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Record W2095557517 · doi:10.1016/j.gendis.2014.09.002

Highly efficient retinal gene delivery with helper-dependent adenoviral vectors

2014· article· en· W2095557517 on OpenAlexafffund
Simon Lam, Huibi Cao, Jing Wu, Rongqi Duan, Jim Hu

Bibliographic record

VenueGenes & Diseases · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health ResearchU.S. Public Health ServiceUniversity of British ColumbiaFoundation Fighting BlindnessZoetis
KeywordsABCA4RPE65Genetic enhancementTransgeneStargardt diseaseGene deliveryBiologyRetinalRetinal pigment epitheliumCis-trans-IsomerasesRetinaRetinal degenerationViral vectorGeneVectors in gene therapyReporter geneRetinitis pigmentosaGene expressionGeneticsRecombinant DNANeurosciencePhenotype

Abstract

fetched live from OpenAlex

There have been significant advancements in the field of retinal gene therapy in the past several years. In particular, therapeutic efficacy has been achieved in three separate human clinical trials conducted to assess the ability of adeno-associated viruses (AAV) to treat of a type of Leber's congenital amaurosis caused by RPE65 mutations. However, despite the success of retinal gene therapy with AAV, challenges remain for delivering large therapeutic genes or genes requiring long DNA regulatory elements for controlling their expression. For example, Stargardt's disease, a form of juvenile macular degeneration, is caused by defects in ABCA4, a gene that is too large to be packaged in AAV. Therefore, we investigated the ability of helper dependent adenovirus (HD-Ad) to deliver genes to the retina as it has a much larger transgene capacity. Using an EGFP reporter, our results showed that HD-Ad can transduce the entire retinal epithelium of a mouse using a dose of only 1 × 105 infectious units and maintain transgene expression for at least 4 months. The results demonstrate that HD-Ad has the potential to be an effective vector for the gene therapy of the retina.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.729

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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