MiR-301b promotes the proliferation, mobility, and epithelial-to-mesenchymal transition of bladder cancer cells by targeting <i>EGR1</i>
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 role of miR-301b in the modulation of the proliferation, migration, and invasion of bladder cancer (BLCA) cells. The expression of miR-301b and EGR1 (early growth response gene 1) mRNA were analyzed by quantitative real-time polymerase chain reaction (qRT-PCR). A dual-luciferase reporter gene system was used to identify the target relationship between miR-301b and EGR1. Cell proliferation, cell cycle, and apoptosis were analyzed by MTT assay, colony-forming assay, and flow cytometry, respectively. Cell motility and invasiveness were assessed by wound healing and Transwell assays. The expression of proteins involved in epithelial-to-mesenchymal transition (EMT) and EGR1 were determined by Western blot. Our results showed that miR-301b was up-regulated while EGR1 was down-regulated in BLCA tissues compared with adjacent normal tissues. The proliferation, migration, and invasiveness of T24 cells (a kind of human BLCA cell) were suppressed by decreasing miR-301b expression or increasing EGR1 expression. In addition, miR-301b promoted EMT signaling by influencing the expression of related proteins. In conclusion, miR-301b promotes the proliferation, migration, and aggressiveness of human BLCA cells by inhibiting the expression of EGR1.
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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 | 0.001 |
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".