Bibliographic record
Abstract
The goal of suicide gene therapy is the specific expression of a toxic gene in cancer cells. In order to achieve this objective, vehicles and transfection strategies must be designed to specifically deliver suicide genes to the desired cells. Up to now, the use of bacteria and other micro-organisms, viruses, and nonviral liposomes as well as the transfection of naked DNA have all been explored as methods of introducing foreign DNA into cells. This chapter describes the use of peptides, proteins, and polymers in the formulation of nonviral transfection agents. A number of recent reviews have outlined the advantages and disadvantages of nonviral systems to deliver therapeutic agents (1–3) and genes (4–9). One advantage of these vectors over viral systems is the diversity of agents that can be used. Unlike viruses, which often lack cell specificity, the potential exists to tailor the delivery of peptide- or polymer-based vectors to target cells of interest. On the other hand, viruses are advantageous in that they have evolved to use natural mechanisms to enter cells and their DNA is packaged to induce the expression of foreign genes. The efficient delivery and expression of novel genes can also be achieved with nonviral systems. Many of the agents discussed in this chapter, however, remain under development and are not commercially available. Nonetheless, there exists a great potential for the use of peptide- and polymer-based delivery agents in clinical applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".