate the viability and apoptosis levels of NPC cells. Transwell as well as wound healing assays were used, respectively, to detect the invasiveness and migration of NPC cells. MiR-572 was highly expressed in NPC tissues as well as NPC cells, and there was lower expression of PPP2R2C in NPC tissues compared with normal samples. MiR-572 could bind to the 3' UTR of PPP2R2C and decrease its expression. Over-expressed miR-572 and decreased PPP2R2C expression could both inhibit proliferation and invasion and induce apoptosis of NPC cells. Thus, miR-572 promotes the proliferation and invasion of NPC by directly down-regulating PPP2R2C.
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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) | 0.001 | 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".