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Record W4377967507 · doi:10.1021/acsabm.2c01068

Assessment of the Efficacy of an LL-37-Encapsulated Keratin Hydrogel for the Treatment of Full-Thickness Wounds

2023· article· en· W4377967507 on OpenAlexaff
Sahar Jelodari, Hamed Daemi, Parvaneh Mohammadi, Javad Verdi, Mohammed J Al-Awady, Jafar Ai, Mahmoud Azami

Bibliographic record

VenueACS Applied Bio Materials · 2023
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsWestern University
FundersRoyan InstituteTehran University of Medical Sciences and Health Services
KeywordsWound healingSelf-healing hydrogelsAngiogenesisKeratinIn vivoBiomedical engineeringSurgeryMedicineChemistryPathologyCancer researchBiologyPolymer chemistry

Abstract

fetched live from OpenAlex

Wound healing remains a burdensome healthcare problem due to moisture loss and bacterial infection. Advanced hydrogel dressings can help to resolve these issues by assisting and accelerating regenerative processes such as cell migration and angiogenesis because of the similarities between their composition and structure with natural skin. In this study, we aimed to develop a keratin-based hydrogel dressing and investigate the impact of the delivery of LL-37 antimicrobial peptide using this hydrogel in treating full-thickness rat wounds. Therefore, oxidized (keratose) and reduced (kerateine) keratins were utilized to prepare 10% (w/v) hydrogels with different ratios of keratose and kerateine. The mechanical properties of these hydrogels with compressive modulus of 6–32 kPa and tan δ <1 render them suitable for wound healing applications. Also, sustained release of LL-37 from the keratin hydrogel was achieved, which can lead to superior wound healing. In vitro studies confirmed that LL-37 containing 25:75% of keratose/kerateine (L-KO25:KN75) would result in significant fibroblast proliferation (∼85% on day 7), adhesion (∼90 cells/HPF), and migration (73% scratch closure after 12 h and complete closure after 24 h). Also, L-KO25:KN75 is capable of eradicating both Gram-negative and Gram-positive bacteria after 18 h. According to in vivo assessment of L-KO25:KN75, wound closure at day 21 was >98% and microvessel density (>30 vessels/HPF at day 14) was significantly superior in comparison to other treatment groups. The mRNA expression of VEGF and IL-6 was also increased in the L-KO25:KN75-treated group and contributed to proper wound healing. Therefore, the LL-37-containing keratin hydrogel ameliorated wound closure, and also angiogenesis was enhanced as a result of LL-37 delivery. These results suggested that the L-KO25:KN75 hydrogel could be a sustainable substitute for skin tissue regeneration in medical applications.

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 score0.002

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 head0.026
GPT teacher head0.305
Teacher spread0.279 · 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

Citations21
Published2023
Admission routes1
Has abstractyes

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