ReviewMicromachines2018
Nanostructure-Enabled and Macromolecule-Grafted Surfaces for Biomedical Applications.
Review in Micromachines, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed, 17 citations in OpenAlex.
- Review on various activator-assisted polymer grafting techniques for smart drug delivery applications.RSC advances · 2025Review
- Review
- Biting Innovations of Mosquito-Based Biomaterials and Medical Devices.Materials (Basel, Switzerland) · 2022Review
- Past and Current Progress in the Development of Antiviral/Antimicrobial Polymer Coating towards COVID-19 Prevention: A Review.Polymers · 2021Review
- Engineered Bioactive Polymeric Surfaces by Radiation Induced Graft Copolymerization: Strategies and Applications.Polymers · 2021Review
- Thermal and Physico-Mechanical Characterizations of Thromboresistant Polyurethane Films.Bioengineering (Basel, Switzerland) · 2019Article
- Engineering Approaches to Prevent Blood Clotting from Medical Implants.Archives in biomedical engineering & biotechnology · 2019Article
- The Role of Electrospun Fiber Scaffolds in Stem Cell Therapy for Skin Tissue Regeneration.Med one · 2019Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Advances in nanotechnology and nanomaterials have enabled the development of functional biomaterials with surface properties that reduce the rate of the device rejection in injectable and implantable biomaterials. In addition, the surface of biomaterials can be functionalized with macromolecules for stimuli-responsive purposes to improve the efficacy and effectiveness in drug release applications. Furthermore, macromolecule-grafted surfaces exhibit a hierarchical nanostructure that mimics nanotextured surfaces for the promotion of cellular responses in tissue engineering. Owing to these unique properties, this review focuses on the grafting of macromolecules on the surfaces of various biomaterials (e.g., films, fibers, hydrogels, and etc.) to create nanostructure-enabled and macromolecule-grafted surfaces for biomedical applications, such as thrombosis prevention and wound healing. The macromolecule-modified surfaces can be treated as a functional device that either passively inhibits adverse effects from injectable and implantable devices or actively delivers biological agents that are locally based on proper stimulation. In this review, several methods are discussed to enable the surface of biomaterials to be used for further grafting of macromolecules. In addition, we review surface-modified films (coatings) and fibers with respect to several biomedical applications. Our review provides a scientific update on the current achievements and future trends of nanostructure-enabled and macromolecule-grafted surfaces in biomedical applications.
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.