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Record W2565299518 · doi:10.1016/s1525-0016(16)32948-3

139. Development of a Therapy for Duchenne Muscular Dystrophy Using Either TALEN of Cas9 Proteins

2016· article· en· W2565299518 on OpenAlexaff
Daniel Agudelo, Joël Rousseau, Jacques P. Tremblay

Bibliographic record

VenueMolecular Therapy · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTranscription activator-like effector nucleaseGenome editingCRISPRCas9BiologyDystrophinDuchenne muscular dystrophyGeneticsExonGeneStop codonExon skippingMuscular dystrophyComputational biology

Abstract

fetched live from OpenAlex

Duchenne muscular dystrophy (DMD) is a hereditary disease due to a mutation of the DMD gene located in the X chromosome. It is mainly caused by the deletion of one or more exons of the DMD gene, which changes the reading frame and results in a premature stop codon and a truncated and inactive dystrophin protein. Nowadays, genome editing by programmable endonucleases like TALENs or the CRISPR/Cas9 systems is a powerful method for developing a treatment for this type of disease. However, the use of DNA encoding these systems leads to a prolonged expression, which may increase the off-target activity of these nucleases.

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 score0.003
Threshold uncertainty score0.009

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.296
Teacher spread0.282 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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