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Record W2055923087 · doi:10.2174/156652306779010651

Ex Vivo Modification of Cells to Induce a Muscle-Based Expression

2006· review· en· W2055923087 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Gene Therapy · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsEx vivoIn vivoCell biologyExpression (computer science)MyocyteBiologyMolecular biologyChemistryComputer scienceGenetics

Abstract

fetched live from OpenAlex

Ex vivo gene therapy is a possible treatment for several muscular dystrophies. The best transgene to be expressed and the appropriate cell type to be used currently remain the subject of many investigations. The most adequate gene modification technique also remains to be established. Different transgenes have already been tested in animal models and transgenic mice. Several cell types were evaluated during the last decades and several vectors or transfection methods were analysed. From these essays, over time, several proofs of principles were made to demonstrate the feasibility of this type of therapy. For DMD, it is possible to express several truncated versions of dystrophin or exon skipping molecules. It is also possible to express other molecules that would mitigate the phenotype. Different cell types are also available. From the well documented myoblasts to the AC133 positive cells, the choice of cell types is exploding. Gene modification also evolved during the last decade. Efficient transfection technique and viral vectors are currently available. Given all these possibilities, the researcher has to make several choices. This review is trying to give clues of how to make those choices.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.823
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.072
GPT teacher head0.360
Teacher spread0.288 · 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