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Record W2048403117 · doi:10.3410/m3-17

Advancements in adeno-associated viral gene therapy approaches: exploring a new horizon

2011· article· en· W2048403117 on OpenAlexaff
Caroline Aalbers, Paul P. Tak, Margriet J. Vervoordeldonk

Bibliographic record

VenueF1000 Medicine Reports · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsGenetic enhancementMedicineClinical trialRheumatoid arthritisGene transferFood and drug administrationAdeno-associated virusViral vectorBioinformaticsDrug developmentGeneIntensive care medicineVector (molecular biology)ImmunologyDrugPharmacologyInternal medicineBiologyGenetics

Abstract

fetched live from OpenAlex

Gene therapy is a promising new therapeutic strategy that has been explored in a wide variety of diseases, ranging from cancer to hemophilia, and ocular disorders to autoimmune diseases, among others. Proof of concept of gene transfer approaches has been shown in over 100 studies of animal models of disease, although only a few are under development for clinical application. The US Food and Drug Administration and the European Medicines Agency have not approved any viral human gene therapy products for sale so far, but the amount of gene-related research and development occurring in the United States and Europe continues to grow at a fast rate. This review summarizes the current status of developments in the field of viral gene therapy using adeno-associated virus as a vector, with a special focus on arthritis. For rheumatoid arthritis, and to a lesser extent for other immune-related inflammatory disorders, several cell and gene transfer approaches have been investigated at the preclinical level and a few have been implemented in clinical trials. Finally, both the potential and the hurdles that are faced during development of a viral gene therapy through to its clinical application are discussed.

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 score0.110
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.161
GPT teacher head0.315
Teacher spread0.154 · 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

Citations29
Published2011
Admission routes1
Has abstractyes

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