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Sun Q, Tao S, Bovone G, Han G, Deshmukh D, Tibbitt MW, Ren Q, Bertsch P, Siqueira G, Fischer P. Versatile Mechanically Tunable Hydrogels for Therapeutic Delivery Applications. Adv Healthc Mater 2024:e2304287. [PMID: 38488218 DOI: 10.1002/adhm.202304287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Indexed: 04/02/2024]
Abstract
Hydrogels provide a versatile platform for biomedical material fabrication that can be structurally and mechanically fine-tuned to various tissues and applications. Applications of hydrogels in biomedicine range from highly dynamic injectable hydrogels that can flow through syringe needles and maintain or recover their structure after extrusion to solid-like wound-healing patches that need to be stretchable while providing a selective physical barrier. In this study, a toolbox is designed using thermo-responsive poly(N-isopropylacrylamide) (PNIPAM) polymeric matrices and nanocelluloses as reinforcing agent to obtain biocompatible hydrogels with altering mechanical properties, from a liquid injectable to a solid-like elastic hydrogel. The liquid hydrogels possess low viscosity and shear-thinning properties at 25 °C, which allows facile injection at room temperature, while they become viscoelastic gels at body temperature. In contrast, the covalently cross-linked solid-like hydrogels exhibit enhanced viscoelasticity. The liquid hydrogels are biocompatible and are able to delay the in vitro release and maintain the bioactivity of model drugs. The antimicrobial agent loaded solid-like hydrogels are effective against typical wound-associated pathogens. This work presents a simple method of tuning hydrogel mechanical strength to easily adapt to applications in different soft tissues and broaden the potential of renewable bio-nanoparticles in hybrid biomaterials with controlled drug release capabilities.
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Affiliation(s)
- Qiyao Sun
- Department of Health Science and Technology, ETH Zurich, Zurich, 8092, Switzerland
| | - Siyuan Tao
- Laboratory for Biointerfaces, Empa, St. Gallen, 9014, Switzerland
| | - Giovanni Bovone
- Macromolecular Engineering Laboratory, D-MAVT, ETH Zurich, Zurich, 8092, Switzerland
| | - Garam Han
- Department of Health Science and Technology, ETH Zurich, Zurich, 8092, Switzerland
| | - Dhananjay Deshmukh
- Macromolecular Engineering Laboratory, D-MAVT, ETH Zurich, Zurich, 8092, Switzerland
- Institute for Mechanical Systems, D-MAVT, ETH Zurich, Zurich, 8092, Switzerland
| | - Mark W Tibbitt
- Macromolecular Engineering Laboratory, D-MAVT, ETH Zurich, Zurich, 8092, Switzerland
| | - Qun Ren
- Laboratory for Biointerfaces, Empa, St. Gallen, 9014, Switzerland
| | - Pascal Bertsch
- Drug Delivery and Biophysics of Biopharmaceuticals, Department of Pharmacy, University of Copenhagen, Copenhagen, 2100, Denmark
| | - Gilberto Siqueira
- Cellulose & Wood Materials Laboratory, EMPA, Dübendorf, 8600, Switzerland
| | - Peter Fischer
- Department of Health Science and Technology, ETH Zurich, Zurich, 8092, Switzerland
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Hokkinen L, Kesti A, Lepomäki J, Anttalainen O, Kontunen A, Karjalainen M, Aittoniemi J, Vuento R, Lehtimäki T, Oksala N, Roine A. Differential mobility spectrometry classification of bacteria. Future Microbiol 2020; 15:233-240. [DOI: 10.2217/fmb-2019-0192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Aim: Rapid identification of bacteria would facilitate timely initiation of therapy and improve cost–effectiveness of treatment. Traditional methods (culture, PCR) require reagents, consumables and hours to days to complete the identification. In this study, we examined whether differential mobility spectrometry could classify most common bacterial species, genera and between Gram status within minutes. Materials & methods: Cultured bacterial sample gaseous headspaces were measured with differential mobility spectrometry and data analyzed using k-nearest-neighbor and leave-one-out cross-validation. Results: Differential mobility spectrometry achieved a correct classification rate 70.7% for all bacterial species. For bacterial genera, the rate was 77.6% and between Gram status, 89.1%. Conclusion: Largest difficulties arose in distinguishing bacteria of the same genus. Future improvement of the sensor characteristics may improve the classification accuracy.
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Affiliation(s)
- Lauri Hokkinen
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
| | - Artturi Kesti
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
| | - Jaakko Lepomäki
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
| | - Osmo Anttalainen
- Vascular & interventional Center, Tampere University Hospital, Tampere, Finland
| | - Anton Kontunen
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
| | - Markus Karjalainen
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
| | | | | | - Terho Lehtimäki
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
- Fimlab Laboratories, Tampere, Finland
- Finnish Cardiovascular Research Center – Tampere, Tampere University, Tampere, Finland
| | - Niku Oksala
- Vascular & interventional Center, Tampere University Hospital, Tampere, Finland
- Department of Surgery, Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
| | - Antti Roine
- Faculty of Medicine & Health Technology, Tampere University, Tampere, Finland
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