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The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

Core–Shell Structured Antimicrobial Nanofiber Dressings Containing Herbal Extract and Antibiotics Combination for the Prevention of Biofilms and Promotion of Cutaneous Wound Healing

Abstract

Burn wounds are susceptible to microbial invasion from both resident and exogenous bacteria, which becomes a critical public health issue and causes substantial economic burden. There is a perceived demand to produce new antimicrobial wound dressings that hinder bacterial colonization while accelerating the healing process and hence would provide an improved standard of care for patients. Since ancient times, herbal extracts from medicinally important plants have extensively been used for treating burn injuries. This work reports the utility of electrospun nanofibers containing plant extracts and antibiotics combination as a multifunctional scaffold for treating second-degree burns. First, we determined the various components of plant extracts from Gymnema sylvestre by two different processing methods and their synergism with minocycline antibiotics. Then, we prepared core–shell nanofibrous dressings with poly-ε-caprolactone/gelatin laden with minocycline hydrochloride as a shell and gelatin infused with G. sylvestre extracts (ultrasound-assisted extracts and cold macerated extracts) as the core using coaxial electrospinning. The electrospun nanofibers displayed a smooth, continuous, and bead-free morphology with adequate wettability. The presence of extract components in the core–shell nanofibers resulted in enhanced mechanical properties when compared to pristine mats. The core–shell structures resulted in sustained release of the bioactive components when compared to nanofiber blends. Core–shell nanofiber mats containing plant extracts and antibiotic combinations displayed potent antimicrobial and antibiofilm properties while promoting the spread and proliferation of skin cells when compared to pristine mats. In a porcine model of cutaneous second-degree burns, we showed that wounds treated with the antimicrobial dressing improved re-epithelialization and collagen organization in comparison to untreated wounds.

Overview

Integrity signals

Registry

Crossref · 10.1021/acsami.0c20642

Cites

41 of 41 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Citations

Cites

Research works printed but not linked: 1

  1. Tackling Drug-Resistant Infections Globally: Final Report and Recommendations, Review on Antimicrobial Resistance, May 2016, https://amr-review.org/sites/default/files/160525_Final%20paper_with%20cover.pdf (accessed October 30, 2020)

Cited by

See all 115

Metadata

Authors
Ramalingam, R., Dhand, C., Mayandi, V., Leung, C. M., Ezhilarasu, H., Karuppannan, S. K., Prasannan, P., Ong, S. T., Sunderasan, N., Kaliappan, I., Kamruddin, M., Barathi, V. A., Verma, N. K., Ramakrishna, S., Lakshminarayanan, R., & Arunachalam, K. D.
Affiliations
  • SRM Institute of Science and Technology (IN)
  • Advanced Materials and Processes Research Institute (IN)
  • Nanyang Technological University (SG)
  • National University of Singapore (SG)
  • Department of Pharmaceutical Chemistry, SRM College of Pharmacy, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu (Dt), Tamil Nadu 603203, India
  • Indira Gandhi Centre for Atomic Research (IN)
Corresponding author
  • Ramakrishna, Seeram
  • Lakshminarayanan, Rajamani
  • Arunachalam, Kantha Deivi
Venue
ACS Applied Materials & Interfaces
Published
2021-05-24
Volume
13
Issue
21
Pages
24356-24369
ISSN
  • 1944-8244 (ISSN-L)
  • 1944-8252
OpenAlex
W3164766431
Cited by
115
References
41
Citations by year
2026: 12 · 2025: 21 · 2024: 23 · 2023: 24 · 2022: 28 · 2021: 7
FWCI
4.88
Type
journal article
Language
en
Open access
closed
Locations
  • ACS Applied Materials & Interfaces (publishedVersion)
  • PubMed (publishedVersion)
  • DR-NTU (Nanyang Technological University) (submittedVersion)
Funders
  • Agency for Science, Technology and Research (IAF-PP H17/01/a0/0K9)
  • National Medical Research Council (NMRC/CBRG/0048/2013, NMRC/TCR/008-SERI/2013)
  • UGC-DAE Consortium for Scientific Research (CSR-KN/CRS-70/2015-16/811)
  • Singapore National Eye Centre (R1181/83/2014)
  • Lee Kong Chian School of Medicine, Nanyang Technological University Singapore (L0412290, SAI-L0494003)
Topics
  • Physical Sciences › Materials Science › Biomaterials › Electrospun Nanofibers in Biomedical Applications
  • Health Sciences › Medicine › Surgery › Wound Healing and Treatments
  • Physical Sciences › Materials Science › Polymers and Plastics › Dyeing and Modifying Textile Fibers
Keywords
antimicrobial dressings, core-shell nanofibers, coaxial electrospinning, burn wound healing, second-degree burns, Gymnema sylvestre, herbal plant extracts, minocycline, antibiotic synergy, antibiofilm activity, sustained drug release, re-epithelialization, collagen organization, porcine burn model
MeSH terms
Animals, Anti-Infective Agents, Bacterial Adhesion, Bandages, Humans, Skin, Swine, Wound Healing, Biofilms, Herbal Medicine, Cell Proliferation, Nanofibers

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.