Programmed cell death 4 (PDCD4) suppresses metastastic potential of human hepatocellular carcinoma cells
Bibliographic record
Abstract
BACKGROUND: Hepatocellular carcinoma (HCC) is a lethal malignancy with high rate of metastasis and poor prognosis. There are no effective managements to block metastasis of HCC. Programmed cell death 4 (PDCD4) is found to be a tumor transformation suppressor. Among investigations on effects of PDCD4, little is about the metastatic potentials of HCC cells. This study was to investigate the role of PDCD4 on metastatic potential of human HCC cells. METHODS: We examined the expression of PDCD4 in three HCC cell lines with different metastatic potentials, MHCC-97H (high metastatic potential), MHCC-97L (low metastatic potential) and Hep3B (no metastatic potential). A plasmid encoding PDCD4 gene was constructed and then transfected into HCC cells with the lowest PDCD4 expression level. Effects of PDCD4 on cell proliferation, cell apoptosis, gene expression of metastasis tumor antigen 1 (MTA1) and in vitro migration and invasion capacity were assessed after transfection. RESULTS: Our results showed that the expression level of PDCD4 was inversely correlated to the metastatic potential of HCC cells. After transfection with the PDCD4 gene, HCC cell proliferation rate was significantly decreased, cell apoptosis rate was significantly increased, the expression of MTA1 gene, HCC cell migration and Matrigel invasion were also remarkably inhibited. CONCLUSION: PDCD4 expression is inversely correlated to the metastatic potential of HCC cells. PDCD4 can effectively suppress the metastatic potential of HCC cells.
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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".