Hsa_circ_0101432 promotes the development of hepatocellular carcinoma (HCC) by adsorbing miR-1258 and miR-622
Bibliographic record
Abstract
The present research was major in investigating the regulation association among hsa_circ_0101432 (has_circ_RPPH1), miR-1258, miR-622 and MAPK1 in hepatocellular carcinoma (HCC), and we explored the mechanism underlying pathogenesis of HCC. Microarray analysis was employed to detect hsa_circ_0101432 expression in HCC. Hsa_circ_0101432 was verified as a circRNA by testing divergent primers and RNase R. And qRT-PCR was performed to determine the expression of hsa_circ_0101432, miR-1258, miR-622 and MAPK1 mRNA. Furthermore, miRanda predicted that mRNAs targeted miR-1258 and miR-622. CCK-8 assay, colony formation assay, flow cytometry as well as transwell assay were performed to detect cell viability, proliferation, apoptosis and invasive ability, respectively. Xenograft in nude mice was applied to observe tumor growth in vivo. Up-regulated hsa_circ_0101432 and down-regulated miR-1258 and miR-622 were detected in HCC while Hsa_circ_0101432 enhanced expression of MAPK1 mRNA by targeting miR-1258 and miR-622. Knocking down hsa_circ_0101432 or overexpressing miR-1258 and miR-622 inhibited proliferation and invasive ability of HCC cell and promoted cell apoptosis. Hsa_circ_0101432 was confirmed to promote tumor growth via inhibiting miR-1258 and miR-622 expression and promoting MAPK1 mRNA expression by in vivo experiment. Hsa_circ_0101432 inhibited HCC cell apoptosis, promoted cell proliferation, invasive ability and HCC tumor growth by targeting miR-1258 and miR-622 and upregulating MAPK1 mRNA expression.
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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".