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Record W4379878663 · doi:10.1038/s41592-023-01896-x

Hardwiring tissue-specific AAV transduction in mice through engineered receptor expression

2023· article· en· W4379878663 on OpenAlexfundno aff
James Zengel, Yu Xin Wang, Jai Woong Seo, Ke Ning, James N. Hamilton, Bo Wu, Marina N. Raie, Colin Holbrook, Shiqi Su, Derek R. Clements, Sirika Pillay, Andreas S. Puschnik, Monte M. Winslow, Juliana Idoyaga, Claude M. Nagamine, Yang Sun, Vinit B. Mahajan, Katherine W. Ferrara, Helen M. Blau, Jan E. Carette

Bibliographic record

VenueNature Methods · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
FundersNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Eye InstituteNational Institute on AgingCanadian Institutes of Health ResearchBurroughs Wellcome FundInternational Retinal Research FoundationDivision of Intramural Research, National Institute of Allergy and Infectious DiseasesBrightFocus FoundationOffice of Academic Affiliations, Department of Veterans AffairsCalifornia Institute for Regenerative MedicineResearch to Prevent BlindnessChemistry, Engineering and Medicine for Human Health, Stanford UniversityLi Ka Shing FoundationU.S. Department of Veterans AffairsMilky Way Research FoundationGovernment of CanadaNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsTransduction (biophysics)TransgeneBiologyAdeno-associated virusCell biologyGenetically modified mouseSignal transductionGene deliveryCell typeCellGeneGenetic enhancementGeneticsVector (molecular biology)Recombinant DNA

Abstract

fetched live from OpenAlex

The development of transgenic mouse models that express genes of interest in specific cell types has transformed our understanding of basic biology and disease. However, generating these models is time- and resource-intensive. Here we describe a model system, SELective Expression and Controlled Transduction In Vivo (SELECTIV), that enables efficient and specific expression of transgenes by coupling adeno-associated virus (AAV) vectors with Cre-inducible overexpression of the multi-serotype AAV receptor, AAVR. We demonstrate that transgenic AAVR overexpression greatly increases the efficiency of transduction of many diverse cell types, including muscle stem cells, which are normally refractory to AAV transduction. Superior specificity is achieved by combining Cre-mediated AAVR overexpression with whole-body knockout of endogenous Aavr, which is demonstrated in heart cardiomyocytes, liver hepatocytes and cholinergic neurons. The enhanced efficacy and exquisite specificity of SELECTIV has broad utility in development of new mouse model systems and expands the use of AAV for gene delivery in vivo.

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)0.001
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 score0.284
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.035
GPT teacher head0.400
Teacher spread0.365 · 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

Citations35
Published2023
Admission routes1
Has abstractyes

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