MétaCan
Menu
Back to cohort
Record W4235746837 · doi:10.1121/1.4800281

Ultrasound-mediated gene delivery: Cardiovascular applications for chronic ischemia, heart failure and ischemia-reperfusion injury

2013· article· en· W4235746837 on OpenAlexaff
Azadeh Mofid, Paul J. Lee, Howard Leong‐Poi

Bibliographic record

VenueProceedings of meetings on acoustics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsGenetic enhancementIschemiaGene deliveryMedicineTherapeutic angiogenesisHeart failureAngiogenesisSonoporationCancer researchCardiologyGeneUltrasoundMicrobubblesBiologyNeovascularizationRadiology

Abstract

fetched live from OpenAlex

Ultrasound-mediated gene delivery (UMGD) is a non-invasive gene transfer technique, utilizing high power ultrasound and DNA-bearing microbubbles. Despite modest transfection efficiency, its high organ, tissue specificity and repeatability make it an attractive therapeutic option. UMGD has been used in a variety of in vivo applications, including cardiac and skeletal muscle, kidney, liver, cerebral and even lung, and have been studied using many gene vectors, including plasmid, viral and small interfering RNA. This presentation will focus specifically on cardiac applications using plasmid DNA, including 1) introduction of UMGD in the heart, including optimization of parameters and protocols, 2) UMGD for therapeutic angiogenesis in chronic ischemia, including multi pro-angiogenic gene therapy and combination gene- and progenitor cell-based therapies for chronic hindlimb ischemia, and 3) applications for anti-apoptotic therapy in heart failure and ischemia-reperfusion injury.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of meetings on acousticsSame topicVirus-based gene therapy researchFrench-language works237,207