Literature DB >> 31748051

Feasibility of Using Vitamin E-Loaded Poly(ε-caprolactone)/Gelatin Nanofibrous Mat to Prevent Oxidative Stress in Skin.

Saba Kalantary1, Farideh Golbabaei1, Masoud Latifi2, Mohammad Ali Shokrgozar3, Mehdi Yaseri4.   

Abstract

Some occupational skin exposures lead to the formation of reactive oxygen species (ROS). The occupational exposure of workers to ROS has been found to be associated with an increased risk of developing skin injuries; therefore, it is essential to protect skin against ROS formation. Recently, some studies have been conducted on introducing better alternatives for skin protection. Nanofibers are good candidates for this purpose. The current study was carried out to assess vitamin E-loaded hybrid Poly(ε-caprolactone) (PCL)/gelatin (Gt) nanofibres mats as protective layers of skin exposed to occupational exposures. Vitamin E (VE) was successfully incorporated into PCL/Gt nanofibers while they were formed by electrospinning method. Nanofibers mats were characterized using scanning electron microscopy (SEM) and fourier transform infrared spectroscopy (FTIR). Their degradation behavior, in vitro release, biocompatibility, and antioxidant activity were studied. The diameters of the PCL/Gt/VE nanofibers decreased with the addition of vitamin E. The degradation rate of nanofibers was equal to 42.98 and 50.69% during 7 and 14 days, respectively. Nanofibers containing vitamin E showed an initial burst followed by a sustained release. The PCL/Gt/VE nanofibers exhibited good free radical scavenging activities despite being exposed to a high electrical potential during electrospinning. PCL/Gt/VE nanofibers supported a higher level of viability compared to PCL/Gt ones and significantly assisted human skin cells against tert-Butyl hydroperoxide (t-BHP) induced oxidative stress. Overall, PCL/Gt/VE nanofibers can potentially be used to protect skin against oxidative stress as a novel approach for worker's healthcare.

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Year:  2020        PMID: 31748051     DOI: 10.1166/jnn.2020.17486

Source DB:  PubMed          Journal:  J Nanosci Nanotechnol        ISSN: 1533-4880


  1 in total

1.  Prediction of hypericin content in Hypericum perforatum L. in different ecological habitat using artificial neural networks.

Authors:  Maryam Saffariha; Ali Jahani; Reza Jahani; Sajid Latif
Journal:  Plant Methods       Date:  2021-01-26       Impact factor: 4.993

  1 in total

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