Knockdown Strategies for the Study of Proprotein Convertases and Proliferation in Prostate Cancer Cells
Bibliographic record
Abstract
Gene silencing strategies targeting mRNA are suitable methods to validate the functions of specific genes. In this chapter, we sought to compare two knockdown strategies for the study of proprotein convertases and proliferation in prostate cancer cells. We used both SOFA-HDV ribozyme and lentiviral-mediated shRNA delivery system to reduce PACE4 mRNA levels and validate its implication in the proliferation of DU145 prostate cancer cells. The cellular effects of PACE4 knockdown were assessed (1) in vitro using two tetrazolium salts (MTT and XTT assays) and (2) in vivo using a tumor xenograft approach in immunodeficient mice (Nu/Nu). Our results confirm the unique role of the proprotein convertase PACE4 in prostate cancer cell proliferation while demonstrating advantages and disadvantages of each approach. Achieving target validation in an effective manner is critical, as further development using a drug development approach is highly laborious and requires enormous resources.
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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 | 0.001 |
| 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".