Cationic homopolypeptides: A versatile tool to design multifunctional antimicrobial nanocoatings.

Postoperative infections are the most common complications faced by surgeons after implant surgery. To address this issue, an emerging and promising approach is to develop antimicrobial coatings using antibiotic substitutes. We investigated the use of polycationic homopolypeptides in a layer-by-layer coating combined with hyaluronic acid (HA) to produce an effective antimicrobial shield. The three peptide-based polycations used to make the coatings, poly(l-arginine) (PAR), poly(l-lysine), and poly(l-ornithine), provided an efficient antibacterial barrier by a contact-killing mechanism against Gram-positive, Gram-negative, and antibiotic-resistant bacteria. Moreover, this activity was higher for homopolypeptides containing 30 amino-acid residues per polycation chain, emphasizing the impact of the polycation chain length and its mobility in the coatings to deploy its contact-killing antimicrobial properties. However, the PAR-containing coating emerged as the best candidate among the three selected polycations, as it promoted cell adhesion and epithelial monolayer formation. It also stimulated nitric oxide production in endothelial cells, thereby facilitating angiogenesis and subsequent tissue regeneration. More interestingly, bacteria did not develop a resistance to PAR and (PAR/HA) also inhibited the proliferation of eukaryotic pathogens, such as yeasts. Furthermore, in vivo investigations on a (PAR/HA)-coated hernia mesh implanted on a rabbit model confirmed that the coating had antibacterial properties without causing chronic inflammation. These impressive synergistic activities highlight the strong potential of PAR/HA coatings as a key tool in combating bacteria, including those resistant to conventional antibiotics and associated to medical devices.

Prediction of coating thickness for polyelectrolyte multilayers via machine learning.

Layer-by-layer (LbL) deposition method of polyelectrolytes is a versatile way of developing functional nanoscale coatings. Even though the mechanisms of LbL film development are well-established, currently there are no predictive models that can link film components with their final properties. The current health crisis has shown the importance of accelerated development of biomedical solutions such as antiviral coatings, and the implementation of machine learning methodologies for coating development can enable achieving this. In this work, using literature data and newly generated experimental results, we first analyzed the relative impact of 23 coating parameters on the coating thickness. Next, a predictive model has been developed using aforementioned parameters and molecular descriptors of polymers from the DeepChem library. Model performance was limited because of insufficient number of data points in the training set, due to the scarce availability of data in the literature. Despite this limitation, we demonstrate, for the first time, utilization of machine learning for prediction of LbL coating properties. It can decrease the time necessary to obtain functional coating with desired properties, as well as decrease experimental costs and enable the fast first response to crisis situations (such as pandemics) where coatings can positively contribute. Besides coating thickness, which was selected as an output value in this study, machine learning approach can be potentially used to predict functional properties of multilayer coatings, e.g. biocompatibility, cell adhesive, antibacterial, antiviral or anti-inflammatory properties.

Recent Advances in Antiinflammatory Material Design.

Implants and prostheses are widely used to replace damaged tissues or to treat various diseases. However, besides the risk of bacterial or fungal infection, an inflammatory response usually occurs. Here, recent progress in the field of anti-inflammatory biomaterials is described. Different materials and approaches are used to decrease the inflammatory response, including hydrogels, nanoparticles, implant surface coating by polymers, and a variety of systems for anti-inflammatory drug delivery. Complex multifunctional systems dealing with inflammation, microbial infection, bone regeneration, or angiogenesis are also described. New promising stimuli-responsive systems, such as pH- and temperature-responsive materials, are also being developed that would enable an "intelligent" antiinflammatory response when the inflammation occurs. Together, different approaches hold promise for creation of novel multifunctional smart materials allowing better implant integration and tissue regeneration.