MicroRNA-30 mediates cell invasion and metastasis in breast cancer
Bibliographic record
Abstract
Despite the great progress in recent years, many aspects of the pathogenesis and progression of breast cancer remain unclear. A better understanding on the molecular mechanisms underlying metastasis and recurrence is crucial to improve the treatment of this lethal disease. MCF-7 cells were xenografted into mice until visible tumors developed, and the cells from tumor tissue and adjacent normal tissue were cultured with 3 passages as mass tumor (MT) cells and invasive tumor (IT) cells, respectively. Microarray analysis was performed to detect several viable microRNAs in these 2 types of cells. Further, miR-30 knockdown was used to investigate its role in tumor aggression. Relative levels of miR-30 were significantly higher in IT cells than MT cells. Knockdown of miR-30 in both MT and IT cells lowered cell proliferation and cell invasion abilities, and thus increased the survival time of mice xenografted with tumor cells. This study suggested that the knockdown of miR-30 decreased proliferation and invasion of carcinoma cells, giving rise to the potential of miR-30 as a tumor target or marker candidate for breast cancer therapy.
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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".