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Record W4255681473 · doi:10.1089/hum.2014.154

Ferret and Pig Models of Cystic Fibrosis: Prospects and Promise for Gene Therapy

2014· article· en· W4255681473 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

VenueHuman Gene Therapy Clinical Development · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Institutes of Health
KeywordsCystic fibrosisGenetic enhancementMedicineGeneBiologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

Large animal models of genetic diseases are rapidly becoming integral to biomedical research as technologies to manipulate the mammalian genome improve.The creation of cystic fibrosis (CF) ferrets and pigs is an example of such progress in animal modeling, with the disease phenotypes in the ferret and pig models more reflective of human CF disease than mouse models.The ferret and pig CF models also provide unique opportunities to develop and assess the effectiveness of gene and cell therapies to treat affected organs.In this review, we examine the organ disease phenotypes in these new CF models and the opportunities to test gene therapies at various stages of disease progression in affected organs.We then discuss the progress in developing recombinant replication-defective adenoviral, adeno-associated viral, and lentiviral vectors to target genes to the lung and pancreas in ferrets and pigs, the two most affected organs in CF.Through this review, we hope to convey the potential of these new animal models for developing CF gene and cell therapies.

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)0.001
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 score0.074
Threshold uncertainty score0.616

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 head0.061
GPT teacher head0.324
Teacher spread0.264 · 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