MétaCan
Menu
Back to cohort
Record W2047457389 · doi:10.1182/blood-2013-12-546218

Rapamycin relieves lentiviral vector transduction resistance in human and mouse hematopoietic stem cells

2014· article· en· W2047457389 on OpenAlexfundno aff
Cathy X. Wang, Blythe Sather, Xuefeng Wang, Jennifer E. Adair, Iram Khan, Swati Singh, Shanshan Lang, Amie B. Adams, Gabrielle Curinga, Hans‐Peter Kiem, Carol H. Miao, David J. Rawlings, Bruce E. Torbett

Bibliographic record

VenueBlood · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Heart, Lung, and Blood InstituteNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsTransduction (biophysics)Stem cellViral vectorHaematopoiesisBiologyHematopoietic stem cellGene deliveryGenetic enhancementCancer researchCell biologyGeneGenetics

Abstract

fetched live from OpenAlex

Transplantation of genetically modified hematopoietic stem cells (HSCs) is a promising therapeutic strategy for genetic diseases, HIV, and cancer. However, a barrier for clinical HSC gene therapy is the limited efficiency of gene delivery via lentiviral vectors (LVs) into HSCs. We show here that rapamycin, an allosteric inhibitor of the mammalian target of rapamycin complexes, facilitates highly efficient lentiviral transduction of mouse and human HSCs and dramatically enhances marking frequency in long-term engrafting cells in mice. Mechanistically, rapamycin enhanced postbinding endocytic events, leading to increased levels of LV cytoplasmic entry, reverse transcription, and genomic integration. Despite increasing LV copy number, rapamycin did not significantly alter LV integration site profile or chromosomal distribution in mouse HSCs. Rapamycin also enhanced in situ transduction of mouse HSCs via direct intraosseous infusion. Collectively, rapamycin strongly augments LV transduction of HSCs in vitro and in vivo and may prove useful for therapeutic gene delivery.

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)0.000
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 score0.003
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.011
GPT teacher head0.247
Teacher spread0.237 · 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

Citations86
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueBloodSame topicVirus-based gene therapy researchFrench-language works237,207