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Record W3209141478 · doi:10.1186/s12967-021-03099-4

Gene therapy for cystic fibrosis: new tools for precision medicine

2021· review· en· W3209141478 on OpenAlexafffundabout
Jin A Lee, Alex Cho, Elena N. Huang, Yiming Xu, Henry Quach, Jim Hu, Amy P. Wong

Bibliographic record

VenueJournal of Translational Medicine · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsSickKids FoundationUniversity of TorontoHospital for Sick Children
FundersInstitute of Human Development, Child and Youth HealthCanadian Institutes of Health ResearchHospital for Sick ChildrenUniversity of Toronto
KeywordsCystic fibrosisGenetic enhancementMedicinePersonalized medicineBioinformaticsPrecision medicineDiseaseComputational biologyIntensive care medicineGeneBiologyPathologyInternal medicineGenetics

Abstract

fetched live from OpenAlex

The discovery of the Cystic fibrosis (CF) gene in 1989 has paved the way for incredible progress in treating the disease such that the mean survival age of individuals living with CF is now ~58 years in Canada. Recent developments in gene targeting tools and new cell and animal models have re-ignited the search for a permanent genetic cure for all CF. In this review, we highlight some of the more recent gene therapy approaches as well as new models that will provide insight into personalized therapies for CF.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.062
GPT teacher head0.413
Teacher spread0.351 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations77
Published2021
Admission routes3
Has abstractyes

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