Bacteria primarily exist in robust, surface-associated communities known as biofilms, ubiquitous in both natural and anthropogenic environments. Mature biofilms resist a wide range of antimicrobial treatments and pose persistent pathogenic threats. Treatment of adherent biofilm is difficult, costly, and, in medical systems such as catheters or implants, frequently impossible. At the same time, strategies for biofilm prevention based on surface chemistry treatments or surface microstructure have been found to only transiently affect initial attachment. Here we report that Slippery LiquidInfused Porous Surfaces (SLIPS) prevent 99.6% of Pseudomonas aeruginosa biofilm attachment over a 7-d period, as well as Staphylococcus aureus (97.2%) and Escherichia coli (96%), under both static and physiologically realistic flow conditions. In contrast, both polytetrafluoroethylene and a range of nanostructured superhydrophobic surfaces accumulate biofilm within hours. SLIPS show approximately 35 times the reduction of attached biofilm versus best case scenario, state-of-the-art PEGylated surface, and over a far longer timeframe. We screen for and exclude as a factor cytotoxicity of the SLIPS liquid, a fluorinated oil immobilized on a structured substrate. The inability of biofilm to firmly attach to the surface and its effective removal under mild flow conditions (about 1 cm∕s) are a result of the unique, nonadhesive, "slippery" character of the smooth liquid interface, which does not degrade over the experimental timeframe. We show that SLIPS-based antibiofilm surfaces are stable in submerged, extreme pH, salinity, and UV environments. They are low-cost, passive, simple to manufacture, and can be formed on arbitrary surfaces. We anticipate that our findings will enable a broad range of antibiofilm solutions in the clinical, industrial, and consumer spaces.antifouling surfaces | biofilm resistance | slippery materials | surface engineering
Most of the world's bacteria exist in robust, sessile communities known as biofilms, ubiquitously adherent to environmental surfaces from ocean floors to human teeth and notoriously resistant to antimicrobial agents. We report the surprising observation that Bacillus subtilis biofilm colonies and pellicles are extremely nonwetting, greatly surpassing the repellency of Teflon toward water and lower surface tension liquids. The biofilm surface remains nonwetting against up to 80% ethanol as well as other organic solvents and commercial biocides across a large and clinically important concentration range. We show that this property limits the penetration of antimicrobial liquids into the biofilm, severely compromising their efficacy. To highlight the mechanisms of this phenomenon, we performed experiments with mutant biofilms lacking ECM components and with functionalized polymeric replicas of biofilm microstructure. We show that the nonwetting properties are a synergistic result of ECM composition, multiscale roughness, reentrant topography, and possibly yet other factors related to the dynamic nature of the biofilm surface. Finally, we report the impenetrability of the biofilm surface by gases, implying defense capability against vapor-phase antimicrobials as well. These remarkable properties of B. subtilis biofilm, which may have evolved as a protection mechanism against native environmental threats, provide a new direction in both antimicrobial research and bioinspired liquid-repellent surface paradigms.antimicrobial resistance | microcomputed tomography | biofilm hydrophobicity | liquid repellency | nonwettability
Bio‐inspired, multifunctional, high‐aspect‐ratio nanostructured surfaces are fabricated in a variety of materials with controlled geometry and stiffness. A soft‐lithography method that allows the one‐to‐one replication of nanostructures and renders it possible to produce arbitrary nanostructures with cross‐sectional shapes, orientations, and 2D lattices that are different from the original master is presented. The actuation of the posts is demonstrated.
This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. The vehicle implementation includes many heterogeneous sensors with significant communications and computation bandwidth to capture and process high-resolution, high-rate sensor data. The output of the comprehensive environmental sensing subsystem is fed into a kinodynamic motion planning algorithm to generate all vehicle motion. The requirements of driving in lanes, three-point turns, parking, and maneuvering through obstacle fields are all generated with a unified planner. A key aspect of the planner is its use of closed-loop simulation in a rapidly exploring randomized trees algorithm, which can randomly explore the space while efficiently generating smooth trajectories in a dynamic and uncertain environment. The overall system was realized through the creation of a powerful new suite of software tools for message passing, logging, and visualization. These innovations provide a strong platform for future research in autonomous driving in global positioning system-denied and highly dynamic environments with poor a priori information. C 2008 Wiley Periodicals, Inc.
This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. The vehicle implementation includes many heterogeneous sensors with significant communications and computation bandwidth to capture and process high-resolution, high-rate sensor data. The output of the comprehensive environmental sensing subsystem is fed into a kino-dynamic motion planning algorithm to generate all vehicle motion. The requirements of driving in lanes, three-point turns, parking, and maneuvering through obstacle fields are all generated with a unified planner. A key aspect of the planner is its use of closed-loop simulation in a Rapidly-exploring Randomized Trees (RRT) algorithm, which can randomly explore the space while efficiently generating smooth trajectories in a dynamic and uncertain environment. The overall system was realized through the creation of a powerful new suite of software tools for message-passing, logging, and visualization. These innovations provide a strong platform for future research in autonomous driving in GPS-denied and highly dynamic environments with poor a priori information.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.