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Record W2000987352 · doi:10.1089/dna.2009.0915

Efficient Transfection of Endothelial Cells by a Double-Pulse Electroporation Method

2009· article· en· W2000987352 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

VenueDNA and Cell Biology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Inactivation Methods
Canadian institutionsCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsElectroporationTransfectionBiologyUmbilical veinEndothelial stem cellCell cultureCell biologyLipofectamineMolecular biologyHuman umbilical vein endothelial cellGeneIn vitroGeneticsVector (molecular biology)Recombinant DNA

Abstract

fetched live from OpenAlex

Primary endothelial cells are largely recognized as hard-to-transfect cells. We have been using a double-pulse electroporation technique to efficiently insert genetic material into human umbilical vein endothelial cell (HUVEC). Previously, this technique has been successfully used on hard-to-transfect monocytic cells. Using a conventional electroporation device, we have tested this protocol on HUVECs and compared it with conventional transfection techniques. The average transfection efficiency was up to 68% as measured by the ability of the cells to efficiently express the red fluorophore of the tdTomato gene. Similar results were obtained in human aortic endothelial cells and human microvascular endothelial cells. This technique does not require any particular expensive device, specific medium, or reagent, and the results we obtained so far exceed those of any other previous protocol. This is therefore an affordable and efficient transfection technique that opens new avenues in vascular endothelial research.

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)0.000
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 score0.138
Threshold uncertainty score0.366

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 head0.007
GPT teacher head0.274
Teacher spread0.267 · 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