Editorial: Current approaches to CRISPR/Cas9 delivery
Bibliographic record
Abstract
Effective use of the CRISPR technologies requires a good understanding of the guide sequences, whose selectivity and efficacy have to be optimized to identify the right nucleotide sequences for editing. The enzymes capable of undertaking the genomic cleavage have to be similarly efficient and error-free when undertaking the required editing reactions. Very active and competitive research is underway to tackle these challenges and the biotechnology industry has spun several leading companies whose goal is to commercialize the full potential of CRISPR technology. Coupled with this endeavor, effective delivery systems are sought to transport the gene editing cargo to their site of action. The required cargo could be derived from different molecules, short oligonucleotides, long nucleic acid molecules derived from DNA or RNA, and active proteins ready to undertake enzymatic reactions. The diversity of the possible CRISPR enabling molecules will likely require different types of delivery systems that may have to be optimized for different cargo. Nevertheless, viral vectors have found initial utility to undertake the required delivery, given their broad applicability and efficient delivery mechanism as a result of evolutionary process, especially in the absence (or reduced) of safety concerns typical of cell culture and preclinical animal models. Some of the viral systems have been already translated into the clinical setting with careful attention to safety aspects of such a delivery mode. Non-viral approaches to delivery are taking flight as well to realize the full clinical potential of CRISPR, offering reduced safety concerns as compared to the use of viruses in patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".