Improving transgene expression and CRISPR‐Cas9 efficiency with molecular engineering‐based molecules
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As a novel and robust gene-editing tool, the Clustered Regularly Interspaced Short Palindromic Repeats CRISPR-associated protein 9 (CRISPR-Cas9) system has revolutionized gene therapy. Plasmid vector delivery is the most commonly used method for integrating the CRISPR-Cas9 system into cells. However, such foreign cytosolic DNAs trigger an innate immune response (IIR) within cells, which can hinder gene editing by inhibiting transgene expression. Although some small molecules have been shown to avoid the action of IIR on plasmids, they only work on a single target and may also affect cell viability. A genetic approach that works at a comprehensive level for manipulating IIR is still lacking. Here, we designed and constructed several artificial nucleic acid molecules (ANAMs), which are combinations of aptamers binding to two key players of IIR (β-catenin and NF-κB). ANAMs strongly inhibited the IIR in cells, thus improving transgene expression. We also used ANAMs to improve the gene-editing efficiency of the CRISPR-Cas9 system and its derivatives, thus enhancing the apoptosis of cancer cells induced by CRISPR-Cas9. ANAMs can be valuable tools for improving transgene expression and gene editing in mammalian cells.
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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) | 0.000 | 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) | 0.000 | 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 it