Evidence map›Paper›PMID 39273137›Full record

ArticleInternational journal of molecular sciences2024

Fabrication of Mupirocin-Loaded PEGylated Chitosan Nanoparticulate Films for Enhanced Wound Healing.

Shajahan Azeez, Anbazhagan Sathiyaseelan, Kaviyarasan Venkatesan, Myeong-Hyeon Wang

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shajahan AzeezCentre for Advanced Studies in Botany, University of Madras, Guindy Campus, Chennai 600025, India.ORCID 0000-0001-7186-6926
Anbazhagan SathiyaseelanDepartment of Bio-Health Convergence, Kangwon National University, Chuncheon 24341, Republic of Korea.ORCID 0000-0001-8142-0063
Kaviyarasan VenkatesanCentre for Advanced Studies in Botany, University of Madras, Guindy Campus, Chennai 600025, India.
Myeong-Hyeon WangDepartment of Bio-Health Convergence, Kangwon National University, Chuncheon 24341, Republic of Korea.ORCID 0000-0003-1760-1622

Funding

National Research Foundation of Korea 2021R1I1A1A01057742; 2022R1A2C2091029
6 · The paper itself

Abstract

Chitosan-based biomaterials are being investigated for their unique properties that support skin regeneration and wound healing. This study focused on the preparation and characterization of a mupirocin (Mup)-loaded PEGylated chitosan (CS-PEG) nanoparticulate film (NF) [CBNF]. The CBNF was characterized using FTIR spectroscopy and SEM analysis. The results demonstrated that CBNF was successfully incorporated into the composites, as shown by functional group modification through FTIR analysis. Additionally, the SEM micrograph revealed the deposition of nanoparticles (<200 nm) on the surface of transparent CBNF. The film has higher water absorption (≥1700%) and moderate water retention ability within 6 h. Furthermore, histological findings showed significant development, with re-epithelialization and granulation of tissues after 19 days, indicating the healing efficiency of CNBF. These results suggest that drug-loaded films could be an effective carrier and delivery agent for Mup-like anti-inflammatory drugs.

Indexed as

ChitosanMupirocinNanoparticlesPolyethylene GlycolsWound HealingAnimalsAnti-Bacterial AgentsDrug CarriersSpectroscopy, Fourier Transform InfraredAnti-Bacterial AgentsChitosanDrug CarriersMupirocinPolyethylene Glycolschitosancomposite filmin vivomupirocinPEGwound healing

Identifiers

PMID39273137
PMCPMC11394824

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.