MicroRNA-181 inhibits proliferation and promotes apoptosis of chondrocytes in osteoarthritis by targeting <i>PTEN</i>
Post-publication record
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Bibliographic record
Abstract
OBJECTIVE: To investigate the effects of microRNA-181 (miR-181) on the proliferation and apoptosis of chondrocytes in osteoarthritis (OA) by targeting PTEN. METHODS: The chondrocytes in logarithmic growth phase were selected and divided into 6 test groups: the normal, blank, negative control, miR-181 mimic, miR-181 inhibitor, and miR-181 inhibitor + PTEN-siRNA groups. Reverse transcription qPCR was used to detect the expressions of miR-181 and PTEN mRNA. MTT assay and flow cytometry were performed to detect cell proliferation and apoptosis. The protein expressions of PARP and caspase-3 and the activity of MMP-2 and MMP-9 were detected by Western blotting and gelatin zymography assay. RESULTS: The miR-181 mimic group showed increased miR-181 expression and decreased PTEN expression compared with the other 5 groups. Also, by comparison with the other 5 groups, the cell proliferation rate declined and the rate of cell apoptosis was elevated in the miR-181 mimic group. The MiR-181 mimic group showed remarkably increased protein expression of caspase-3 and PARP compared with the other 5 groups. The activity of MMP-2 and MMP-9 was higher in the miR-181 mimic group than the other 5 groups. CONCLUSION: MiR-181 could up-regulate the expressions of caspase-3, PARP, MMP-2, and MMP-9, and thereby inhibit cell proliferation and promote apoptosis of chondrocytes in OA by targeting PTEN.
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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 | 0.001 |
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".