ArticleBioengineering & translational medicine2026
Shelf-stable, ready-to-use therapeutic patches: Dip-and-deliver solutions for personalized wound care.
Article in Bioengineering & translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic wounds often require advanced dressing materials that can conform to complex skin movements and maintain therapeutic efficacy. Conventional dressings are typically non-adhesive and non-auxetic, necessitating external fixation and limiting their mechanical compatibility with natural tissue deformation. To overcome these challenges, we developed an auxetic skin mesh platform with instant adhesion, enabling improved mechanical conformity and ability to mimic skin movement. In this study, we developed a shelf-stable auxetic skin mesh capable of loading and releasing a broad range of therapeutics through a simple dip-and-deliver process. We compared air-dried and freeze-dried meshes against unprocessed controls to evaluate mechanical strength, adhesion, porosity, and drug-release performance. The platform effectively delivered diverse cargos, including lipid nanoparticles (LNPs), extracellular vesicles (EVs), proteins, small molecules, and FDA-approved drugs such as platelet-derived growth factor (PDGF-BB) and antibiotics, demonstrating controlled release and enhanced angiogenesis in a diabetic mouse model. These results highlight the mesh's versatility as a bioadhesive drug-delivery system with strong potential to improve wound healing outcomes.
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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 Socratic graph.