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Record W2133709240 · doi:10.1038/mt.2013.258

Skin Electroporation of a Plasmid Encoding hCAP-18/LL-37 Host Defense Peptide Promotes Wound Healing

2014· article· en· W2133709240 on OpenAlexafffund
Lars Steinstraesser, Martin C. Lam, Frank Jacobsen, Paolo E. Porporato, Kiran Kumar Chereddy, Mustafa Becerikli, Ingo Stricker, Robert E. W. Hancock, Marcus Lehnhardt, Pierre Sonveaux, Véronique Préat, Gaëlle Vandermeulen

Bibliographic record

VenueMolecular Therapy · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAntimicrobial Peptides and Activities
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchFédération Wallonie-BruxellesFonds De La Recherche Scientifique - FNRS
KeywordsElectroporationWound healingChemokineCell biologyBiologyMolecular biologyGenetic enhancementAngiogenesisTransfectionImmunologyCancer researchInflammationGeneBiochemistry

Abstract

fetched live from OpenAlex

Host defense peptides, in particular LL-37, are emerging as potential therapeutics for promoting wound healing and inhibiting bacterial growth. However, effective delivery of the LL-37 peptide remains limiting. We hypothesized that skin-targeted electroporation of a plasmid encoding hCAP-18/LL-37 would promote the healing of wounds. The plasmid was efficiently delivered to full-thickness skin wounds by electroporation and it induced expression of LL-37 in the epithelium. It significantly accelerated reepithelialization of nondiabetic and diabetic wounds and caused a significant VEGFa and interleukin (IL)-6 induction. IL-6 was involved in LL-37-mediated keratinocyte migration in vitro and IL-6 neutralizing antibodies delivered to mice were able to suppress the wound healing activity of the hCAP-18/LL-37 plasmid. In a hindlimb ischemia model, electroporation of the hCAP-18/LL-37 plasmid increased blood perfusion, reduced muscular atrophy, and upregulated the angiogenic chemokines VEGFa and SDF-1a, and their receptors VEGF-R and CXCR-4. These findings demonstrate that a localized gene therapy with LL-37 is a promising approach for the treatment of wounds.

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 score0.009
Threshold uncertainty score0.766

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 head0.012
GPT teacher head0.232
Teacher spread0.220 · 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

Citations81
Published2014
Admission routes2
Has abstractyes

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