Factors limiting autogene‐based cytoplasmic expression systems
Bibliographic record
Abstract
The relatively low levels of transfection that can be achieved by current gene delivery systems have limited the therapeutic utility of gene transfer. This is especially true for non-viral gene delivery systems, where the levels of gene expression achieved are usually well below the levels achieved by viral gene transfer systems. Previous work from our laboratory describes an enhanced dual promoter autogene-based cytoplasmic expression system that gives rise to levels of gene expression 20-fold higher than that of a CMV nuclear expression plasmid control. Here various strategies are described to increase the levels of autogene-based gene expression by changing variables such as the type of nuclear promoter, phage RNAP gene, and IRES element. Although insights into the function of various IRES elements were gained, none of these changes demonstrated a significant increase in gene expression. However, determination of the mRNA levels achieved using quantitative RNase protection assays and immunofluorescence experiments revealed that transgene mRNA levels were saturated at up to 10 times higher than all other mRNA in the transfected cell combined. It follows that mRNA production, as well as translation, are important factors limiting autogene-based cytoplasmic expression.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".