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Record W4289260770 · doi:10.1016/j.omtm.2022.07.010

Targeting the lung epithelium after intravenous delivery by directed evolution of underexplored sites on the AAV capsid

2022· article· en· W4289260770 on OpenAlexfundno aff
David Goertsen, Nick Goeden, Nicholas C. Flytzanis, Viviana Gradinaru

Bibliographic record

VenueMolecular Therapy — Methods & Clinical Development · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of HealthAdvanced Research Projects AgencyDefense Advanced Research Projects AgencyCalifornia Institute of TechnologyCystic Fibrosis Foundation
KeywordsTransgeneCapsidGenetic enhancementLungGene deliveryTransduction (biophysics)Computational biologyBiologyMedicineVirologyCell biologyVirusGenePathologyBioinformaticsGeneticsInternal medicineBiophysics

Abstract

fetched live from OpenAlex

Advances in adeno-associated virus (AAV) engineering have provided exciting new tools for research and potential solutions for gene therapy. However, the lung has not received the same tailored engineering as other major targets of debilitating genetic disorders. To address this, here we engineered the surface-exposed residues AA452-458 of AAV9 capsid proteins at the three-fold axis of symmetry and employed a Cre-transgenic-based screening platform to identify AAV capsids targeted to the lung after intravenous delivery in mice. Using a custom image processing pipeline to quantify transgene expression across whole tissue images, we found that one engineered variant, AAV9.452sub.LUNG1, displays dramatically improved transgene expression in lung tissue after systemic delivery in mice. This improved transduction extends to alveolar epithelial type II cells, expanding the toolbox for gene therapy research for diseases specific to the lung.

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 score0.001
Threshold uncertainty score0.002

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.369
Teacher spread0.326 · 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

Citations22
Published2022
Admission routes1
Has abstractyes

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