MicroRNA-10b controls the metastasis and proliferation of colorectal cancer cells by regulating Krüppel-like factor 4
Bibliographic record
Abstract
Mir-10b has been reported as a key regulator of metastasis in many human tumours. Moreover, it has also been regarded as a prognostic marker and therapeutic target of colorectal cancer (CRC). Whether miR-10b could affect the metastasis and proliferation of CRC is unclear. MiR-10b expression was detected by qPCR in human CRC tissues and cell line, Luciferase activity was employed for miR-10b binding to the 3`UTR of KLF4, Genes expression were examined by western blot, and mRNA by qPCR. PI and Annexin V staining were used to evaluate the cell cycle and apoptosis. Cell proliferation was detected with MTT, and cell migration and invasion were performed with Transwell assay. We found that miR-10b expression was up-regulated in metastatic CRC tissues and cell lines. Inhibition of miR-10b prevented cancer cell metastasis and growth by inducing cell-cycle arrest and apoptosis in vitro. Moreover, we found that KLF4 was a direct target of miR-10b. MiR-10b inhibitor led to the up-regulation of E-cadherin expression and the down-regulation of cyclin D1, which were partly abrogated after silencing KLF4.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.010 |
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".