Effects of survivin interference RNA on non-small cell lung carcinoma
Bibliographic record
Abstract
OBJECTIVES: The primary purpose of this study was to investigate the in vitro and in vivo effect of survivin interference RNA (siRNA) on non-small cell lung cancer. METHODS: Lentivirus was used as a vector to transfer siRNA into human lung cancer A549 cells. The proliferation of the cancer cells was assessed by MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay. The lentivirus-mediated siRNA was also injected into the transplanted A549 tumor tissues in mice. Tumour growth was assessed after 11 injections over a period of 21 days. RESULTS: Compared with the placebo and the blank lentiviral vector groups, the siRNA treatment group had reduced cell growth rate following 4 days of the treatment (P < 0.01). The average size of the transplanted A549 tumours in the siRNA treatment group (0.75+/-0.16 cm3, n=8) was smaller than in the placebo (2.09+/-0.22 cm3, n=6) or the blank lentivrial vector groups (1.89+/-0.18 cm3, n=6) (P < 0.01). The tumour growth inhibition rate in the siRNA groups was 46.1%. CONCLUSION: Lentivirus-mediated siRNA therapy inhibits the growth of human lung cancer cells in vitro. The siRNA therapy also suppresses the growth of the transplanted lung cancer in mice.
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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".