Natural lignocellulose fibers-based bio-dressing for accelerated wound healing and machine learning-assisted smart multimodal sensing.

Journal: Biomaterials
Published Date:

Abstract

The integration of ultrasensitive smart human-machine interaction and well skin-like healing capabilities into the biomaterials-based dressing still remains great challenges. Herein, a sort of novel multifunctional lignocellulose dressing is proposed by combining ammonia-oxygen pretreatment with papermaking strategy, which promotes wound healing and achieves synchronous and resolvable self-powered quadruple sensing. In-situ aminated lignin within lignocellulose skeleton and the incorporated foreign natural tea polyphenols (TP) on outer wall synergistically enhanced the polarity of the lignocellulose, the optimized lignocellulose/TP TENG displayed the highest output performance, with the maximum output power of 210.43 mW/m, 890.72 % higher than that of pristine lignocellulose. Benefiting from the reinforced triboelectricity and abundant polar groups, the as-constructed bio-dressing is highly responsive to multiple stimuli with the assistance of machine learning, including pressure, humidity, and material types. Moreover, the unique three-dimensional interwoven networks of fibers and phenolic hydroxyl on TP endows the bio-dressing with high air permeability of 4.5 mm s, excellent antibacterial and antioxidant properties, and high mechanical strength. After coating the lignocellulose-dressing, the wound recovery can be significantly accelerated within 12 days and the wound healing state can be monitored in single-electrode model. Our findings offered a reliable strategy to design and fabricate advanced biomaterials, boosting the development of future point-of-care applications.

Authors

  • Chao Li
    McGill University Health Centre, McGill Adult Unit for Congenital Heart Disease Excellence, Montreal, Québec, Canada.
  • Jian Du
    Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
  • Lingyu Zhu
    Department of Materials Science and Engineering, City University of Hong Kong, 999077, Hong Kong, China.
  • Jinwen Hu
    Department of Radiology, Shanghai Putuo District People's Hospital, Shanghai, China.
  • Chenglong Fu
  • Jie Lu
    Department of Endocrinology and Metabolism, the Affiliated Hospital of Qingdao University, Qingdao, People's Republic of China.
  • Haishun Du
    Department of Biological Systems Engineering, University of Wisconsin-Madison, Madison, WI, 53706, USA.
  • Haisong Wang
    Liaoning Key Lab of Lignocellulose Chemistry and BioMaterials, Liaoning Collaborative Innovation Center for Lignocellulosic Biorefinery, College of Light Industry and Chemical Engineering, Dalian Polytechnic University, Dalian, 116034, China. Electronic address: wanghs@dlpu.edu.cn.
  • Dong Lv
    School of Business Administration, Huaqiao University, Quanzhou, China.

Keywords

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