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Record W2041607260 · doi:10.1182/blood-2013-04-497354

Robust ZFN-mediated genome editing in adult hemophilic mice

2013· article· en· W2041607260 on OpenAlexaff
Xavier M. Anguela, Rajiv P. Sharma, Yannick Doyon, Jeffrey C. Miller, Hojun Li, Virginia Haurigot, Michelle Rohde, Sunnie Wong, Robert J. Davidson, Shangzhen Zhou, Philip D. Gregory, Michael C. Holmes, Katherine A. High

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthHoward Hughes Medical Institute
KeywordsZinc finger nucleaseGenome editingBiologyZinc fingerGenetic enhancementGenomeGeneComputational biologyTranscription activator-like effector nucleaseDNAGeneticsCell biologyVirologyTranscription factor

Abstract

fetched live from OpenAlex

Monogenic diseases, including hemophilia, represent ideal targets for genome-editing approaches aimed at correcting a defective gene. Here we report that systemic adeno-associated virus (AAV) vector delivery of zinc finger nucleases (ZFNs) and corrective donor template to the predominantly quiescent livers of adult mice enables production of high levels of human factor IX in a murine model of hemophilia B. Further, we show that off-target cleavage can be substantially reduced while maintaining robust editing by using obligate heterodimeric ZFNs engineered to minimize unwanted cleavage attributable to homodimerization of the ZFNs. These results broaden the therapeutic potential of AAV/ZFN-mediated genome editing in the liver and could expand this strategy to other nonreplicating cell types.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.216
Teacher spread0.210 · 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 source (direct Gemma or distilled Codex), 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

Citations173
Published2013
Admission routes1
Has abstractyes

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