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Alginate-chitosan hydrogel formulations for VEGFA expressed baculovirus delivery promoting angiogenesis for wound healing and revascularization

2024· article· en· W4403805757 on OpenAlexafffund
Sabrina Schaly, Paromita Islam, Satya Prakash

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMedicineAngiogenesisChitosanWound healingRevascularizationBiomedical engineeringVascular endothelial growth factor AVEGF receptorsSurgeryVascular endothelial growth factorCancer researchBiochemistryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background Baculoviruses, engineered to express growth factors, offer a promising avenue for short-term gene therapy, such as wound dressings, due to their safety and specificity. Encapsulation in natural polymers like alginate and chitosan addresses limitations like serum inactivation and fragility, while promoting sustained delivery and shielding from immune inactivation. Wound healing involves complex processes that can be enhanced by maintaining an antimicrobial, moist environment, which promotes cell migration and angiogenesis. Vascular endothelial cell growth factor A (VEGFA) is known to be one of the most potent pro-angiogenic factors and plays a key role in wound healing. Purpose This investigation seeks to enhance wound healing and angiogenesis, support the revascularization process, and provide anti-inflammatory and anti-microbial effects. Additionally, it aims to assess the preclinical efficacy and safety of the approach. Methods Ionic cross-linking was used for virus encapsulation under aseptic conditions. The capsules were assessed for their surface morphology, particle size, zeta potential, and in vitro release profile. Additionally, their therapeutic potential was studied using cell lines. The efficacy of hydrogel delivery of VEGFA-expressing baculoviruses in promoting cell migration and angiogenesis for wound healing applications was investigated on Human Umbilical Vein Endothelial Cells (HUVECs). Hydrogel morphology, swelling, and encapsulation efficiency were evaluated, along with endothelial tube formation assays and hemocompatibility studies on HUVECs. Results Encapsulation of baculovirus expressing the VEGFA gene in alginate and chitosan–alginate hydrogels achieve a high encapsulation efficiency of 99.9%. This allows for prolonged virus delivery and an increased therapeutic window. The encapsulated baculovirus maintains activity and is released over eight days, with a transduction efficiency of over 40%. This promotes tube formation, cell proliferation, and cell migration for angiogenesis, particularly beneficial for chronic wound-healing applications. The hydrogels also prevented E. coli and C. albicans growth directly below and inhibited C. albicans growth surrounding the alginate–chitosan hydrogels. The hydrogels demonstrated no cytotoxicity and good blood compatibility. Conclusion This proof of concept underscores the potential of encapsulated baculovirus delivery systems for various gene therapy applications including cardiovascular tissue regeneration and revascularization.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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".

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Citations6
Published2024
Admission routes2
Has abstractyes

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