Precise template-free correction restores gene function in Tay-Sachs disease while reframing is ineffective
Bibliographic record
Abstract
expression by frameshift. In an engineered cell model, we explore the use of CRISPR-Cas9 for therapeutic editing of c.1278insTATC. Within genomic microduplications, the microhomology-mediated end joining (MMEJ) pathway is favored to repair double-stranded breaks with collateral deletion of one repeat. Protospacer adjacent motif (PAM) constraints on Cas9 endonuclease activity prevented cleavage at the duplication center, the optimal position for MMEJ initiation. Rather, cleavage 1 bp from the c.1278insTATC duplication center spontaneously reconstructed the wild-type sequence at ∼14.7% frequency, with concomitant restoration of normal cellular HexA activity. As an alternative to perfect correction, short insertions or deletions were serially introduced to restore an open reading frame across a 19-bp sequence encompassing c.1278insTATC. Frame-restored variants did not recover significant HexA function, presumably due to structural incompatibility of incurred amino acid insertions. Hence, precise correction of c.1278insTATC is the only therapeutically relevant outcome achieved in this study, with MMEJ highlighted as a potential template-free CRISPR-Cas9 modality to that end.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".