Prediction of Broad-Spectrum Pathogen Attachment to Coating Materials for Biomedical Devices

Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence

Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face in the future. There have been various attempts to preserve the efficacy of existing antimicrobials, develop new and efficient antimicrobials, manage infections with multi-drug resistant strains, and improve patient outcomes, resulting in a growing mass of routinely available data, including electronic health records and microbiological information that can be employed to develop individualised antimicrobial stewardship. Machine learning methods have been developed to predict antimicrobial resistance from whole-genome sequencing data, forecast medication susceptibility, recognise epidemic patterns for surveillance purposes, or propose new antibacterial treatments and accelerate scientific discovery. Unfortunately, there is an evident gap between the number of machine learning applications in science and the effective implementation of these systems. This narrative review highlights some of the outstanding opportunities that machine learning offers when applied in research related to antimicrobial resistance. In the future, machine learning tools may prove to be superbugs' kryptonite. This review aims to provide an overview of available publications to aid researchers that are looking to expand their work with new approaches and to acquaint them with the current application of machine learning techniques in this field.

A potential alternative to fungicides using actives-free (meth)acrylate polymers for protection of wheat crops from fungal attachment and infection

Fungicidal compounds are actives widely used for crop protection from fungal infection, but they can also kill beneficial organisms, enter the food chain and promote resistant pathogen strains from overuse. Here we report the first field crop trial of homopolymer materials that prevent fungal attachment, showing successful crop protection via an actives-free approach. In the trial, formulations containing two candidate polymers were applied to young wheat plants that were subject to natural infection with the wheat pathogen Zymoseptoria tritici. A formulation containing one of the candidate polymers, poly(di(ethylene glycol) ethyl ether acrylate) (abbreviated DEGEEA), produced a significant reduction (26%) in infection of the crop by Z. tritici, delivering protection against fungal infection that compared favourably with three different commercially established fungicide programmes tested in parallel. Furthermore, the sprayed polymers did not negatively affect wheat growth. The two lead polymer candidates were initially identified by bio-performance testing using in vitro microplate- and leaf-based assays and were taken forward successfully into a programme to optimize and scale-up their synthesis and compound them into a spray formulation. Therefore, the positive field trial outcome has also established the validity of the smaller-scale, laboratory-based bioassay data and scale-up methodologies used. Because fungal attachment to plant surfaces is a first step in many crop infections, this non-eluting polymer: (i) now offers significant potential to deliver protection against fungal attack, while (ii) addressing the fourth and aligning with the eleventh principles of green chemistry by using chemical products designed to preserve efficacy of function while reducing toxicity. A future focus should be to develop the material properties for this and other applications including other fungal pathogens.

Applied machine learning as a driver for polymeric biomaterials design

Polymers are ubiquitous to almost every aspect of modern society and their use in medical products is similarly pervasive. Despite this, the diversity in commercial polymers used in medicine is stunningly low. Considerable time and resources have been extended over the years towards the development of new polymeric biomaterials which address unmet needs left by the current generation of medical-grade polymers. Machine learning (ML) presents an unprecedented opportunity in this field to bypass the need for trial-and-error synthesis, thus reducing the time and resources invested into new discoveries critical for advancing medical treatments. Current efforts pioneering applied ML in polymer design have employed combinatorial and high throughput experimental design to address data availability concerns. However, the lack of available and standardized characterization of parameters relevant to medicine, including degradation time and biocompatibility, represents a nearly insurmountable obstacle to ML-aided design of biomaterials. Herein, we identify a gap at the intersection of applied ML and biomedical polymer design, highlight current works at this junction more broadly and provide an outlook on challenges and future directions.

Linear Binary Classifier to Predict Bacterial Biofilm Formation on Polyacrylates

Bacterial infections are increasingly problematic due to the rise of antimicrobial resistance. Consequently, the rational design of materials naturally resistant to biofilm formation is an important strategy for preventing medical device-associated infections. Machine learning (ML) is a powerful method to find useful patterns in complex data from a wide range of fields. Recent reports showed how ML can reveal strong relationships between bacterial adhesion and the physicochemical properties of polyacrylate libraries. These studies used robust and predictive nonlinear regression methods that had better quantitative prediction power than linear models. However, as nonlinear models' feature importance is a local rather than global property, these models were hard to interpret and provided limited insight into the molecular details of material-bacteria interactions. Here, we show that the use of interpretable mass spectral molecular ions and chemoinformatic descriptors and a linear binary classification model of attachment of three common nosocomial pathogens to a library of polyacrylates can provide improved guidance for the design of more effective pathogen-resistant coatings. Relevant features from each model were analyzed and correlated with easily interpretable chemoinformatic descriptors to derive a small set of rules that give model features tangible meaning that elucidate relationships between the structure and function. The results show that the attachment of Pseudomonas aeruginosa and Staphylococcus aureus can be robustly predicted by chemoinformatic descriptors, suggesting that the obtained models can predict the attachment response to polyacrylates to identify anti-attachment materials to synthesize and test in the future.

Perspectives on development of biomedical polymer materials in artificial intelligence age

Polymer materials are widely used in biomedicine, chemistry and material science, whose traditional preparations are mainly based on experience, intuition and conceptual insight, having been applied to the development of many new materials, but facing great challenges due to the vast design space for biomedical polymers. So far, the best way to solve these problems is to accelerate material design through artificial intelligence, especially machine learning. Herein, this paper will introduce several successful cases, and analyze the latest progress of machine learning in the field of biomedical polymers, then discuss the opportunities of this novel method. In particular, this paper summarizes the material database, open-source determination tools, molecular generation methods and machine learning models that have been used for biopolymer synthesis and property prediction. Overall, machine learning could be more effectively deployed on the material design of biomedical polymers, and it is expected to become an extensive driving force to meet the huge demand for customized designs.

Introduction of Materials Genome Technology and Its Applications in the Field of Biomedical Materials

Traditional research and development (R&D) on biomedical materials depends heavily on the trial and error process, thereby leading to huge economic and time burden. Most recently, materials genome technology (MGT) has been recognized as an effective approach to addressing this problem. In this paper, the basic concepts involved in the MGT are introduced, and the applications of MGT in the R&D of metallic, inorganic non-metallic, polymeric, and composite biomedical materials are summarized; in view of the existing limitations of MGT for R&D of biomedical materials, potential strategies are proposed on the establishment and management of material databases, the upgrading of high-throughput experimental technology, the construction of data mining prediction platforms, and the training of relevant materials talents. In the end, future trend of MGT for R&D of biomedical materials is proposed.

Discovery of a polymer resistant to bacterial biofilm, swarming, and encrustation

Innovative approaches to prevent catheter-associated urinary tract infections (CAUTIs) are urgently required. Here, we describe the discovery of an acrylate copolymer capable of resisting single- and multispecies bacterial biofilm formation, swarming, encrustation, and host protein deposition, which are major challenges associated with preventing CAUTIs. After screening ~400 acrylate polymers, poly(tert-butyl cyclohexyl acrylate) was selected for its biofilm- and encrustation-resistant properties. When combined with the swarming inhibitory poly(2-hydroxy-3-phenoxypropyl acrylate), the copolymer retained the bioinstructive properties of the respective homopolymers when challenged with Proteus mirabilis, Pseudomonas aeruginosa, Staphylococcus aureus, and Escherichia coli. Urinary tract catheterization causes the release of host proteins that are exploited by pathogens to colonize catheters. After preconditioning the copolymer with urine collected from patients before and after catheterization, reduced host fibrinogen deposition was observed, and resistance to diverse uropathogens was maintained. These data highlight the potential of the copolymer as a urinary catheter coating for preventing CAUTIs.

Antimicrobial Properties of Plant Fibers

Healthcare-associated infections (HAI), or nosocomial infections, are a global health and economic problem in developed and developing countries, particularly for immunocompromised patients in their intensive care units (ICUs) and surgical site hospital areas. Recurrent pathogens in HAIs prevail over antibiotic-resistant bacteria, such as methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa. For this reason, natural antibacterial mechanisms are a viable alternative for HAI treatment. Natural fibers can inhibit bacterial growth, which can be considered a great advantage in these applications. Moreover, these fibers have been reported to be biocompatible and biodegradable, essential features for biomedical materials to avoid complications due to infections and significant immune responses. Consequently, tissue engineering, medical textiles, orthopedics, and dental implants, as well as cosmetics, are fields currently expanding the use of plant fibers. In this review, we will discuss the source of natural fibers with antimicrobial properties, antimicrobial mechanisms, and their biomedical applications.

Materiomically Designed Polymeric Vehicles for Nucleic Acids: Quo Vadis?

Despite rapid advances in molecular biology, particularly in site-specific genome editing technologies, such as CRISPR/Cas9 and base editing, financial and logistical challenges hinder a broad population from accessing and benefiting from gene therapy. To improve the affordability and scalability of gene therapy, we need to deploy chemically defined, economical, and scalable materials, such as synthetic polymers. For polymers to deliver nucleic acids efficaciously to targeted cells, they must optimally combine design attributes, such as architecture, length, composition, spatial distribution of monomers, basicity, hydrophilic-hydrophobic phase balance, or protonation degree. Designing polymeric vectors for specific nucleic acid payloads is a multivariate optimization problem wherein even minuscule deviations from the optimum are poorly tolerated. To explore the multivariate polymer design space rapidly, efficiently, and fruitfully, we must integrate parallelized polymer synthesis, high-throughput biological screening, and statistical modeling. Although materiomics approaches promise to streamline polymeric vector development, several methodological ambiguities must be resolved. For instance, establishing a flexible polymer ontology that accommodates recent synthetic advances, enforcing uniform polymer characterization and data reporting standards, and implementing multiplexed in vitro and in vivo screening studies require considerable planning, coordination, and effort. This contribution will acquaint readers with the challenges associated with materiomics approaches to polymeric gene delivery and offers guidelines for overcoming these challenges. Here, we summarize recent developments in combinatorial polymer synthesis, high-throughput screening of polymeric vectors, omics-based approaches to polymer design, barcoding schemes for pooled in vitro and in vivo screening, and identify materiomics-inspired research directions that will realize the long-unfulfilled clinical potential of polymeric carriers in gene therapy.

Machine learning approaches for biomolecular, biophysical, and biomaterials research

A fluent conversation with a virtual assistant, person-tailored news feeds, and deep-fake images created within seconds-all those things that have been unthinkable for a long time are now a part of our everyday lives. What these examples have in common is that they are realized by different means of machine learning (ML), a technology that has fundamentally changed many aspects of the modern world. The possibility to process enormous amount of data in multi-hierarchical, digital constructs has paved the way not only for creating intelligent systems but also for obtaining surprising new insight into many scientific problems. However, in the different areas of biosciences, which typically rely heavily on the collection of time-consuming experimental data, applying ML methods is a bit more challenging: Here, difficulties can arise from small datasets and the inherent, broad variability, and complexity associated with studying biological objects and phenomena. In this Review, we give an overview of commonly used ML algorithms (which are often referred to as "machines") and learning strategies as well as their applications in different bio-disciplines such as molecular biology, drug development, biophysics, and biomaterials science. We highlight how selected research questions from those fields were successfully translated into machine readable formats, discuss typical problems that can arise in this context, and provide an overview of how to resolve those encountered difficulties.

Biocompatible Materials in Otorhinolaryngology and Their Antibacterial Properties

For decades, biomaterials have been commonly used in medicine for the replacement of human body tissue, precise drug-delivery systems, or as parts of medical devices that are essential for some treatment methods. Due to rapid progress in the field of new materials, updates on the state of knowledge about biomaterials are frequently needed. This article describes the clinical application of different types of biomaterials in the field of otorhinolaryngology, i.e., head and neck surgery, focusing on their antimicrobial properties. The variety of their applications includes cochlear implants, middle ear prostheses, voice prostheses, materials for osteosynthesis, and nasal packing after nasal/paranasal sinuses surgery. Ceramics, such as as hydroxyapatite, zirconia, or metals and metal alloys, still have applications in the head and neck region. Tissue engineering scaffolds and drug-eluting materials, such as polymers and polymer-based composites, are becoming more common. The restoration of life tissue and the ability to prevent microbial colonization should be taken into consideration when designing the materials to be used for implant production. The authors of this paper have reviewed publications available in PubMed from the last five years about the recent progress in this topic but also establish the state of knowledge of the most common application of biomaterials over the last few decades.

De Novo Design of Entropy-Driven Polymers Resistant to Bacterial Attachment via Multicomponent Reactions

Nonbactericidal polymers that prevent bacterial attachment are important for public health, environmental protection, and avoiding the generation of superbugs. Here, inspired by the physical bactericidal process of carbon nanotubes and graphene derivatives, we develop nonbactericidal polymers resistant to bacterial attachment by using multicomponent reactions (MCRs) to introduce molecular "needles" (rigid aliphatic chains) and molecular "razors" (multicomponent structures) into polymer side chains. Computer simulation reveals the occurrence of spontaneous entropy-driven interactions between the bacterial bilayers and the "needles" and "razors" in polymer structures and provides guidance for the optimization of this type of polymers for enhanced resistibility to bacterial attachment. The blending of the optimized polymer with commercially available polyurethane produces a film with remarkably superior stability of the resistance to bacterial adhesion after wear compared with that of commercial mobile phone shells made by the Sharklet technology. This proof-of-concept study explores entropy-driven polymers resistant to bacterial attachment via a combination of MCRs, computer simulation, and polymer chemistry, paving the way for the de novo design of nonbactericidal polymers to prevent bacterial contamination.

High-Throughput Methods in the Discovery and Study of Biomaterials and Materiobiology

The complex interaction of cells with biomaterials (i.e., materiobiology) plays an increasingly pivotal role in the development of novel implants, biomedical devices, and tissue engineering scaffolds to treat diseases, aid in the restoration of bodily functions, construct healthy tissues, or regenerate diseased ones. However, the conventional approaches are incapable of screening the huge amount of potential material parameter combinations to identify the optimal cell responses and involve a combination of serendipity and many series of trial-and-error experiments. For advanced tissue engineering and regenerative medicine, highly efficient and complex bioanalysis platforms are expected to explore the complex interaction of cells with biomaterials using combinatorial approaches that offer desired complex microenvironments during healing, development, and homeostasis. In this review, we first introduce materiobiology and its high-throughput screening (HTS). Then we present an in-depth of the recent progress of 2D/3D HTS platforms (i.e., gradient and microarray) in the principle, preparation, screening for materiobiology, and combination with other advanced technologies. The Compendium for Biomaterial Transcriptomics and high content imaging, computational simulations, and their translation toward commercial and clinical uses are highlighted. In the final section, current challenges and future perspectives are discussed. High-throughput experimentation within the field of materiobiology enables the elucidation of the relationships between biomaterial properties and biological behavior and thereby serves as a potential tool for accelerating the development of high-performance biomaterials.

Self-Limiting Mussel Inspired Thin Antifouling Coating with Broad-Spectrum Resistance to Biofilm Formation to Prevent Catheter-Associated Infection in Mouse and Porcine Models

Catheter-associated urinary tract infections (CAUTIs) are one of the most commonly occurring hospital-acquired infections. Current coating strategies to prevent catheter-associated biofilm formation are limited by their poor long-term efficiency and limited applicability to diverse materials. Here, the authors report a highly effective non-fouling coating with long-term biofilm prevention activity and is applicable to diverse catheters. The thin coating is lubricous, stable, highly uniform, and shows broad spectrum prevention of biofilm formation of nine different bacterial strains and prevents the migration of bacteria on catheter surface. The coating method is adapted to human-sized catheters (both intraluminal and extraluminal) and demonstrates long-term biofilm prevention activity over 30 days in challenging conditions. The coated catheters are tested in a mouse CAUTI model and demonstrate high efficiency in preventing bacterial colonization of both Gram-positive and Gram-negative bacteria. Furthermore, the coated human-sized Foley catheters are evaluated in a porcine CAUTI model and show consistent efficiency in reducing biofilm formation by Escherichia coli (E. coli) over 95%. The simplicity of the coating method, the ability to apply this coating on diverse materials, and the high efficiency in preventing bacterial adhesion increase the potential of this method for the development of next generation infection resistant medical devices.

Precision Design of Antimicrobial Surfaces

The overall expectation from an antimicrobial surface has been high considering the need for efficiency in preventing the attachment and growth of pathogenic microbes, durability, safety to both humans and environment as well as cost-effectiveness. To date, antimicrobial surface design has been mostly conducted liberally, without rigorous consideration of establishing robust structure-activity relationships for each design strategy or of the use intended for a specific antimicrobial material. However, the variability among the domain bacteria, which is the most diverse of all, alongside the highly dynamic nature of the bacteria-surface interface have taught us that the likelihood of finding universal antimicrobial surfaces is low. In this perspective we discuss some of the current hurdles faced by research in this promising field, emphasizing the relevance and complexity of probing the bacteria-surface interface, and explain why we feel it would greatly benefit from a more streamlined ad-hoc approach.

In Vitro Evaluation of Polihexanide, Octenidine and NaClO/HClO-Based Antiseptics against Biofilm Formed by Wound Pathogens

Chronic wounds complicated with biofilm formed by pathogens remain one of the most significant challenges of contemporary medicine. The application of topical antiseptic solutions against wound biofilm has been gaining increasing interest among clinical practitioners and scientific researchers. This paper compares the activity of polyhexanide-, octenidine- and hypochlorite/hypochlorous acid-based antiseptics against biofilm formed by clinical strains of Candida albicans, Staphylococcus aureus and Pseudomonas aeruginosa. The analyses included both standard techniques utilizing polystyrene plates and self-designed biocellulose-based models in which a biofilm formed by pathogens was formed on an elastic, fibrinous surface covered with a fibroblast layer. The obtained results show high antibiofilm activity of polihexanide- and octenidine-based antiseptics and lack or weak antibiofilm activity of hypochlorite-based antiseptic of total chlorine content equal to 80 parts per million. The data presented in this paper indicate that polihexanide- or octenidine-based antiseptics are highly useful in the treatment of biofilm, while hypochlorite-based antiseptics with low chlorine content may be applied for wound rinsing but not when specific antibiofilm activity is required.

Single-Cell Tracking on Polymer Microarrays Reveals the Impact of Surface Chemistry on Pseudomonas aeruginosa Twitching Speed and Biofilm Development

Bacterial biofilms exhibit up to 1000 times greater resistance to antibiotic or host immune clearance than planktonic cells. Pseudomonas aeruginosa produces retractable type IV pili (T4P) that facilitate twitching motility on surfaces. The deployment of pili is one of the first responses of bacteria to surface interactions and because of their ability to contribute to cell surface adhesion and biofilm formation, this has relevance to medical device-associated infections. While polymer chemistry is known to influence biofilm development, its impact on twitching motility is not understood. Here, we combine a polymer microarray format with time-lapse automated microscopy to simultaneously assess P. aeruginosa twitching motility on 30 different methacrylate/acrylate polymers over 60 min post inoculation using a high-throughput system. During this critical initial period where the decision to form a biofilm is thought to occur, similar numbers of bacterial cells accumulate on each polymer. Twitching motility is observed on all polymers irrespective of their chemistry and physical surface properties, in contrast to the differential biofilm formation noted after 24 h of incubation. However, on the microarray polymers, P. aeruginosa cells twitch at significantly different speeds, ranging from 5 to ∼13 nm/s, associated with crawling or walking and are distinguishable from the different cell surface tilt angles observed. Chemometric analysis using partial least-squares (PLS) regression identifies correlations between surface chemistry, as measured by time-of-flight secondary ion mass spectrometry (ToF-SIMS), and both biofilm formation and single-cell twitching speed. The relationships between surface chemistry and these two responses are different for each process. There is no correlation between polymer surface stiffness and roughness as determined by atomic force measurement (AFM), or water contact angle (WCA), and twitching speed or biofilm formation. This reinforces the dominant and distinct contributions of material surface chemistry to twitching speed and biofilm formation.

Antifibrotic strategies for medical devices

A broad range of medical devices initiate an immune reaction known as the foreign body response (FBR) upon implantation. Here, collagen deposition at the surface of the implant occurs as a result of the FBR, ultimately leading to fibrous encapsulation and, in many cases, reduced function or failure of the device. Despite significant efforts, the prevention of fibrotic encapsulation has not been realized at this point in time. However, many next-generation medical technologies including cellular therapies, sensors and devices depend on the ability to modulate and control the FBR. For these technologies to become viable, significant advances must be made in understanding the underlying mechanism of this response as well as in the methods modulating this response. In this review, we highlight recent advances in the development of materials and coatings providing a reduced FBR and emphasize key characteristics of high-performing approaches. We also provide a detailed overview of the state-of-the-art in strategies relying on controlled drug release, the surface display of bioactive signals, materials-based approaches, and combinations of these approaches. Finally, we offer perspectives on future directions in this field.

Non-leaching, Highly Biocompatible Nanocellulose Surfaces That Efficiently Resist Fouling by Bacteria in an Artificial Dermis Model

Bacterial biofilm infections incur massive costs on healthcare systems worldwide. Particularly worrisome are the infections associated with pressure ulcers and prosthetic, plastic, and reconstructive surgeries, where staphylococci are the major biofilm-forming pathogens. Non-leaching antimicrobial surfaces offer great promise for the design of bioactive coatings to be used in medical devices. However, the vast majority are cationic, which brings about undesirable toxicity. To circumvent this issue, we have developed antimicrobial nanocellulose films by direct functionalization of the surface with dehydroabietic acid derivatives. Our conceptually unique design generates non-leaching anionic surfaces that reduce the number of viable staphylococci in suspension, including drug-resistant Staphylococcus aureus, by an impressive 4-5 log units, upon contact. Moreover, the films clearly prevent bacterial colonization of the surface in a model mimicking the physiological environment in chronic wounds. Their activity is not hampered by high protein content, and they nurture fibroblast growth at the surface without causing significant hemolysis. In this work, we have generated nanocellulose films with indisputable antimicrobial activity demonstrated using state-of-the-art models that best depict an "in vivo scenario". Our approach is to use fully renewable polymers and find suitable alternatives to silver and cationic antimicrobials.

Hyperosmotic Infusion and Oxidized Surfaces Are Essential for Biofilm Formation of Staphylococcus capitis From the Neonatal Intensive Care Unit

Staphylococcus capitis is an opportunistic pathogen often implicated in bloodstream infections in the neonatal intensive care unit (NICU). This is assisted by its ability to form biofilms on indwelling central venous catheters (CVC), which are highly resistant to antibiotics and the immune system. We sought to understand the fundamentals of biofilm formation by S. capitis in the NICU, using seventeen clinical isolates including the endemic NRCS-A clone and assessing nine commercial and two modified polystyrene surfaces. S. capitis clinical isolates from the NICU initiated biofilm formation only in response to hyperosmotic conditions, followed by a developmental progression driven by icaADBC expression to establish mature biofilms, with polysaccharide being their major extracellular polymer substance (EPS) matrix component. Physicochemical features of the biomaterial surface, and in particular the level of the element oxygen present on the surface, significantly influenced biofilm development of S. capitis. A lack of highly oxidized carbon species on the surface prevented the immobilization of S. capitis EPS and the formation of mature biofilms. This information provides guidance in regard to the preparation of hyperosmolar total parenteral nutrition and the engineering of CVC surfaces that can minimize the risk of catheter-related bloodstream infections caused by S. capitis in the NICU.

Nanoscale in silico classification of ligand functionalised surfaces for protein adsorption resistance

Non-specific protein adsorption represents a significant challenge for the design of efficient and safe nanoparticles for biomedical applications since it may prevent functional ligands to target the desired specific receptors which can limit the efficacy of novel drug delivery systems and biosensors. The biofilm formation initiated by protein adsorption on surfaces limits the lifetime and safety of medical implants and tissue regenerative scaffolds. The development of biofouling resistant surfaces is therefore a major goal for the widespread uptake of nanomedicine. Here, we provide a relatively simple computational screening method based on the rational physically grounded criteria that may suffice in selection of surface grafted ligands for protein rejection, and test whether these criteria can be extrapolated from a specific protein to generic protein-resistant surfaces. Using all-atom molecular dynamics simulations we characterise four types of ligand functionalised surfaces at aqueous interfaces in terms of the surface hydrophobicity and ligand dynamics. We demonstrate how our hypothesised interfacial design based on the select physical characteristics of the ligated surfaces can enable the rejection of a protein from the surface. The ligand screening procedure and the detailed atomistic characterisation of the protein rejection process presented suggest that minimizing the adsorption of surface active proteins requires specific surface topographies and ligand chemistries that are able to maximise the entropic penalty associated with the restriction of the ligand dynamics and trapping interfacial water by adsorbed proteins.

Development of dual anti-biofilm and anti-bacterial medical devices

Silicone catheters impregnated with antibiotics and coated with an anti-attachment polyacrylate produce a device with dual anti-biofilm and anti-bacterial properties.

Contact-active antibacterial polyethylene foils via atmospheric air plasma induced polymerisation of quaternary ammonium salts

Polyethylene (PE) foils were modified with potent contact-active antibacterial quaternary ammonium salts (QAS) by an atmospheric air plasma activation step, followed by graft-polymerisation of vinylbenzyltrimethylammonium chloride (VBTAC) monomers. The presented approach uses a cost efficient air plasma activation and subsequent radical polymerisation in highly concentrated aqueous monomer solutions to generate efficient antibacterial materials. The obtained contact-active poly-VBTAC modified PE foils feature a homogeneous and 300 nm thick polymer layer with a high charge density of approximately 10¹⁶ N⁺/cm². The antibacterial properties were evaluated against Gram-negative (P. aeruginosa, E. coli) and Gram-positive (S. aureus, S. epidermidis) bacteria. The materials showed strong antibacterial activity by eradicating all the inoculated bacteria with bacterial challenges of 10⁴ to 10⁵ CFU/cm² and good reductions even at maximum challenge (10⁸ CFU/cm²). We have confirmed contact-activity by an agar diffusion assay. The obtained materials are therefore highly attractive for applications, for example, in packaging and are a contribution to an ecomic and green antimicrobial management without release of biocides to the environment.

Ethylene Glycol Dicyclopentenyl (Meth)Acrylate Homo and Block Copolymers via Nitroxide Mediated Polymerization

Nitroxide-mediated polymerization (NMP), (homo and block copolymerization with styrene (S) and butyl methacrylate/S) of ethylene glycol dicyclopentenyl ether (meth)acrylates (EGDEA and EGDEMA) was studied using BlocBuilder alkoxyamines. EGDEA homopolymerization was not well-controlled, independent of temperature (90-120 °C), or additional free nitroxide (0-10 mol%) used. Number average molecular weights (Mn) achieved for poly(EGDEA) were 4.0-9.5 kg mol-1 and were accompanied by high dispersity (Ð = Mw/Mn = 1.62-2.09). Re-initiation and chain extension of the poly(EGDEA) chains with styrene (S) indicated some block copolymer formation, but a high fraction of chains were terminated irreversibly. EGDEA-stat-S statistical copolymerizations with a low mol fraction S in initial feed, fS,0 = 0.05, were slightly better controlled compared to poly(EGDEA) homopolymerizations (Ð was reduced to 1.44 compared to 1.62 at similar conditions). EGDEMA, in contrast, was successfully polymerized using a small fraction of S (fS,0 ~ 10 mol%) to high conversion (72%) to form well-defined EGDEMA-rich random copolymer (molar composition = FEGDEMA = 0.87) of Mn = 14.3 kg mol-1 and Ð = 1.38. EGDEMA-rich compositions were also polymerized with the unimolecular succinimidyl ester form of BlocBuilder initiator, NHS-BlocBuilder with similar results, although Ðs were higher ~1.6. Chain extensions resulted in monomodal shifts to higher molecular weights, indicating good chain end fidelity.

Biofilm formation - what we can learn from recent developments

Although biofilms have been observed early in the history of microbial research, their impact has only recently been fully recognized. Biofilm infections, which contribute to up to 80% of human microbial infections, are associated with common human disorders, such as diabetes mellitus and poor dental hygiene, but also with medical implants. The associated chronic infections such as wound infections, dental caries and periodontitis significantly enhance morbidity, affect quality of life and can aid development of follow-up diseases such as cancer. Biofilm infections remain challenging to treat and antibiotic monotherapy is often insufficient, although some rediscovered traditional compounds have shown surprising efficiency. Innovative anti-biofilm strategies include application of anti-biofilm small molecules, intrinsic or external stimulation of production of reactive molecules, utilization of materials with antimicrobial properties and dispersion of biofilms by digestion of the extracellular matrix, also in combination with physical biofilm breakdown. Although basic principles of biofilm formation have been deciphered, the molecular understanding of the formation and structural organization of various types of biofilms has just begun to emerge. Basic studies of biofilm physiology have also resulted in an unexpected discovery of cyclic dinucleotide second messengers that are involved in interkingdom crosstalk via specific mammalian receptors. These findings even open up new venues for exploring novel anti-biofilm strategies.