ArticleCell journal2022
Fungal Infected Adipose Stem Cells: The Effects of Novel Lipo-Niosome Nanoparticles Loaded with Amphotericin B and Thymus Essential Oil.
Article in Cell journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Lipid-Based Drug Delivery Systems as Emerging Tools to Overcome Antifungal Resistance.International journal of molecular sciences · 2026Review
- Ergosterol: Biological Activities, Mechanistic Evidence, Pharmacokinetic Barriers, and Delivery Strategies.International journal of molecular sciences · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIn this study, we aimed to develop new Lipo-niosomes based nanoparticles loaded with Amphotericin B (AmB) and Thymus Essential Oil (TEO) and test their effectiveness in the treatment of fungal-infected human adipose stem cells (hASCs). MATERIALS AND
methodsIn this experimental study, optimal formulation of AmB and TEO loaded lipo-niosome (based on lipid-surfactant thin-film hydration method) was chemically, and biologically characterized. Therefore, encapsulation capacity, drug release, size, and the survival rate of cells with different concentrations of free and encapsulated AmB/ TEO were evaluated using the MTT method, and its antifungal activity was compared with conventional AmB.
resultsLipo-Niosome containing Tween 60 surfactant: cholesterol: Dipalmitoyl phosphatidylcholine (DPPC): Polyethylene glycol (PEG) with a ratio of 20:40:60:3 were chosen as optimal formulation. Lipo-Niosomes entrapment efficiency was 94.15%. The drug release rate after 24 hours was 52%, 54%, and 48% for Lipo-AmB, Lipo-TEO, and Lipo-AmB/TEO, respectively. Physical and chemical characteristics of the Lipo-Niosomes particles indicated size of 200 nm and a dispersion index of 0.32 with a Zeta potential of -24.56 mv. Furthermore, no chemical interaction between drugs and nano-carriers was observed. The cell viability of adipose mesenchymal stem cells exposed to 50 μg/ml of free AmB, free TEO, and free AmB/TEO was 13.4, 58, and 36.9%, respectively. Whereas the toxicity of the encapsulated formulas of these drugs was 48.9, 70.8, and 58.3% respectively. The toxicity of nanoparticles was very low (8.5%) at this concentration. Fluorescence microscopic images showed that the antifungal activity of Lipo-AmB/ TEO was significantly higher than free formulas of AmB, TEO, and AmB/TEO.
conclusionIn this study, we investigated the efficacy of the TEO/AmB combination, in both free and encapsulatedniosomal form, on the growth of fungal infected-hASCs. The results showed that the AmB/TEO-loaded Lipo-Niosomes can be suggested as a new efficient anti-fungal nano-system for patients treated with hASCs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.