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Record W6999108906

Carvacrol-Loaded Phytosomes for Enhanced Wound Healing: Molecular Docking, Formulation, DoE-Aided Optimization, and in vitro/in vivo Evaluation

2023· article· en· W6999108906 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldMedicine
TopicSilymarin and Mushroom Poisoning
Canadian institutionsnot available
Fundersnot available
KeywordsLiposomeZeta potentialWound dressingCetrimideIn vivo
DOInot available

Abstract

fetched live from OpenAlex

Ahmed Mowafy Tafish,1,2 Mohamed El-Sherbiny,3,4 Ahmed A Al‐Karmalawy,5,6 Osama Abd El-Azeem Soliman,1 Noha Mohamed Saleh1 1Department of Pharmaceutics, Faculty of Pharmacy, Mansoura University, Mansoura, 35516, Egypt; 2Department of Pharmaceutical Technology, Faculty of Pharmacy, Horus University, New Damietta, 34518, Egypt; 3Department of Basic Medical Sciences, College of Medicine, AlMaarefa University, Riyadh, Saudi Arabia; 4Department of Anatomy, Faculty of Medicine, Mansoura University, Mansoura, 35516, Egypt; 5Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Horus University, New Damietta, 34518, Egypt; 6Pharmaceutical Chemistry Department, Faculty of Pharmacy, Ahram Canadian University, 6th of October City, Giza, 12566, EgyptCorrespondence: Noha Mohamed Saleh, Associate Professor of Pharmaceutics, Department of Pharmaceutics, Faculty of Pharmacy, Mansoura University, Mansoura, 35516, Egypt, Tel +2 01064536677, Fax +2 050 2247496, Email nunu_ramy@mans.edu.egBackground: Despite recent advances in wound healing products, phytochemicals have been considered promising and attractive alternatives. Carvacrol (CAR), a natural phenolic compound, has been reported to be effective in wound healing.Purpose: This work endeavored to develop novel CAR-loaded phytosomes for the enhancement of the wound healing process.Methods: Molecular docking was performed to compare the affinities of the different types of phospholipids to CAR. Phytosomes were prepared by three methods (thin-film hydration, cosolvency, and salting out) using Lipoid S100 and Phospholipon 90H with three levels of saturation percent (0%, 50%, and 100%), and three levels of phospholipid molar percent (66.67%, 75%, and 80%). The optimization was performed using Design Expert where particle size, polydispersity index, and zeta potential were chosen as dependent variables. The optimized formula (F1) was further investigated regarding entrapment efficiency, TEM, 1H-NMR, FT-IR, DSC, X-RD, in vitro release, ex vivo permeation, and stability. Furthermore, it was incorporated into a hydrogel formulation, and an in vivo study was conducted to investigate the wound-healing properties of F1.Results: F1 was chosen as the optimized formula prepared via the thin-film hydration method with a saturation percent and a phospholipid molar percent of zero and 66.67, respectively. TEM revealed the spherical shape of phytosomal vesicles with uniform size, while the results of 1H-NMR, FT-IR, DSC, and X-RD confirmed the formation of the phytosomal complex. F1 demonstrated a higher in vitro release and a slower permeation than free CAR. The wound area of F1-treated animals showed a marked reduction associated with a high degree of collagen fiber deposition and enhanced cellular proliferation.Conclusion: F1 can be considered as a promising remedy for the enhancement of wound healing and hence it would be hoped to undergo further investigation.Graphical Abstract: Keywords: carvacrol, phospholipids, docking, phytosome, release, topical, wound healing

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.196
GPT teacher head0.545
Teacher spread0.348 · 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.

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
Published2023
Admission routes1
Has abstractyes

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