Editorial: Current approaches to CRISPR/Cas9 delivery
Bibliographic record
Abstract
Current approaches to CRISPR/Cas9 deliveryEffective 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.This special issue has been compiled to highlight the recent developments in the CRISPR field.Six manuscripts have been compiled under the "Current Approaches to CRISPR/Cas9 Delivery" theme, originating from researchers in widely different geographic locations, including Russia, Ethiopia, China and United States.To provide a background on CRISPR and various opportunities, Shakirova et al. summarized the currently existing CRISPR/Cas9 applications with an eye on cell reprogramming.They have been compared with other non-CRISPR approaches and future perspectives and opportunities were highlighted.The review provides a glimpse into the evolution of cell
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.014 | 0.014 |
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".