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Record W2071450180 · doi:10.1089/hum.2009.220

Transient Increase in Intrahepatic Pressure Mediates Successful Treatment of the Gunn Rat with Reduced Doses of Lentiviral Vector

2010· article· en· W2071450180 on OpenAlexaff
Françoise Schmitt, Maude Flageul, Anne Dariel, Virginie Pichard, Cecilia Abarrategui Pontes, Sébastien Boni, Guillaume Podevin, Anne Myara, Nicolas Ferry, Tuan Huy Nguyen

Bibliographic record

VenueHuman Gene Therapy · 2010
Typearticle
Languageen
FieldMedicine
TopicLiver physiology and pathology
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsViral vectorGenetic enhancementTransduction (biophysics)In vivoGene deliveryVector (molecular biology)MedicineBiologyGenePharmacologyBiochemistryGenetics

Abstract

fetched live from OpenAlex

Lentiviral vectors can stably transduce hepatocytes and are promising tools for gene therapy of hepatic diseases. Although hepatocytes are accessible to blood-borne viral vectors through fenestrations of the hepatic endothelium, improved liver transduction after delivery of vectors to the blood stream is needed. As the normal endothelial fenestration and lentiviral vectors are similar in size (150 nm), we hypothesized that a transient increase in hepatic blood pressure may enhance in vivo gene transfer to hepatocytes. We designed a simple surgical procedure, by which the liver is temporarily excluded from blood flow. Lentiviral vectors were injected in a large volume to increase intrahepatic pressure. We demonstrated that in the Gunn rat, a model of Crigler-Najjar disease, the administration of low vector doses (corresponding to a multiplicity of infection of 0.2) by this procedure resulted in therapeutic correction of hyperbilirubinemia, without toxicity. The correction was sustained for 10 months (end of study). The same vector amounts yielded only partial correction after intraportal delivery. We believe that this new and clinically applicable strategy may broaden the range of genetic liver diseases accessible to gene therapy.

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 score0.337
Threshold uncertainty score0.286

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 head0.016
GPT teacher head0.266
Teacher spread0.249 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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