MiR-204 suppresses cell proliferation and promotes apoptosis in ovarian granulosa cells via targeting TPT1 in polycystic ovary syndrome
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
MicroRNA (miR)-204 is known to be associated with several different diseases. Polycystic ovary syndrome (PCOS) has the highest incidence rate among the endocrine disorders in females between the ages of 18 and 44. We aimed to illustrate the miR-204 function in PCOS. MiR-204 expression levels in tissue and cell were examined through RT-qPCR. Colony formation assay and MTT assay were applied to detect the cell viability. Flow cytometry was employed to examine the apoptosis and cell cycle in cells. RNA binding protein immunoprecipitation assay and luciferase reporter assay were provided to demonstrate the direct interaction between translationally controlled tumor protein (TPT1) and miR-204. The expression of miR-204 was declined in KGN cells and ovarian cortex tissues of PCOS patients. MiR-204 enhanced the colony formation capacity and cell proliferation in KGN cells. Cell cycle and apoptosis were also influenced by miR-204. Since miR-204 has direct interaction with TPT1, TPT1 overexpression suppressed the miR-204-induced apoptosis and cell cycle alteration in KGN cells. MiR-204 inhibits the cell viability and induces apoptosis and cell cycle arrest by directly interacting with TPT1, indicating a role of miR-204 to be a potential target in the PCOS patients.
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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".