miR-96 targets <i>SOX6</i> and promotes proliferation, migration, and invasion of hepatocellular carcinoma
Bibliographic record
Abstract
Recent research suggested that microRNA 96 (miR-96) might function as an oncogene in several types of cancers. Therefore, the purpose of this study was to probe into the mechanism of miR-96 in hepatocellular carcinoma (HCC) cells. HCC tissues and non-tumorous tissues, HCC cell lines, and healthy cell lines were all involved in this study. Quantitative real-time PCR (qRT-PCR) and Western blot were used to detect miR-96 and SOX6 mRNA and protein expressions. The direct regulation of miR96 on SOX6 was confirmed by luciferase reporter assays. Cell proliferation and growth were determined by MTT (3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide) assay and colony formation assay. Wound healing and transwell assay were employed for migration and invasion analyses. Finally, SPSS 21.0 and GraphPad 7.0 were applied for statistical analyses. In HCC tissues, miR-96 was highly expressed while SOX6 was lowly expressed. The overexpression of miR-96 reversely inhibited the expression of SOX6, contributing to the promotion of the biological functions of HCC cells. miR-96 could promote cell proliferation, migration, and invasion in HCC by targeting SOX6.
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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) | 0.002 | 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".