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Record W4410202978 · doi:10.1016/j.ymthe.2025.05.005

Template-assisted sequence knockin rescues skeletal and cardiac muscle function in a deletion model of Duchenne muscular dystrophy

2025· article· en· W4410202978 on OpenAlexafffund
Sina Fatehi, M. Rok, Ryan M. Marks, Emily Huynh, Natalie Kozman, Hong Truong, Lijun Chi, Bei Yan, Enzhe Khazeeva, Paul Delgado-Olguı́n, Evgueni A. Ivakine, Ronald D. Cohn

Bibliographic record

VenueMolecular Therapy · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsCentre for Global Health ResearchHospital for Sick ChildrenOccupational Cancer Research CentreGenome CanadaUniversity of Toronto
FundersCanadian Institutes of Health ResearchSickkids Research Institute
KeywordsDuchenne muscular dystrophySkeletal muscleMuscular dystrophyBiologyGene knockinFunction (biology)Cell biologyGeneticsAnatomyGene

Abstract

fetched live from OpenAlex

Duchenne muscular dystrophy (DMD) poses challenges in therapy design due to dystrophin's complex role in maintaining muscle function since the restoration of truncated protein products has failed to completely address the disease's pathophysiology in clinical trials. As ∼70% of patients harbor deletions, strategies enabling targeted DNA insertion to restore full-length dystrophin protein are essential. Here, we present template-assisted sequence knockin (TASK), a strategy that we employed to specifically correct the Dmd Δ52-54 mutation in a murine model. By co-delivering a repair template and the Cas9 nuclease using AAV9s, the splice-competent sequence for Dmd exons 52-54 was integrated into the residual intron 54 locus, resulting in the systemic restoration of full-length dystrophin at therapeutically relevant levels in the heart and across all skeletal muscles, leading to significant functional improvements. TASK demonstrates the highest efficiency of exogenous DNA knockin reported to date, achieving rescue of key dystrophic hallmarks in a deletion model of DMD.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.178
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.254
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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